Azimuth Observability Enhancement During Inertial Navigation System In-Flight Alignment

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喜马拉雅山区大气与环境综合观测研究支撑青藏高原地球系统科学发展

喜马拉雅山区大气与环境综合观测研究支撑青藏高原地球系统科学发展

中国科学院野外台站CAS Field Station引用格式:马伟强, 马耀明, 谢志鹏, 等. 喜马拉雅山区大气与环境综合观测研究支撑青藏高原地球系统科学发展. 中国科学院院刊, 2023, 38(10): 1561-1571, doi: 10.16418/j.issn.1000-3045.20231008003.Ma W Q, Ma Y M, Xie Z P, et al. Comprehensive atmospheric and environmental observations in the Himalayan region advances development of Earth system science on the Tibetan Plateau. Bulletin of Chinese Academy of Sciences, 2023, 38(10): 1561-1571, doi: 10.16418/j.issn.1000-3045.20231008003. (in Chinese)喜马拉雅山区大气与环境综合观测研究支撑青藏高原地球系统科学发展马伟强1,2马耀明1,2*谢志鹏1,2*陈学龙1,2王宾宾1,2韩存博1,2李茂善2,3仲雷2,4孙方林2,5王忠彦1,2席振华1,2刘莲1,2马彬1,2胡伟1,21 中国科学院青藏高原研究所青藏高原地球系统与资源环境重点实验室北京1001012 中国科学院珠穆朗玛大气与环境综合观测研究站日喀则8582003 成都信息工程大学大气科学学院成都6102254 中国科学技术大学地球和空间科学学院合肥2300265 中国科学院西北生态环境资源研究院兰州730000摘要中国科学院珠穆朗玛大气与环境综合观测研究站(以下简称“珠峰站”)位于珠穆朗玛峰自然保护区核心区域,围绕我国青藏高原生态保护和生态文明高地建设及经济社会可持续发展的国家战略科技需求,致力于地球“第三极”复杂地形山地大气过程和环境变化研究。

超高压辅助胶束法提取落叶松中二氢槲皮素的工艺优化

超高压辅助胶束法提取落叶松中二氢槲皮素的工艺优化

杨帆,霍志伟,朱雯,等. 超高压辅助胶束法提取落叶松中二氢槲皮素的工艺优化[J]. 食品工业科技,2023,44(23):175−183. doi:10.13386/j.issn1002-0306.2023020026YANG Fan, HUO Zhiwei, ZHU Wen, et al. Optimization of Ultrahigh Pressure Assisted Micellar Extraction of Taxifolin from Larch[J]. Science and Technology of Food Industry, 2023, 44(23): 175−183. (in Chinese with English abstract). doi:10.13386/j.issn1002-0306.2023020026· 工艺技术 ·超高压辅助胶束法提取落叶松中二氢槲皮素的工艺优化杨 帆,霍志伟,朱 雯,赵修华*(东北林业大学化学化工与资源利用学院,黑龙江哈尔滨 150040)摘 要:为简化二氢槲皮素提取工艺,降低能耗与成本,提高提取效率,促进二氢槲皮素的综合应用,本研究采用黑龙江省的兴安落叶松为原料,运用超高压辅助胶束提取技术提取落叶松中二氢槲皮素,测定落叶松树根、树干等不同部位的二氢槲皮素总含量。

以此总含量为基础,对提取胶束进行筛选,采用响应面试验对提取工艺进行优化,考察了料液比、提取压力、提取次数及胶束浓度4种不同因素对二氢槲皮素提取率的影响,并与微波提取、超声提取、回流提取等不同提取工艺进行能耗与CO 2排放比较。

结果表明,最终确定提取胶束为茶皂素,最佳提取工艺条件为:茶皂素浓度8%,料液比1:11.5,提取压力157 MPa ,提取次数3次,保压时间5 min ,在此最佳条件下重复进行3次实验,二氢槲皮素实际提取率可达84.35%±1.20%,与预测值84.98%基本一致。

MEWS评分在急诊留观患者护理决策中的作用分析

MEWS评分在急诊留观患者护理决策中的作用分析

MEWS评分在急诊留观患者护理决策中的作用分析一、MEWS评分的概念简化急诊患者危重度评估(Modified Early Warning Score,MEWS)是一种通过观察生命体征来评估患者病情变化的评分系统。

MEWS评分包括呼吸频率、心率、收缩压、体温和意识状态五个指标,通过对这些指标进行评分,并将评分结果相加,来评估患者的病情变化程度。

当评分结果高于一定阈值时,就需要及时采取相应的护理措施,以避免患者病情的进一步恶化。

MEWS评分系统简单易行、操作方便,因此在临床中得到了广泛的使用。

二、MEWS评分在急诊留观患者护理决策中的作用1. 及时发现患者病情变化在急诊留观患者的护理过程中,患者病情的变化可能随时发生,而且有些变化可能相当微弱,容易被忽略。

通过对患者进行定期的MEWS评分,可以及时监测患者的生命体征指标,并将评分结果及时记录在案。

一旦发现患者的MEWS评分升高,就可以及时采取护理措施,以防止患者病情的进一步恶化。

MEWS评分在急诊留观患者护理决策中可以起到及时发现患者病情变化的作用。

2. 提高护理质量MEWS评分可以帮助医护人员及时发现患者的病情变化,有利于提高护理质量。

通过对患者进行定期的MEWS评分,可以及时发现患者的病情变化,及时采取相应的护理措施,有利于减少医疗事故的发生,提高医疗质量和护理效果。

3. 促进医护人员间的交流在急诊留观患者的护理决策中,医护人员之间的交流配合是至关重要的。

通过对患者进行定期的MEWS评分,可以使医护人员更好地了解患者的病情变化情况,并及时进行交流,共同制定护理方案,有利于提高医护人员之间的沟通和配合,促进医护团队的协作效率。

三、MEWS评分在急诊留观患者护理决策中的局限性1. 评分标准不够客观MEWS评分系统主要通过对患者的生命体征指标进行评分,存在一定的主观性。

不同的医护人员可能会对患者的生命体征指标进行评判时存在主观性,因此可能会对评分结果产生一定的误差。

外文翻译---一种确定大气垂直折光系数的新方法

外文翻译---一种确定大气垂直折光系数的新方法

附录A VERTICAL ATMOSPHERIC REFRACTION COEFFICIENT TODETERMINE NEW WAYS OFFRIST.interoductionA long time, trigonometric leveling observations in many types of geodetic measurement concept is considered a class of low precision, the reason for this is because of the vast numbers of measurements so far have not found work well to eliminate the impact of a trigonometric leveling a major factor in the accuracy of the methods and measures, thus limiting this approach in the elevation measurement. We know that, in addition to observational error, the impact of trigonometric leveling is a major factor in the accuracy of the vertical atmospheric refraction and vertical deviation, when the distance is longer, the accuracy of trigonometric leveling is mainly affected by the effects of atmospheric refraction vertical. Therefore,Many workers have long been measured in the study to determine the vertical atmospheric refraction coefficient method. Long-term studies have shown that analysis of radio field as a result of the atmosphere of time and space with the rapidly changing, especially in recent changes in surface temperature gradient is very large, in order to establish a universal and practical model to eliminate or accurate atmospheric correction of the effects of the vertical refractive index is very difficult and even almost impossible. In recent years, with the continuous development of measuring instruments and updating, especially the precision range finder trigonometric leveling in the application, causing a number of scholars on the refractive index of Geodesy more in-depth research.SECOND, atmospheric vertical refraction coefficientWe know that the density of light through the medium non-uniform refraction will occur, so that light into a complex of both curvature and torsion ofspace curves. In the survey, because the temperature in time and space changes in the density of the atmosphere have also taken place in time and space changes, so the speed of light waves, amplitude, phase and propagation direction are randomly generated impact. In light of such properties, it is difficult to even make it almost impossible to use a general model useful to describe the light in。

砂质碎屑流沉积研究进展

砂质碎屑流沉积研究进展

砂质碎屑流沉积研究进展摘要:国外深水沉积发展了50年,从浊流定义的普遍应用,到今天对鲍马序列、约克扇等经典模式持否定态度,深水沉积研究经历了一个推陈出新的过程。

目前国外流行的砂质碎屑流理论是经典浊流理论的部分否定与新发展。

本问阐述国外砂质碎屑流的概念、鉴别特征、沉积模式等最新认识,以运用砂质碎屑流理论解释鄂尔多斯盆地湖盆中部厚砂岩的成因机制为例,揭示我国陆相湖盆中心坡折带砂体分布特征与形成机制,为开拓陆相勘探领域提供理论支撑。

关键字:深水沉积浊流砂质碎屑流深水块状砂岩鄂尔多斯盆地砂质碎屑流最先由美籍印度人G.Shanmugam博士提出,早在1996年,他就挑战传统浊流观点,在Journal of Sedimentary Research上发表了“High-density turbidity currents : are they sandy debris flows ?”一文[1],提出在深水区发育大规模砂质碎屑流的新认识,此后又陆续发表多篇研究论文[2-3],在全球沉积界引起了广泛关注, 目前砂质碎屑流的研究成果代表了深水重力流最新的研究进展。

1、研究背景浊流的概念在过去60多年的重力流研究中影响深远[3-4],然而,浊流概念体系因只建立在沉积相模型上而存有缺陷,如经典浊流的“鲍马序列”[5]以及高密度浊流或粗粒浊流的“Lowe 序列”[6]。

这些模式没有从现代海洋“砂质浊流”中获得过经验数据,仅通过露头研究了古代岩心,尤其是还没有人能够通过不同沉积物浓度和粒度的实验证实现代海洋中能产生真实的砾石级浊流和砂质浊流[3-4],也无人能通过实验室水槽实验证实浊流能够通过悬浮机制运载砂或砾石,并产生垂相的浊流相模式。

虽然存在上述问题,但由于认识误区的存在,浊流概念还是日渐流行[7]。

其实,自鲍玛序列一提出来就曾受到过批评[17-19],只是没有引起注意。

Shanmugam作为反对派“弱势群体”的一方对鲍玛序列的批判只是敢于站出来的一个代表,诚如Miall[20]所说:“因为我们在潜意识中对鲍玛浊积岩都有一个自认为很好的定义,这样就不难解释为什么许多沉积学描述和解释都偏离了方向,直到像Shanmugam之类的人出现并带来了新看法,说明深海砂岩并不等于浊积岩。

ABSTRACT Progressive Simplicial Complexes

ABSTRACT Progressive Simplicial Complexes

Progressive Simplicial Complexes Jovan Popovi´c Hugues HoppeCarnegie Mellon University Microsoft ResearchABSTRACTIn this paper,we introduce the progressive simplicial complex(PSC) representation,a new format for storing and transmitting triangu-lated geometric models.Like the earlier progressive mesh(PM) representation,it captures a given model as a coarse base model together with a sequence of refinement transformations that pro-gressively recover detail.The PSC representation makes use of a more general refinement transformation,allowing the given model to be an arbitrary triangulation(e.g.any dimension,non-orientable, non-manifold,non-regular),and the base model to always consist of a single vertex.Indeed,the sequence of refinement transforma-tions encodes both the geometry and the topology of the model in a unified multiresolution framework.The PSC representation retains the advantages of PM’s.It defines a continuous sequence of approx-imating models for runtime level-of-detail control,allows smooth transitions between any pair of models in the sequence,supports progressive transmission,and offers a space-efficient representa-tion.Moreover,by allowing changes to topology,the PSC sequence of approximations achieves betterfidelity than the corresponding PM sequence.We develop an optimization algorithm for constructing PSC representations for graphics surface models,and demonstrate the framework on models that are both geometrically and topologically complex.CR Categories:I.3.5[Computer Graphics]:Computational Geometry and Object Modeling-surfaces and object representations.Additional Keywords:model simplification,level-of-detail representa-tions,multiresolution,progressive transmission,geometry compression.1INTRODUCTIONModeling and3D scanning systems commonly give rise to triangle meshes of high complexity.Such meshes are notoriously difficult to render,store,and transmit.One approach to speed up rendering is to replace a complex mesh by a set of level-of-detail(LOD) approximations;a detailed mesh is used when the object is close to the viewer,and coarser approximations are substituted as the object recedes[6,8].These LOD approximations can be precomputed Work performed while at Microsoft Research.Email:jovan@,hhoppe@Web:/jovan/Web:/hoppe/automatically using mesh simplification methods(e.g.[2,10,14,20,21,22,24,27]).For efficient storage and transmission,meshcompression schemes[7,26]have also been developed.The recently introduced progressive mesh(PM)representa-tion[13]provides a unified solution to these problems.In PM form,an arbitrary mesh M is stored as a coarse base mesh M0together witha sequence of n detail records that indicate how to incrementally re-fine M0into M n=M(see Figure7).Each detail record encodes theinformation associated with a vertex split,an elementary transfor-mation that adds one vertex to the mesh.In addition to defininga continuous sequence of approximations M0M n,the PM rep-resentation supports smooth visual transitions(geomorphs),allowsprogressive transmission,and makes an effective mesh compressionscheme.The PM representation has two restrictions,however.First,it canonly represent meshes:triangulations that correspond to orientable12-dimensional manifolds.Triangulated2models that cannot be rep-resented include1-d manifolds(open and closed curves),higherdimensional polyhedra(e.g.triangulated volumes),non-orientablesurfaces(e.g.M¨o bius strips),non-manifolds(e.g.two cubes joinedalong an edge),and non-regular models(i.e.models of mixed di-mensionality).Second,the expressiveness of the PM vertex splittransformations constrains all meshes M0M n to have the same topological type.Therefore,when M is topologically complex,the simplified base mesh M0may still have numerous triangles(Fig-ure7).In contrast,a number of existing simplification methods allowtopological changes as the model is simplified(Section6).Ourwork is inspired by vertex unification schemes[21,22],whichmerge vertices of the model based on geometric proximity,therebyallowing genus modification and component merging.In this paper,we introduce the progressive simplicial complex(PSC)representation,a generalization of the PM representation thatpermits topological changes.The key element of our approach isthe introduction of a more general refinement transformation,thegeneralized vertex split,that encodes changes to both the geometryand topology of the model.The PSC representation expresses anarbitrary triangulated model M(e.g.any dimension,non-orientable,non-manifold,non-regular)as the result of successive refinementsapplied to a base model M1that always consists of a single vertex (Figure8).Thus both geometric and topological complexity are recovered progressively.Moreover,the PSC representation retains the advantages of PM’s,including continuous LOD,geomorphs, progressive transmission,and model compression.In addition,we develop an optimization algorithm for construct-ing a PSC representation from a given model,as described in Sec-tion4.1The particular parametrization of vertex splits in[13]assumes that mesh triangles are consistently oriented.2Throughout this paper,we use the words“triangulated”and“triangula-tion”in the general dimension-independent sense.Figure 1:Illustration of a simplicial complex K and some of its subsets.2BACKGROUND2.1Concepts from algebraic topologyTo precisely define both triangulated models and their PSC repre-sentations,we find it useful to introduce some elegant abstractions from algebraic topology (e.g.[15,25]).The geometry of a triangulated model is denoted as a tuple (K V )where the abstract simplicial complex K is a combinatorial structure specifying the adjacency of vertices,edges,triangles,etc.,and V is a set of vertex positions specifying the shape of the model in 3.More precisely,an abstract simplicial complex K consists of a set of vertices 1m together with a set of non-empty subsets of the vertices,called the simplices of K ,such that any set consisting of exactly one vertex is a simplex in K ,and every non-empty subset of a simplex in K is also a simplex in K .A simplex containing exactly d +1vertices has dimension d and is called a d -simplex.As illustrated pictorially in Figure 1,the faces of a simplex s ,denoted s ,is the set of non-empty subsets of s .The star of s ,denoted star(s ),is the set of simplices of which s is a face.The children of a d -simplex s are the (d 1)-simplices of s ,and its parents are the (d +1)-simplices of star(s ).A simplex with exactly one parent is said to be a boundary simplex ,and one with no parents a principal simplex .The dimension of K is the maximum dimension of its simplices;K is said to be regular if all its principal simplices have the same dimension.To form a triangulation from K ,identify its vertices 1m with the standard basis vectors 1m ofm.For each simplex s ,let the open simplex smdenote the interior of the convex hull of its vertices:s =m:jmj =1j=1jjsThe topological realization K is defined as K =K =s K s .The geometric realization of K is the image V (K )where V :m 3is the linear map that sends the j -th standard basis vector jm to j 3.Only a restricted set of vertex positions V =1m lead to an embedding of V (K )3,that is,prevent self-intersections.The geometric realization V (K )is often called a simplicial complex or polyhedron ;it is formed by an arbitrary union of points,segments,triangles,tetrahedra,etc.Note that there generally exist many triangulations (K V )for a given polyhedron.(Some of the vertices V may lie in the polyhedron’s interior.)Two sets are said to be homeomorphic (denoted =)if there ex-ists a continuous one-to-one mapping between them.Equivalently,they are said to have the same topological type .The topological realization K is a d-dimensional manifold without boundary if for each vertex j ,star(j )=d .It is a d-dimensional manifold if each star(v )is homeomorphic to either d or d +,where d +=d:10.Two simplices s 1and s 2are d-adjacent if they have a common d -dimensional face.Two d -adjacent (d +1)-simplices s 1and s 2are manifold-adjacent if star(s 1s 2)=d +1.Figure 2:Illustration of the edge collapse transformation and its inverse,the vertex split.Transitive closure of 0-adjacency partitions K into connected com-ponents .Similarly,transitive closure of manifold-adjacency parti-tions K into manifold components .2.2Review of progressive meshesIn the PM representation [13],a mesh with appearance attributes is represented as a tuple M =(K V D S ),where the abstract simpli-cial complex K is restricted to define an orientable 2-dimensional manifold,the vertex positions V =1m determine its ge-ometric realization V (K )in3,D is the set of discrete material attributes d f associated with 2-simplices f K ,and S is the set of scalar attributes s (v f )(e.g.normals,texture coordinates)associated with corners (vertex-face tuples)of K .An initial mesh M =M n is simplified into a coarser base mesh M 0by applying a sequence of n successive edge collapse transforma-tions:(M =M n )ecol n 1ecol 1M 1ecol 0M 0As shown in Figure 2,each ecol unifies the two vertices of an edgea b ,thereby removing one or two triangles.The position of the resulting unified vertex can be arbitrary.Because the edge collapse transformation has an inverse,called the vertex split transformation (Figure 2),the process can be reversed,so that an arbitrary mesh M may be represented as a simple mesh M 0together with a sequence of n vsplit records:M 0vsplit 0M 1vsplit 1vsplit n 1(M n =M )The tuple (M 0vsplit 0vsplit n 1)forms a progressive mesh (PM)representation of M .The PM representation thus captures a continuous sequence of approximations M 0M n that can be quickly traversed for interac-tive level-of-detail control.Moreover,there exists a correspondence between the vertices of any two meshes M c and M f (0c f n )within this sequence,allowing for the construction of smooth vi-sual transitions (geomorphs)between them.A sequence of such geomorphs can be precomputed for smooth runtime LOD.In addi-tion,PM’s support progressive transmission,since the base mesh M 0can be quickly transmitted first,followed the vsplit sequence.Finally,the vsplit records can be encoded concisely,making the PM representation an effective scheme for mesh compression.Topological constraints Because the definitions of ecol and vsplit are such that they preserve the topological type of the mesh (i.e.all K i are homeomorphic),there is a constraint on the min-imum complexity that K 0may achieve.For instance,it is known that the minimal number of vertices for a closed genus g mesh (ori-entable 2-manifold)is (7+(48g +1)12)2if g =2(10if g =2)[16].Also,the presence of boundary components may further constrain the complexity of K 0.Most importantly,K may consist of a number of components,and each is required to appear in the base mesh.For example,the meshes in Figure 7each have 117components.As evident from the figure,the geometry of PM meshes may deteriorate severely as they approach topological lower bound.M 1;100;(1)M 10;511;(7)M 50;4656;(12)M 200;1552277;(28)M 500;3968690;(58)M 2000;14253219;(108)M 5000;029010;(176)M n =34794;0068776;(207)Figure 3:Example of a PSC representation.The image captions indicate the number of principal 012-simplices respectively and the number of connected components (in parenthesis).3PSC REPRESENTATION 3.1Triangulated modelsThe first step towards generalizing PM’s is to let the PSC repre-sentation encode more general triangulated models,instead of just meshes.We denote a triangulated model as a tuple M =(K V D A ).The abstract simplicial complex K is not restricted to 2-manifolds,but may in fact be arbitrary.To represent K in memory,we encode the incidence graph of the simplices using the following linked structures (in C++notation):struct Simplex int dim;//0=vertex,1=edge,2=triangle,...int id;Simplex*children[MAXDIM+1];//[0..dim]List<Simplex*>parents;;To render the model,we draw only the principal simplices ofK ,denoted (K )(i.e.vertices not adjacent to edges,edges not adjacent to triangles,etc.).The discrete attributes D associate amaterial identifier d s with each simplex s(K ).For the sake of simplicity,we avoid explicitly storing surface normals at “corners”(using a set S )as done in [13].Instead we let the material identifier d s contain a smoothing group field [28],and let a normal discontinuity (crease )form between any pair of adjacent triangles with different smoothing groups.Previous vertex unification schemes [21,22]render principal simplices of dimension 0and 1(denoted 01(K ))as points and lines respectively with fixed,device-dependent screen widths.To better approximate the model,we instead define a set A that associates an area a s A with each simplex s 01(K ).We think of a 0-simplex s 00(K )as approximating a sphere with area a s 0,and a 1-simplex s 1=j k 1(K )as approximating a cylinder (with axis (j k ))of area a s 1.To render a simplex s 01(K ),we determine the radius r model of the corresponding sphere or cylinder in modeling space,and project the length r model to obtain the radius r screen in screen pixels.Depending on r screen ,we render the simplex as a polygonal sphere or cylinder with radius r model ,a 2D point or line with thickness 2r screen ,or do not render it at all.This choice based on r screen can be adjusted to mitigate the overhead of introducing polygonal representations of spheres and cylinders.As an example,Figure 3shows an initial model M of 68,776triangles.One of its approximations M 500is a triangulated model with 3968690principal 012-simplices respectively.3.2Level-of-detail sequenceAs in progressive meshes,from a given triangulated model M =M n ,we define a sequence of approximations M i :M 1op 1M 2op 2M n1op n 1M nHere each model M i has exactly i vertices.The simplification op-erator M ivunify iM i +1is the vertex unification transformation,whichmerges two vertices (Section 3.3),and its inverse M igvspl iM i +1is the generalized vertex split transformation (Section 3.4).Thetuple (M 1gvspl 1gvspl n 1)forms a progressive simplicial complex (PSC)representation of M .To construct a PSC representation,we first determine a sequence of vunify transformations simplifying M down to a single vertex,as described in Section 4.After reversing these transformations,we renumber the simplices in the order that they are created,so thateach gvspl i (a i)splits the vertex a i K i into two vertices a i i +1K i +1.As vertices may have different positions in the different models,we denote the position of j in M i as i j .To better approximate a surface model M at lower complexity levels,we initially associate with each (principal)2-simplex s an area a s equal to its triangle area in M .Then,as the model is simplified,wekeep constant the sum of areas a s associated with principal simplices within each manifold component.When2-simplices are eventually reduced to principal1-simplices and0-simplices,their associated areas will provide good estimates of the original component areas.3.3Vertex unification transformationThe transformation vunify(a i b i midp i):M i M i+1takes an arbitrary pair of vertices a i b i K i+1(simplex a i b i need not be present in K i+1)and merges them into a single vertex a i K i. Model M i is created from M i+1by updating each member of the tuple(K V D A)as follows:K:References to b i in all simplices of K are replaced by refer-ences to a i.More precisely,each simplex s in star(b i)K i+1is replaced by simplex(s b i)a i,which we call the ancestor simplex of s.If this ancestor simplex already exists,s is deleted.V:Vertex b is deleted.For simplicity,the position of the re-maining(unified)vertex is set to either the midpoint or is left unchanged.That is,i a=(i+1a+i+1b)2if the boolean parameter midp i is true,or i a=i+1a otherwise.D:Materials are carried through as expected.So,if after the vertex unification an ancestor simplex(s b i)a i K i is a new principal simplex,it receives its material from s K i+1if s is a principal simplex,or else from the single parent s a i K i+1 of s.A:To maintain the initial areas of manifold components,the areasa s of deleted principal simplices are redistributed to manifold-adjacent neighbors.More concretely,the area of each princi-pal d-simplex s deleted during the K update is distributed toa manifold-adjacent d-simplex not in star(a ib i).If no suchneighbor exists and the ancestor of s is a principal simplex,the area a s is distributed to that ancestor simplex.Otherwise,the manifold component(star(a i b i))of s is being squashed be-tween two other manifold components,and a s is discarded. 3.4Generalized vertex split transformation Constructing the PSC representation involves recording the infor-mation necessary to perform the inverse of each vunify i.This inverse is the generalized vertex split gvspl i,which splits a0-simplex a i to introduce an additional0-simplex b i.(As mentioned previously, renumbering of simplices implies b i i+1,so index b i need not be stored explicitly.)Each gvspl i record has the formgvspl i(a i C K i midp i()i C D i C A i)and constructs model M i+1from M i by updating the tuple (K V D A)as follows:K:As illustrated in Figure4,any simplex adjacent to a i in K i can be the vunify result of one of four configurations in K i+1.To construct K i+1,we therefore replace each ancestor simplex s star(a i)in K i by either(1)s,(2)(s a i)i+1,(3)s and(s a i)i+1,or(4)s,(s a i)i+1and s i+1.The choice is determined by a split code associated with s.Thesesplit codes are stored as a code string C Ki ,in which the simplicesstar(a i)are sortedfirst in order of increasing dimension,and then in order of increasing simplex id,as shown in Figure5. V:The new vertex is assigned position i+1i+1=i ai+()i.Theother vertex is given position i+1ai =i ai()i if the boolean pa-rameter midp i is true;otherwise its position remains unchanged.D:The string C Di is used to assign materials d s for each newprincipal simplex.Simplices in C Di ,as well as in C Aibelow,are sorted by simplex dimension and simplex id as in C Ki. A:During reconstruction,we are only interested in the areas a s fors01(K).The string C Ai tracks changes in these areas.Figure4:Effects of split codes on simplices of various dimensions.code string:41422312{}Figure5:Example of split code encoding.3.5PropertiesLevels of detail A graphics application can efficiently transitionbetween models M1M n at runtime by performing a sequence ofvunify or gvspl transformations.Our current research prototype wasnot designed for efficiency;it attains simplification rates of about6000vunify/sec and refinement rates of about5000gvspl/sec.Weexpect that a careful redesign using more efficient data structureswould significantly improve these rates.Geomorphs As in the PM representation,there exists a corre-spondence between the vertices of the models M1M n.Given acoarser model M c and afiner model M f,1c f n,each vertexj K f corresponds to a unique ancestor vertex f c(j)K cfound by recursively traversing the ancestor simplex relations:f c(j)=j j cf c(a j1)j cThis correspondence allows the creation of a smooth visual transi-tion(geomorph)M G()such that M G(1)equals M f and M G(0)looksidentical to M c.The geomorph is defined as the modelM G()=(K f V G()D f A G())in which each vertex position is interpolated between its originalposition in V f and the position of its ancestor in V c:Gj()=()fj+(1)c f c(j)However,we must account for the special rendering of principalsimplices of dimension0and1(Section3.1).For each simplexs01(K f),we interpolate its area usinga G s()=()a f s+(1)a c swhere a c s=0if s01(K c).In addition,we render each simplexs01(K c)01(K f)using area a G s()=(1)a c s.The resultinggeomorph is visually smooth even as principal simplices are intro-duced,removed,or change dimension.The accompanying video demonstrates a sequence of such geomorphs.Progressive transmission As with PM’s,the PSC representa-tion can be progressively transmitted by first sending M 1,followed by the gvspl records.Unlike the base mesh of the PM,M 1always consists of a single vertex,and can therefore be sent in a fixed-size record.The rendering of lower-dimensional simplices as spheres and cylinders helps to quickly convey the overall shape of the model in the early stages of transmission.Model compression Although PSC gvspl are more general than PM vsplit transformations,they offer a surprisingly concise representation of M .Table 1lists the average number of bits re-quired to encode each field of the gvspl records.Using arithmetic coding [30],the vertex id field a i requires log 2i bits,and the boolean parameter midp i requires 0.6–0.9bits for our models.The ()i delta vector is quantized to 16bitsper coordinate (48bits per),and stored as a variable-length field [7,13],requiring about 31bits on average.At first glance,each split code in the code string C K i seems to have 4possible outcomes (except for the split code for 0-simplex a i which has only 2possible outcomes).However,there exist constraints between these split codes.For example,in Figure 5,the code 1for 1-simplex id 1implies that 2-simplex id 1also has code 1.This in turn implies that 1-simplex id 2cannot have code 2.Similarly,code 2for 1-simplex id 3implies a code 2for 2-simplex id 2,which in turn implies that 1-simplex id 4cannot have code 1.These constraints,illustrated in the “scoreboard”of Figure 6,can be summarized using the following two rules:(1)If a simplex has split code c12,all of its parents havesplit code c .(2)If a simplex has split code 3,none of its parents have splitcode 4.As we encode split codes in C K i left to right,we apply these two rules (and their contrapositives)transitively to constrain the possible outcomes for split codes yet to be ing arithmetic coding with uniform outcome probabilities,these constraints reduce the code string length in Figure 6from 15bits to 102bits.In our models,the constraints reduce the code string from 30bits to 14bits on average.The code string is further reduced using a non-uniform probability model.We create an array T [0dim ][015]of encoding tables,indexed by simplex dimension (0..dim)and by the set of possible (constrained)split codes (a 4-bit mask).For each simplex s ,we encode its split code c using the probability distribution found in T [s dim ][s codes mask ].For 2-dimensional models,only 10of the 48tables are non-trivial,and each table contains at most 4probabilities,so the total size of the probability model is small.These encoding tables reduce the code strings to approximately 8bits as shown in Table 1.By comparison,the PM representation requires approximately 5bits for the same information,but of course it disallows topological changes.To provide more intuition for the efficiency of the PSC repre-sentation,we note that capturing the connectivity of an average 2-manifold simplicial complex (n vertices,3n edges,and 2n trian-gles)requires ni =1(log 2i +8)n (log 2n +7)bits with PSC encoding,versus n (12log 2n +95)bits with a traditional one-way incidence graph representation.For improved compression,it would be best to use a hybrid PM +PSC representation,in which the more concise PM vertex split encoding is used when the local neighborhood is an orientableFigure 6:Constraints on the split codes for the simplices in the example of Figure 5.Table 1:Compression results and construction times.Object#verts Space required (bits/n )Trad.Con.n K V D Arepr.time a i C K i midp i (v )i C D i C Ai bits/n hrs.drumset 34,79412.28.20.928.1 4.10.453.9146.1 4.3destroyer 83,79913.38.30.723.1 2.10.347.8154.114.1chandelier 36,62712.47.60.828.6 3.40.853.6143.6 3.6schooner 119,73413.48.60.727.2 2.5 1.353.7148.722.2sandal 4,6289.28.00.733.4 1.50.052.8123.20.4castle 15,08211.0 1.20.630.70.0-43.5-0.5cessna 6,7959.67.60.632.2 2.50.152.6132.10.5harley 28,84711.97.90.930.5 1.40.453.0135.7 3.52-dimensional manifold (this occurs on average 93%of the time in our examples).To compress C D i ,we predict the material for each new principalsimplex sstar(a i )star(b i )K i +1by constructing an ordered set D s of materials found in star(a i )K i .To improve the coding model,the first materials in D s are those of principal simplices in star(s )K i where s is the ancestor of s ;the remainingmaterials in star(a i )K i are appended to D s .The entry in C D i associated with s is the index of its material in D s ,encoded arithmetically.If the material of s is not present in D s ,it is specified explicitly as a global index in D .We encode C A i by specifying the area a s for each new principalsimplex s 01(star(a i )star(b i ))K i +1.To account for this redistribution of area,we identify the principal simplex from which s receives its area by specifying its index in 01(star(a i ))K i .The column labeled in Table 1sums the bits of each field of the gvspl records.Multiplying by the number n of vertices in M gives the total number of bits for the PSC representation of the model (e.g.500KB for the destroyer).By way of compari-son,the next column shows the number of bits per vertex required in a traditional “IndexedFaceSet”representation,with quantization of 16bits per coordinate and arithmetic coding of face materials (3n 16+2n 3log 2n +materials).4PSC CONSTRUCTIONIn this section,we describe a scheme for iteratively choosing pairs of vertices to unify,in order to construct a PSC representation.Our algorithm,a generalization of [13],is time-intensive,seeking high quality approximations.It should be emphasized that many quality metrics are possible.For instance,the quadric error metric recently introduced by Garland and Heckbert [9]provides a different trade-off of execution speed and visual quality.As in [13,20],we first compute a cost E for each candidate vunify transformation,and enter the candidates into a priority queueordered by ascending cost.Then,in each iteration i =n 11,we perform the vunify at the front of the queue and update the costs of affected candidates.4.1Forming set of candidate vertex pairs In principle,we could enter all possible pairs of vertices from M into the priority queue,but this would be prohibitively expensive since simplification would then require at least O(n2log n)time.Instead, we would like to consider only a smaller set of candidate vertex pairs.Naturally,should include the1-simplices of K.Additional pairs should also be included in to allow distinct connected com-ponents of M to merge and to facilitate topological changes.We considered several schemes for forming these additional pairs,in-cluding binning,octrees,and k-closest neighbor graphs,but opted for the Delaunay triangulation because of its adaptability on models containing components at different scales.We compute the Delaunay triangulation of the vertices of M, represented as a3-dimensional simplicial complex K DT.We define the initial set to contain both the1-simplices of K and the subset of1-simplices of K DT that connect vertices in different connected components of K.During the simplification process,we apply each vertex unification performed on M to as well in order to keep consistent the set of candidate pairs.For models in3,star(a i)has constant size in the average case,and the overall simplification algorithm requires O(n log n) time.(In the worst case,it could require O(n2log n)time.)4.2Selecting vertex unifications fromFor each candidate vertex pair(a b),the associated vunify(a b):M i M i+1is assigned the costE=E dist+E disc+E area+E foldAs in[13],thefirst term is E dist=E dist(M i)E dist(M i+1),where E dist(M)measures the geometric accuracy of the approximate model M.Conceptually,E dist(M)approximates the continuous integralMd2(M)where d(M)is the Euclidean distance of the point to the closest point on M.We discretize this integral by defining E dist(M)as the sum of squared distances to M from a dense set of points X sampled from the original model M.We sample X from the set of principal simplices in K—a strategy that generalizes to arbitrary triangulated models.In[13],E disc(M)measures the geometric accuracy of disconti-nuity curves formed by a set of sharp edges in the mesh.For the PSC representation,we generalize the concept of sharp edges to that of sharp simplices in K—a simplex is sharp either if it is a boundary simplex or if two of its parents are principal simplices with different material identifiers.The energy E disc is defined as the sum of squared distances from a set X disc of points sampled from sharp simplices to the discontinuity components from which they were sampled.Minimization of E disc therefore preserves the geom-etry of material boundaries,normal discontinuities(creases),and triangulation boundaries(including boundary curves of a surface and endpoints of a curve).We have found it useful to introduce a term E area that penalizes surface stretching(a more sophisticated version of the regularizing E spring term of[13]).Let A i+1N be the sum of triangle areas in the neighborhood star(a i)star(b i)K i+1,and A i N the sum of triangle areas in star(a i)K i.The mean squared displacement over the neighborhood N due to the change in area can be approx-imated as disp2=12(A i+1NA iN)2.We let E area=X N disp2,where X N is the number of points X projecting in the neighborhood. To prevent model self-intersections,the last term E fold penalizes surface folding.We compute the rotation of each oriented triangle in the neighborhood due to the vertex unification(as in[10,20]).If any rotation exceeds a threshold angle value,we set E fold to a large constant.Unlike[13],we do not optimize over the vertex position i a, but simply evaluate E for i a i+1a i+1b(i+1a+i+1b)2and choose the best one.This speeds up the optimization,improves model compression,and allows us to introduce non-quadratic energy terms like E area.5RESULTSTable1gives quantitative results for the examples in thefigures and in the video.Simplification times for our prototype are measured on an SGI Indigo2Extreme(150MHz R4400).Although these times may appear prohibitive,PSC construction is an off-line task that only needs to be performed once per model.Figure9highlights some of the benefits of the PSC representa-tion.The pearls in the chandelier model are initially disconnected tetrahedra;these tetrahedra merge and collapse into1-d curves in lower-complexity approximations.Similarly,the numerous polyg-onal ropes in the schooner model are simplified into curves which can be rendered as line segments.The straps of the sandal model initially have some thickness;the top and bottom sides of these straps merge in the simplification.Also note the disappearance of the holes on the sandal straps.The castle example demonstrates that the original model need not be a mesh;here M is a1-dimensional non-manifold obtained by extracting edges from an image.6RELATED WORKThere are numerous schemes for representing and simplifying tri-angulations in computer graphics.A common special case is that of subdivided2-manifolds(meshes).Garland and Heckbert[12] provide a recent survey of mesh simplification techniques.Several methods simplify a given model through a sequence of edge col-lapse transformations[10,13,14,20].With the exception of[20], these methods constrain edge collapses to preserve the topological type of the model(e.g.disallow the collapse of a tetrahedron into a triangle).Our work is closely related to several schemes that generalize the notion of edge collapse to that of vertex unification,whereby separate connected components of the model are allowed to merge and triangles may be collapsed into lower dimensional simplices. Rossignac and Borrel[21]overlay a uniform cubical lattice on the object,and merge together vertices that lie in the same cubes. Schaufler and St¨u rzlinger[22]develop a similar scheme in which vertices are merged using a hierarchical clustering algorithm.Lue-bke[18]introduces a scheme for locally adapting the complexity of a scene at runtime using a clustering octree.In these schemes, the approximating models correspond to simplicial complexes that would result from a set of vunify transformations(Section3.3).Our approach differs in that we order the vunify in a carefully optimized sequence.More importantly,we define not only a simplification process,but also a new representation for the model using an en-coding of gvspl=vunify1transformations.Recent,independent work by Schmalstieg and Schaufler[23]de-velops a similar strategy of encoding a model using a sequence of vertex split transformations.Their scheme differs in that it tracks only triangles,and therefore requires regular,2-dimensional trian-gulations.Hence,it does not allow lower-dimensional simplices in the model approximations,and does not generalize to higher dimensions.Some simplification schemes make use of an intermediate vol-umetric representation to allow topological changes to the model. He et al.[11]convert a mesh into a binary inside/outside function discretized on a three-dimensional grid,low-passfilter this function,。

基于压缩感知理论的二维DOA估计

基于压缩感知理论的二维DOA估计

第47卷第3期2021年3月北京工业大学学报JOURNAL OF BEIJING UNIVERSITY OF TECHNOLOGYVol.47No.3Mar.2021基于压缩感知理论的二维DOA估计窦慧晶,梁霄,张文倩(北京工业大学信息学部,北京100124)摘要:二维波达方向(direction of arrival,DOA)估计在雷达探测、电子对抗、医学成像等领域有着广泛的应用.针对现有算法估计精度不足、计算量巨大的问题,在基于压缩感知理论的背景下提出一种二维均匀L型阵列信号的DOA估计算法.该算法首先对阵列信号的俯仰角和方位角构建空间合成角,并对空间合成角构建过完备冗余字典;再利用正交化高斯随机矩阵构造观测矩阵;最后通过改进RM-FOCUSS算法和求解三角函数的方法还原出方位角和俯仰角.理论研究表明,该方法在高信噪比、多快拍条件下比传统算法具有更高的估计精度和分辨力,且通过压缩采样降低了运算量.仿真实验验证了上述结论.关键词:DOA估计;压缩感知;过完备冗余字典;稀疏表示;压缩采样;测量矩阵中图分类号:TN911文献标志码:A文章编号:0254-0037(2021)03-0231-08doi:10.11936/bjutxb2019100002Two-dimensional DOA Estimation Based onCompressed Sensing TheoryDOU Huijing,LIANG Xiao,ZHANG Wenqian(Faculty of Information Technology,Beijing University of Technology,Beijing100124,China)Abstract:Two-dimensional direction of arrival(DOA)estimation has been widely used in radar detection,electronic reconnaissance,medical imaging and other fields.Aiming at the problems of inadequate estimation accuracy and enormous computational load of existing algorithms,a DOA estimation algorithm for two-dimensional uniform L-shaped array signals was presented in this paper based on compressed sensing theory.First,an over-complete redundant dictionary was established by using the space frequency of the azimuth angle and pitch angle.Then the orthogonal Gaussian random matrix was used to construct the measurement matrix.Finally,azimuth and elevation were restored by improving RM -FOCUSS algorithm and solving trigonometric function.The theoretical research shows that the proposed method has higher estimation accuracy and resolution than the traditional algorithm under the conditions of high SNR and multi-snapshot,and it reduces the computational complexity by compressing sampling.The simulation results verify the effectiveness and correctness.Key words:direction of arrival(DOA)estimation;compressed sensing(CS);over-complete redundant dictionary;spare representation;compressed sampling;measurement matrix二维波达方向(direction of arrival,DOA)估计在阵列信号处理领域有着重要的研究意义,与一维收稿日期:2019-10-11基金项目:国家自然科学基金资助项目(61171137);北京市教育委员会科研发展计划资助项目(KM201210005001)作者简介:窦慧晶(1969—),女,副教授,主要从事数字信号处理、信号参量估计阵列信号处理、语音信号处理方面的研究, E-mail:dhuijing@232北京工业大学学报2021年DOA估计相比,该估计算法能够更精确描述目标的空间特性,因此DOA估计在二维信号领域更具实际应用价值[1-2].二维多重信号分类(two-dimensional multiple signal classification,2-D MUSIC)算法是目前已有的二维阵列信号DOA估计算法中最为经典的估计算法之一,该算法核心思想是将传统的一维MUSIC估计算法在二维空间进行直接推广,由于该算法需要二维谱峰搜索因而导致计算量巨大,且需要各信源的中心频率已知,因此很难满足实际应用⑶.为了解决上述缺陷,有学者提出一种无须谱峰搜索的二维旋转不变子空间(two-dimensional estimating signal parameter via rotational invariance techniques,2-D ESPRIT)算法以及二维传播算子(two-dimensional propagation method,2-D PM)算法⑷.这些算法的相继问世使阵列信号的处理性能得到一定的提高,但因其在小快拍数及低信噪比情况下估计性能严重下降而无法推广到实际应用中.在众多阵列结构中,由于L型阵列具有结构简单、实施容易、估计性能佳等优点而被广泛用于工程领域.为解决二维信号角度匹配精度不高且计算复杂的问题,文献[5]提出一种基于L型阵列的无须手动配对的二维DOA估计算法,通过引入新的合成角度计算出新的导向矢量,进而获得原信号的俯仰角和方位角.尽管该方法能够自动完成角度配对,但需要多次谱峰搜索及特征值分解导致计算复杂度过高.文献[6]提出一种新的二维DOA估计方法,该算法首先将方位角和俯仰角分别估计出来,再通过阵列输出的互相关和信号功率对2个角度进行匹配,由于需要大量的采样信号使得该方法不可有效避免大量的数值计算.为降低运算量有学者提出利用阵列数据的协方差矩阵进行二维角度估计的算法[7-8].文献[9]提出一种利用多相干信号对方位角和俯仰角进行配对的方法,通过利用协方差矩阵最小化构造的代价函数从而实现角度配对,该算法存在的最大弊端是在构造协方差矩阵的过程中可能会引入外界噪声,从而影响其估计性能.压缩感知(comprehensive sensing,CS)理论的出现为现代信号处理带来一种更高效、更精确的方法,文献[10]提出基于该理论的£-SVD算法,该算法通过对接收信号进行奇异值分解(singular value decomposition,SVD)来降低算法复杂度和对噪声的敏感性,然后利用二阶锥规划的方法求解相应的优化问题,该算法在小快拍数和低信噪比时有很好的性能,并且可以直接用于相干信号[11].该方法摆脱了传统奈奎斯特采样定理带来超大计算量的束缚.基于此,众多学者将压缩感知理论引入到DOA估计中来,从而达到降低计算量的目的.文献[12]提出一种基于协方差矩阵联合稀疏重构的降维波达方向估计算法,该算法充分利用阵列孔径,无须预先估计目标数目,参数估计性能在低信噪比及小快拍数据长度下优势明显,但在其他方面尚有改进余地.本文在基于压缩感知理论的背景下提出一种二维L 型阵列信号的DOA估计算法.该方法在高信噪比、多快拍条件下相较于传统算法具有更高的估计精度和分辨力,且具有较低的运算量.1信号模型本文试验采用L型均匀阵列,该模型中2个子阵互相垂直,成90。

Improving the accuracy of static GPS positioning with a new stochastic modelling procedure

Improving the accuracy of static GPS positioning with a new stochastic modelling procedure

INTRODUCTION GPS carrier phase measurements are extensively used for all high precision static and kinematic positioning applications. The least-squares estimation technique is usually employed in the data processing step, and basically requires the definition of two models: (a) the functional model, and (b) the stochastic model. The functional model describes the mathematical relationship between the GPS observations and the unknown parameters, while the stochastic model describes the statistical characteristics of the GPS observations (see, eg., Leick, 1995; Rizos 1997; and other texts). The stochastic model is therefore dependent on the selection of the functional model. A double-differencing technique is commonly used for constructing the functional model as it can eliminate many of the troublesome GPS biases, such as the atmospheric biases, the receiver and satellite clock biases, and so on. However, some unmodelled biases still remain in the GPS observables, even after such data differencing. Many researchers have emphasised the importance of the stochastic model, especially for high accuracy applications, for example, Barnes et al. (1998), Cross et al. (1994), Han (1997), Teunissen (1997), Wang (1998), Wang et. al. (2001) for both the static and kinematic positioning applications. In principle it is possible to further improve the accuracy and reliability of GPS results through an enhancement of the stochastic model. Previous studies have shown that GPS measurements have a heteroscedastic, space- and timecorrelated error structure (eg., Wang 1998; Wang et al., 1998a). The challenge is to find a way to realistically incorporate such information into the stochastic model. This paper deals only with the static positioning case. Several stochastic modelling techniques have recently been proposed to accommodate the heteroscedastic behaviour of GPS observations. Some are based on the signal-to-noise (SNR) ratio model (eg., Barnes et al., 1998; Brunner et al., 1999; Hartinger & Brunner, 1998; Lau & Mok, 1999; Talbot, 1988), others use a satellite elevation dependent approach (eg., Euler & Goad, 1991; Gerdan, 1995; Han, 1997; Jin, 1996; Rizos etPHY Chalermchon Satirapod is currently a Ph.D. student at the School of Geomatic Engineering, The University of New South Wales (UNSW), supported by a scholarship from the Chulalongkorn University. He graduated with a Bachelor of Engineering (Surveying) and Master of Engineering (Surveying) from Chulalongkorn University, Thailand, in 1994 and 1997 respectively. He joined the Department of Survey Engineering at Chulalongkorn University as a lecturer in late 1994. In early 1998 he joined UNSW's Satellite Navigation and Positioning (SNAP) group as a Ph.D. student. His research is focussed on automated and quality assured GPS surveying for a range of applications. ABSTRACT For high precision static GPS positioning applications, carrier phase measurements have to be processed. It is well known that there are two important aspects to the optimal processing of GPS measurements: the definition of the functional model, and the associated stochastic model. These two models must be correctly defined in order to achieve high reliability in the positioning results. The functional model is nowadays sufficiently known, however the definition of the stochastic model still remains a challenging research topic. Previous studies have shown that the GPS measurements have a heteroscedastic, space- and time-correlated error structure. Therefore, a realistic stochastic modelling procedure should take all of these error features into account. In this paper, a new stochastic modelling procedure is introduced. This procedure also takes into account the temporal correlations in the GPS measurements. To demonstrate its performance, both simulated and real data sets for short to medium length baselines have been analysed. The results indicate that the accuracy of GPS results can be improved to the millimetre level.

重构高海拔地区空间连续的MODIS地表温度

重构高海拔地区空间连续的MODIS地表温度

重构高海拔地区空间连续的MODIS地表温度2.青海师范大学文学院青海西宁 810000摘要:地表温度(LST)是地表系统的关键参数之一。

虽然遥感具有获得全球覆盖的LST观测能力。

但是,由于云层覆盖和轨道间隙的影响,遥感LST产品总是存在空缺。

本文选取青藏高原阿里地区作为研究区域探讨了利用经验正交函数插值法(DINEOF)在高海拔地区对中分辨率成像光谱仪(MODIS)的适用性。

通过对重构前后地表温度的空间分析,验证了DINEOF方法可以很好地恢复LST 的空间格局。

关键字:地表温度;MODIS;数据重构;DINEOF一、引言地表温度(LST)是区域和全球尺度上陆地表层系统过程的关键参数,能够提供地表能量平衡状态的时空变化信息,在天气预报、全球大气环流模式以及区域气候模式等研究领域得到广泛的应用[1]。

从地表能量平衡来看,LST和地球表面发射率,决定了地表发射的长波辐射总量。

从水文角度来看,LST影响近地表蒸散过程。

在高纬度和高海拔地区例如青藏地区,LST也是永久冻土和冰/雪消融的指标。

LST还可用作大尺度地区土壤呼吸的预测因子并且也是区域和全球碳循环的影像因子。

由于云层覆盖和轨道间隙的影响,缺失值始终是MODIS LST产品应用的限制因素,为了克服这个问题,本研究使用了经验正交函数插值(DINEOF)方法。

与基于物理的LST重建方法和统计方法相比,DINEOF需要更少的输入参数,并且计算量更大计算效率更高效。

在以往的研究中,DINEOF方法已成功应用于海表温度[2]、叶绿素a质量浓度[3]、海表盐度[4]重构,并且结果表明DINEOF方法具有较高的重建精度,即使在SST严重的数据缺失情况下也是如此。

在本文中,2020年阿里地区的MODIS AQUA LST 产品(MOD11A1)和(MYD11A1)用于测试DINEOF方法在重构高海拔地区LST的适用性。

二、研究区域与研究数据2.1研究区域概况青藏高原的阿里地区,是西藏面积第二大的地级单位,与印度、尼泊尔接壤,平均海拔4500米以上[5]。

用于微裂缝储层描述的一项新技术(一)

用于微裂缝储层描述的一项新技术(一)

摘要: 本文发表 了一项新技术的测试用例( 沙特阿拉伯W dy i uah 油田Uazh n ya 油藏 ) , 这项技术使用了人工增强磁化率各向异性 (A S 来表征微裂缝油气藏。 EM ) 在这些油 气藏中,微裂缝是形成孔隙度和/ 或渗透率的基础 。常规地质描述 既费钱又费时, 并且难 以定地评价裂缝对孔隙度和渗透率的影响。因此, 需要一种有效的方法来
储层样品具有对储层有效孔 隙度和渗透率有贡献的开启 、连通天然裂 缝,则该 样品被称作具有裂缝性孔 隙组构 。如果天然裂缝缺乏 、密度较低或被 阻塞 ,造 成它们对储层孔 隙度和/ 或渗透率影响很 小或没有影 响, 则储层样品就被称作具 有非裂缝性孔 隙组构 。
1 3 目标 . 微裂 缝 油气 藏 主 要 是用 岩 相 学 和 常 规 岩 石物 理 学方 法 来 表 征 的 。我 们 研 究
度。测试样品中的开启微裂缝使 Ua zhB C中的储层有效孔 隙度平均值增加 了 ny a- / 3— O。连通微裂缝产状估计使 U az hB C 65% n y a— / 的平均渗透率增加 了 7% 5 。这与微 裂缝 U a zhB C井产能是该油藏非裂缝层段井的 45 1 倍这一事实一致。探 ny a— / .- 4 测到 了北东一 南西渗透率异常的最大渗透率趋势。EM AS技术在其他拥有微裂缝储
的 目的是开发和试验 一种用于微裂缝 油气藏描述 的快速 、 经济和 非常规 的方法 ,
维普资讯
20 年 4 2 08 月 5日
用 于微 裂缝 储层 描述 的一 项新 技术 ( ) 一
用 于微 裂 缝储 层 描 述 的一 项 新技 术 ( ) 一
M h m e S A e , E n t o a m d . me n r es A. ai o d H 1 o w

光伏发电英文文献Ultra-High Efficiency Photovoltaic

光伏发电英文文献Ultra-High Efficiency Photovoltaic

Ultra-High Efficiency Photovoltaic Cells for Large Scale Solar Power GenerationYoshiaki NakanoAbstract The primary targets of our project are to dras-tically improve the photovoltaic conversion efficiency and to develop new energy storage and delivery technologies. Our approach to obtain an efficiency over40%starts from the improvement of III–V multi-junction solar cells by introducing a novel material for each cell realizing an ideal combination of bandgaps and lattice-matching.Further improvement incorporates quantum structures such as stacked quantum wells and quantum dots,which allow higher degree of freedom in the design of the bandgap and the lattice strain.Highly controlled arrangement of either quantum dots or quantum wells permits the coupling of the wavefunctions,and thus forms intermediate bands in the bandgap of a host material,which allows multiple photon absorption theoretically leading to a conversion efficiency exceeding50%.In addition to such improvements, microfabrication technology for the integrated high-effi-ciency cells and the development of novel material systems that realizes high efficiency and low cost at the same time are investigated.Keywords Multi-junctionÁQuantum wellÁConcentratorÁPhotovoltaicINTRODUCTIONLarge-scale photovoltaic(PV)power generation systems, that achieve an ultra-high efficiency of40%or higher under high concentration,are in the spotlight as a new technology to ease drastically the energy problems.Mul-tiple junction(or tandem)solar cells that use epitaxial crystals of III–V compound semiconductors take on the active role for photoelectric energy conversion in such PV power generation systems.Because these solar cells operate under a sunlight concentration of5009to10009, the cost of cells that use the epitaxial crystal does not pose much of a problem.In concentrator PV,the increased cost for a cell is compensated by less costly focusing optics. The photons shining down on earth from the sun have a wide range of energy distribution,from the visible region to the infrared region,as shown in Fig.1.Multi-junction solar cells,which are laminated with multilayers of p–n junctions configured by using materials with different band gaps,show promise in absorbing as much of these photons as possible,and converting the photon energy into elec-tricity with minimum loss to obtain high voltage.Among the various types of multi-junction solar cells,indium gallium phosphide(InGaP)/gallium arsenide(GaAs)/ger-manium(Ge)triple-junction cells that make full use of the relationship between band gaps and diverse lattice con-stants offered by compound semiconductors have the advantage of high conversion efficiency because of their high-quality single crystal with a uniform-size crystal lat-tice.So far,a conversion efficiency exceeding41%under conditions where sunlight is concentrated to an intensity of approximately5009has been reported.The tunnel junction with a function equivalent to elec-trodes is inserted between different materials.The positive holes accumulated in the p layer and the electrons in the adjacent n layer will be recombined and eliminated in the tunnel junction.Therefore,three p–n junctions consisting of InGaP,GaAs,and Ge will become connected in series. The upper limit of the electric current is set by the mini-mum value of photonflux absorbed by a single cell.On the other hand,the sum of voltages of three cells make up the voltage.As shown in Fig.1,photons that can be captured in the GaAs middle cell have a smallflux because of the band gap of each material.As a result,the electric currentoutputAMBIO2012,41(Supplement2):125–131 DOI10.1007/s13280-012-0267-4from the GaAs cell theoretically becomes smaller than that of the others and determines the electric current output of the entire tandem cell.To develop a higher efficiency tandem cell,it is necessary to use a material with a band gap narrower than that of GaAs for the middle cell.In order to obtain maximum conversion efficiency for triple-junction solar cells,it is essential to narrow down the middle cell band gap to 1.2eV and increase the short-circuit current density by 2mA/cm 2compared with that of the GaAs middle cell.When the material is replaced with a narrower band gap,the output voltage will drop.However,the effect of improving the electric current balance out-performs this drop in output voltage and boosts the effi-ciency of the entire multi-junction cell.When a crystal with such a narrow band gap is grown on a Ge base material,lattice relaxation will occur in the middle of epitaxial crystal growth because the lattice constants of narrower band-gap materials are larger than that of Ge (as shown in Fig.2).As a result,the carrier transport properties will degrade due to dislocation.Researchers from the international research center Solar Quest,the University of Tokyo,aim to move beyond such material-related restrictions,and obtain materials and structures that have effective narrow band gaps while maintaining lattice matching with Ge or GaAs.To achieve this goal,we have taken three approaches as indicated in Fig.3.These approaches are explained in detail below.DILUTE NITROGEN-ADDED BULK CRYSTAL Indium gallium nitride arsenide (InGaNAs)is a bulk material consists of InGaAs,which contains several percent of nitrogen.InGaNAs has a high potential for achieving a narrow band gap while maintaining lattice matching with Ge or GaAs.However,InGaNAs has a fatal problem,that is,a drop in carrier mobility due to inhomogeneousdistribution of nitrogen (N).To achieve homogeneous solid solution of N in crystal,we have applied atomic hydrogen irradiation in the film formation process and addition of a very small amount of antimony (Sb)(Fig.3).The atomic hydrogen irradiation technology and the nitrogen radical irradiation technology for incorporating N efficiently into the crystal can be achieved only through molecular beam epitaxy (MBE),which is used to fabricate films under high vacuum conditions.(Nitrogen radical irradiation is a technology that irradiates the surface of a growing crystal with nitrogen atoms that are resolved by passing nitrogen through a plasma device attached to the MBE system.)Therefore,high-quality InGaNAs has been obtained only by MBE until now.Furthermore,as a small amount of Sb is also incorporated in a crystal,it is nec-essary to control the composition of five elements in the crystal with a high degree of accuracy to achieve lattice matching with Ge or GaAs.We have overcome this difficulty by optimizing the crystal growth conditions with high precision and devel-oped a cell that has an InGaNAs absorption layer formed on a GaAs substrate.The short-circuit current has increased by 9.6mA/cm 2for this cell,compared with a GaAs single-junction cell,by narrowing the band gap down to 1.0eV.This technology can be implemented not only for triple-junction cells,but also for higher efficiency lattice-matched quadruple-junction cells on a Ge substrate.In order to avoid the difficulty of adjusting the compo-sition of five elements in a crystal,we are also taking an approach of using GaNAs with a lattice smaller than that of Ge or GaAs for the absorption layer and inserting InAs with a large lattice in dot form to compensate for the crystal’s tensile strain.To make a solid solution of N uniformly in GaNAs,we use the MBE method for crystal growth and the atomic hydrogen irradiation as in the case of InGaNAs.We also believe that using 3D-shaped InAs dots can effectively compensate for the tensile strainthatFig.1Solar spectrum radiated on earth and photon flux collected by the top cell (InGaP),middle cell (GaAs),and bottom cell (Ge)(equivalent to the area of the filled portions in the figure)occurs in GaNAs.We have measured the characteristics of a single-junction cell formed on a GaAs substrate by using a GaNAs absorption layer with InAs dots inserted.Figure 4shows that we were able to succeed in enhancing the external quantum efficiency in the long-wavelength region (corresponding to the GaNAs absorp-tion)to a level equal to GaAs.This was done by extending the absorption edge to a longer wavelength of 1200nm,and increasing the thickness of the GaNAs layer by increasing the number of laminated InAs quantum dot layers.This high quantum efficiency clearly indicates that GaNAs with InAs dots inserted has the satisfactory quality for middle cell material (Oshima et al.2010).STRAIN-COMPENSATED QUANTUM WELL STRUCTUREIt is extremely difficult to develop a narrow band-gap material that can maintain lattice matching with Ge orGaAs unless dilute nitrogen-based materials mentioned earlier are used.As shown in Fig.2,the conventionally used material InGaAs has a narrower band gap and a larger lattice constant than GaAs.Therefore,it is difficult to grow InGaAs with a thickness larger than the critical film thickness on GaAs without causing lattice relaxation.However,the total film thickness of InGaAs can be increased as an InGaAs/GaAsP strain-compensated multi-layer structure by laminating InGaAs with a thickness less than the critical film thickness in combination with GaAsP that is based on GaAs as well,but has a small lattice constant,and bringing the average strain close to zero (Fig.3.).This InGaAs/GaAsP strain-compensated multilayer structure will form a quantum well-type potential as shown in Fig.5.The narrow band-gap InGaAs layer absorbs the long-wavelength photons to generate electron–hole pairs.When these electron–hole pairs go over the potential bar-rier of the GaAsP layer due to thermal excitation,the electrons and holes are separated by a built-in electricfieldFig.2Relationship between band gaps and lattice constants of III–V-based and IV-based crystalsto generate photocurrent.There is a high probability of recombination of electron–hole pairs that remain in the well.To avoid this recombination,it is necessary to take out the electron–hole pairs efficiently from the well and transfer them to n-type and p-type regions without allowing them to be recaptured into the well.Designing thequantumFig.3Materials and structures of narrow band-gap middle cells being researched by thisteamFig.4Spectral quantum efficiency of GaAs single-junction cell using GaNAs bulk crystal layer (inserted with InAs dots)as the absorption layer:Since the InAs dot layer and the GaNAs bulk layer are stacked alternately,the total thickness of GaNAs layers increases as the number of stacked InAs dot layers is increased.The solid line in the graph indicates the data of a reference cell that uses GaAs for its absorption layer (Oshima et al.2010)well structure suited for this purpose is essential for improving conversion efficiency.The high-quality crystal growth by means of the metal-organic vapor phase epitaxy (MOVPE)method with excellent ability for mass production has already been applied for InGaAs and GaAsP layers in semiconductor optical device applications.Therefore,it is technologically quite possible to incorporate the InGaAs/GaAsP quantum well structure into multi-junction solar cells that are man-ufactured at present,only if highly accurate strain com-pensation can be achieved.As the most basic approach related to quantum well structure design,we are working on fabrication of super-lattice cells with the aim of achieving higher efficiency by making the GaAsP barrier layer as thin as possible,and enabling carriers to move among wells by means of the tunnel effect.Figure 6shows the spectral quantum effi-ciency of a superlattice cell.In this example,the thickness of the GaAsP barrier layer is 5nm,which is not thin enough for proper demonstration of the tunnel effect.When the quantum efficiency in the wavelength range (860–960nm)that corresponds to absorption of the quan-tum well is compared between a cell,which has a con-ventionally used barrier layer and a thickness of 10nm or more,and a superlattice cell,which has the same total layer thickness of InGaAs,the superlattice cell demonstrates double or higher quantum efficiency.This result indicates that carrier mobility across quantum wells is promoted by even the partial use of the tunnel effect.By increasing the P composition in the GaAsP layer,the thickness of well (or the In composition)can be increased,and the barrier layer thickness can be reduced while strain compensation is maintained.A cell with higher quantum efficiency can befabricated while extending the absorption edge to the long-wavelength side (Wang et al.2010,2012).GROWTH TECHNIQUE FOR STRAIN-COMPENSATED QUANTUM WELLTo reduce the strain accumulated in the InGaAs/GaAsP multilayer structure as close to zero as possible,it is nec-essary to control the thickness and atomic content of each layer with high accuracy.The In composition and thickness of the InGaAs layer has a direct effect on the absorption edge wavelength and the GaAsP layer must be thinned to a satisfactory extent to demonstrate fully the tunnel effect of the barrier layer.Therefore,it is desirable that the average strain of the entire structure is adjusted mainly by the P composition of the GaAsP layer.Meanwhile,for MOVPE,there exists a nonlinear rela-tionship between the P composition of the crystal layer and the P ratio [P/(P ?As)]in the vapor phase precursors,which arises from different absorption and desorption phenomena on the surface.As a result,it is not easy to control the P composition of the crystal layer.To break through such a difficulty and promote efficient optimiza-tion of crystal growth conditions,we have applied a mechanism to evaluate the strain of the crystal layer during growth in real time by sequentially measuring the curvature of wafers during growth with an incident laser beam from the observation window of the reactor.As shown in Fig.7,the wafer curvature during the growth of an InGaAs/GaAsP multilayer structure indicates a periodic behavior.Based on a simple mechanical model,it has become clear that the time changes ofwaferFig.5Distribution of potential formed by the InGaAs/GaAsP strain-compensated multilayer structure:the narrow band-gap InGaAs layer is sandwiched between wide band-gap GaAsP layers and,as a result,it as quantum well-type potential distribution.In the well,electron–hole pairs are formed by absorption of long-wavelength photons and at the same time,recombination of electrons and holes takes place.The team from Solar Quest is focusing on developing a superlattice structure with the thinnest GaAsP barrier layercurvature are proportionate to the strain of the crystal layer relative to a substrate during the growing process.One vibration cycle of the curvature is same as the growth time of an InGaAs and GaAsP pair (Sugiyama et al.2011).Therefore,the observed vibration of the wafer curvature reflects the accumulation of the compression strain that occurs during InGaAs growth and the release of the strain that occurs during GaAsP growth.When the strain is completely compensated,the growth of the InGaAs/GaAsP pair will cause this strain to return to the initial value and the wafer curvature will vibrate with the horizontal line as the center.As shown in Fig.7,strain can be compensated almost completely by adjusting the layer structure.Only by conducting a limited number of test runs,the use of such real-time observation technology of the growth layer enables setting the growth conditions for fabricating the layer structure for which strain has been compensated with highaccuracy.Fig.6Spectral quantum efficiency of GaAs single-junction cell using InGaAs/GaAsP superlattice as theabsorption layer:This structure consists of 60layers of InGaAs quantum wells.The graph also shows data of a reference cell that uses GaAs for its absorption layer (Wang et al.2010,2012)Fig.7Changes in wafer curvature over time during growth of the InGaAs/GaAsP multilayer structure.This graph indicates the measurement result and the simulation result of the curvature based on the layer structure(composition ?thickness)obtained by X-ray diffraction.Since compressive strain is applied during InGaAs growth,the curvature decreases as time passes.On the other hand,since tensile strain is applied during GaAsP growth,the curvature changes in the oppositedirection (Sugiyama et al.2011)FUTURE DIRECTIONSIn order to improve the conversion efficiency by enhancing the current matching of multi-junction solar cells using III–V compound semiconductors,there is an urgent need to create semiconductor materials or structures that can maintain lattice matching with Ge or GaAs,and have a band gap of1.2eV.As for InGaNAs,which consists of InGaAs with several percent of nitrogen added,we have the prospect of extending the band edge to1.0eV while retaining sufficient carrier mobility for solar cells by means of atomic hydrogen irradiation and application of a small quantity of Sb during the growth process.In addition,as for GaNAs bulk crystal containing InAs dots,we were able to extend the band edge to1.2eV and produce a high-quality crystal with enoughfilm thickness to achieve the quantum efficiency equivalent to that of GaAs.These crystals are grown by means of MBE. Therefore,measures that can be used to apply these crys-tals for mass production,such as migration to MOVPE, will be investigated after demonstrating their high effi-ciency by embedding these crystals into multi-junction cells.As for the InGaAs/GaAsP strain-compensated quantum well that can be grown using MOVPE,we are working on the development of a thinner barrier layer while compen-sating for the strain with high accuracy by real-time observation of the wafer curvature.We have had the prospect of achieving a quantum efficiency that will sur-pass existing quantum well solar cells by promoting the carrier transfer within the multilayer quantum well struc-ture using the tunnel effect.As this technology can be transferred quite easily to the existing multi-junction solar cell fabrication process,we strongly believe that this technology can significantly contribute to the efficiency improvement of the latest multi-junction solar cells. REFERENCESOshima,R.,A.Takata,Y.Shoji,K.Akahane,and Y.Okada.2010.InAs/GaNAs strain-compensated quantum dots stacked up to50 layers for use in high-efficiency solar cell.Physica E42: 2757–2760.Sugiyama,M.,K.Sugita,Y.Wang,and Y.Nakano.2011.In situ curvature monitoring for metalorganic vapor phase epitaxy of strain-balanced stacks of InGaAs/GaAsP multiple quantum wells.Journal of Crystal Growth315:1–4.Wang,Y.,Y.Wen,K.Watanabe,M.Sugiyama,and Y.Nakano.2010.InGaAs/GaAsP strain-compensated superlattice solar cell for enhanced spectral response.In Proceedings35th IEEE photovoltaic specialists conference,3383–3385.Wang,Y.P.,S.Ma,M.Sugiyama,and Y.Nakano.2012.Management of highly-strained heterointerface in InGaAs/GaAsP strain-balanced superlattice for photovoltaic application.Journal of Crystal Growth.doi:10.1016/j.jcrysgro.2011.12.049. AUTHOR BIOGRAPHYYoshiaki Nakano(&)is Professor and Director General of Research Center for Advanced Science and Technology,the University of Tokyo.His research interests include physics and fabrication tech-nologies of semiconductor distributed feedback lasers,semiconductor optical modulators/switches,monolithically integrated photonic cir-cuits,and high-efficiency heterostructure solar cells.Address:Research Center for Advanced Science and Technology, The University of Tokyo,4-6-1Komaba,Meguro-ku,Tokyo153-8904,Japan.e-mail:nakano@rcast.u-tokyo.ac.jp。

基于超声TOA的环境感知

基于超声TOA的环境感知

第 50 卷第 4 期2023 年 4 月Vol.50,No.4Apr. 2023湖南大学学报(自然科学版)Journal of Hunan University (Natural Sciences )基于超声TOA 的环境感知王刚†,张文静 ,邱文浩(湖南大学 汽车车身先进设计制造国家重点实验室,湖南 长沙 410082)摘要:针对超声波传感器测量过程中方位角存在不确定性的问题,提出了一种基于超声反射波到达时间(Time of Arrival ,TOA )的目标距离及方位角的测量方法,并据此发展了基于超声探测的环境感知方法.基于混合高斯拟合对回波信号进行处理,消除了信号串扰问题,提高了目标距离和方位信息的测量精度.基于传感器波束角的特性,实现了不同距离下目标的同时测量.通过引入“不确定度”,构建信度分配函数,采用DSmT (Dezert-Smarandache Theory )方法进行数据融合,实现地图更新.搭建了实验装置与实验环境,并对相关方法进行了实验验证,实验结果表明,通过135次测量即可实现对环境基本轮廓的建图,建图误差在3 cm 以内.关键词:超声波传感器;到达时间;Dezert-Smarandache 理论;栅格地图中图分类号:TP24 文献标志码:AEnvironment Perception Based on Ultrasonic TOAWANG Gang †,ZHANG Wenjing ,QIU Wenhao(State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body , Hunan University , Changsha 410082, China )Abstract :In order to solve the uncertainty of azimuth in the ultrasonic sensor measurement process , a targetdistance and azimuth measurement method based on time of arrival (TOA ) is proposed , and an environment sensing method based on ultrasonic detection is developed. The echo signal is processed based on the mixed Gaussian fit⁃ting , which eliminates the problem of signal crosstalk and improves the measurement accuracy of target distance and azimuth information. Based on the characteristics of the sensor beam angle , the simultaneous measurement of targets at different distances is achieved. By introducing “uncertainty ”, a set of belief assignment functions is defined , andthe DSmT (Dezert-Smarandache Theory ) method is used for data fusion to realize map updates. Finally , the experi⁃mental device and environment are constructed for verification , and the result shows that the basic contour of the en⁃vironment can be built through 135 measurements , and the mapping error is less than 3 cm. Key words :ultrasonic sensors ;time of arrival (TOA );Dezert-Smarandache theory ;grid map同时定位与地图构建(Simultaneous Localizationand Mapping ,SLAM )是机器人进行环境感知以及定位导航的关键技术[1].目前主流的SLAM 技术主要基于激光或者视觉,但是在一些极端恶劣环境下,例如∗收稿日期:2022-04-07基金项目:国家自然科学基金资助项目(11772123),National Natural Science Foundation of China (11772123)作者简介:王刚(1975―),男,湖南长沙人,湖南大学教授,博士生导师,博士† 通信联系人,E-mail :*************.cn文章编号:1674-2974(2023)04-0021-10DOI :10.16339/ki.hdxbzkb.2023151湖南大学学报(自然科学版)2023 年火灾导致的浓烟,受限于光波穿透能力,激光和视觉传感器的性能均会受到影响.与基于光的环境感知手段相比,超声波传感器具有成本低、抗环境干扰力强等优点,适用于上述恶劣环境,在环境感知领域已经有所运用[2-4].在基于超声波传感器的SLAM建图过程中,由于传感器波束角往往较大,波束角范围内的回波信号都会被检测到,因此其测量结果在测量方位上存在较大的不确定性[5].Tardós等[6]通过声呐扫描进行多次测量来获取反射物的位置信息时,由于波束角很宽,无法确定回波的具体方向,只能用声呐的中轴代替回波方向,这种方法存在明显的角度误差.为了解决超声波传感器测量方位存在不确定性的问题,Bank等[7]提出了切向回归技术,通过将超声波传感器检测到的锥形区域的重叠部分进行融合,并拟合边界直线段来获得环境地图,但这种方法只能检测较为简单的平面目标,对曲面特征的对象难以应用.金世俊等[2]在2009年通过贝叶斯法对每一次测量的扇形区域进行融合,实现栅格地图的更新.Lee等[8]提出一种基于模糊传感器融合从而建立栅格地图的方法.Li等[9]、Yuan等[10]通过引入不确定度,提出了利用DSmT理论进行数据融合来更新地图的方法.以上方法均未从根本上解决传感器的角度信息不确定性的问题,而是通过对多次测量得到的多个扇形区域进行融合,来间接减小超声波传感器测量方位的不确定性,因此上述方法均需要较多的测量次数,建图效率低,计算量较大.本文提出了一种基于超声反射波到达时间(Time of Arrival,TOA)的环境感知方法,通过比较超声回波到达不同传感器的时间,获得反射点的距离和方位,从而在根本上解决了测量方位的不确定性问题.同时,该方法还能对处于波束角内不同距离下的反射物体进行识别与区分,从而进一步减少了测量次数,提高了建图效率.在信号处理方面,利用混合高斯拟合和阈值检测法对回波信号进行处理,解决了信号串扰,提高了TOA测量结果的准确度.继而,基于DSmT(DeZert-Smarandache Theory)的数据融合方法,进行了栅格地图建模,进一步减小了测量误差引起的建图误差.最后通过搭建实验装置和实验环境验证了本文所提出的方法.实验结果表明,所提出的方法较好地复现了环境轮廓,且建图误差在3 cm以内.1 基于TOA的超声回波测量在超声波传感器测量过程中,其波束角范围内的回波信号都会被检测到,而原有的方法只能得到反射物体的距离信息,无法得到其回波方向,从而导致传感器测量方位的不确定性.因此,通常利用指定距离上的扇形区域来表示目标可能存在的位置,并通过融合多个扇形区域来获得反射物体的精确位置[2,8-11],这种方法需要较多的测量次数.本文通过TOA来获得反射物体的方位角信息,以此来解决方位角的不确定性问题.TOA是一种以信号到达时间为基础,结合测距来获得位置信息的方法.图1(a)是本实验采用的超声测量装置,其中处于装置中间位置的传声器T用于发射超声波信号,左右两侧的传声器R1、R2用于接收超声回波信号.超声波传感器主要有静电式和压电式,静电式超声波传感器工艺复杂,需要较高的偏置电压,而压电式超声波传感器具有带宽较窄、在中心频率处的灵敏度高以及输出信号能量大的特性,因此本实验采用压电式超声波传感器.另外,超声波传感器的工作频率与测量的精确度正相关,而与信号传播距离负相关,因此超声波传感器需要选择合适的工作频率.通过实验测试发现,发射传声器的驱动电压与超声的测量范围正相关.即增大发射传声器的驱动电压,可以增大超声的测量范围.本文发射传声器工作在48 V驱动电压下,在2 m的距离范围内,工作频率为25 kHz的超声波传感器可以接收到清晰的回波信号,因此本文选用图1(b)所示工作频率为25 kHz的压电式超声波传感器.超声测距装置单次测量的步骤是:发射传声器T (a)超声波传感器装置图(b)超声接收器(左)及发射器(右)图 1 超声测量装置Fig. 1 Ultrasonic ranging device22第 4 期王刚等:基于超声TOA 的环境感知发出超声波脉冲信号,经反射物体的反射后,分别到达左右接收传声器R 1、R 2.通过对获取的信号进行信号处理,得到回波信号的到达时间,再与超声信号发射的起始时间求差,即可以得到超声回波信号的传播时间.当测量距离远大于传感器的间距时,反射物体的形状对反射点的测量距离和角度的影响很小[12],因此在测量范围内对于连续光滑的反射物体,无论是什么形状,其轮廓在局部范围内都可以简化为一段直线,用这种方法得到的测量结果对于弧面也同样适用.为方便叙述,下文用反射区域来表示这一直线段.如图2所示,对于反射物体,回波信号相当于是发射传声器T 的平面镜像T'发出的,根据TOA 可以得到接收传声器R 1和R 2分别到虚拟发射传声器T'的距离L 1和L 2,d 为超声波传感器之间的距离.根据几何关系,可以得到发射传声器T 与反射区域的垂直距离L f 及反射区域的垂线与传声器连线之间的角度θ.L f =(1)θ=arccos(L 21-L 224dL f)(2)同时,由于传声器具有一定的波束角,为了保证信号的接收效果,信号回波方向与传声器中轴线的夹角ψ应该小于波束角,根据几何关系,可以得到:d ≥||L 1-L 22sin ψ(3)为了满足公式(3)以及保证传声器间距远小于测量距离,本文选取d =30 cm.可见,基于TOA 的测量方法可以直接得到反射区域回波的角度信息,而不需要融合多次测量数据来减小方位角的不确定性,因此该方法在保证精度的同时,大大提高了SLAM 建图效率.2 超声回波信号处理2.1 基于阈值检测和混合高斯拟合的信号处理根据文献[13],接收传声器收到的回波信号可近似为:y (t )=x (t -t 0)cos [2πf 0(t -t 0)]+w (t )(4)其中,x (t -t 0)=a 0e -a 1()t -t 0(t -t 0)2u (t -t 0)(5)式中:u (t -t 0)是延时为t 0的阶跃函数,t 0对应脉冲的起始时间;a 0、a 1是信号的幅值和衰减系数;w (t )是均值为0的白噪声.以图3中细实线所示的某次测试得到的超声回波信号为例,通过选取合适的公式(5)中的参数a 0、a 1,可得到图3中短点线所示的理论回波信号的包络线.由于实际回波信号的包络线会随着反射物体位置的变化而改变,同时该理论回波信号包络线的后半部分会偏离实际回波信号,导致该包络线与实际回波信号的包络线重合度低.因此,根据公式(4)和(5)对应的理论回波信号,无法求得准确的脉冲起始时间.针对这个问题,本文通过对实际测量得到的回波信号进行分析,发现由3个高斯曲线叠加而成的混合高斯曲线能较好地拟合回波信号的包络线.该混合高斯拟合曲线的表达式如下:图 2 基于TOA 的超声测距几何示意图Fig. 2 Geometry of ultrasonic ranging based on TOA图 3 混合高斯拟合信号Fig. 3 The mixed Gaussian fitting signal23湖南大学学报(自然科学版)2023 年V g (t )=a 1exp ()-(t -b 1)2c 1+a 2exp ()-(t -b 2)2c 2+a 3exp ()-(t -b 3)2c 3(6)式中:a 1、a 2、a 3为各高斯函数的混合系数;b 1、b 2、b 3和c 1、c 2、c 3分别为各高斯函数的均值和方差.采用混合高斯拟合方法对图3所示的实测超声回波信号的包络曲线进行拟合,得到图3中粗实线所示的混合高斯拟合曲线.由图3可见,混合高斯拟合曲线与回波信号的包络线几乎完全重合,因此该高斯拟合曲线可以代替回波信号用于阈值检测,从而判断波达时间.通过多次测量发现,超声回波信号的包络线在第一次达到峰值的75%左右时,信号增长速度最快,即斜率最大,故此处的时间信息受噪声干扰的影响也最小.因此选取混合高斯拟合曲线第一次达到其峰值75%的时间作为波达时间.2.2 基于混合高斯拟合曲线的信号串扰抑制由于超声波传感器的波束角较大,因此当传感器之间的距离过近时,发射传声器产生与其中轴呈90°的旁瓣信号会直接传播到接收器.同时,根据压电式超声波传感器的工作原理,发射传声器在发出超声信号的同时,也会激发其壳体的机械振动,并通过传声器固定装置传播到接收传感器,进而引起其中敏感元件的响应.为了表述方便,本文用直达波信号来表示由这两种因素导致的传声器接收到的信号.当反射物体距离测量系统较近时,反射信号与直达波信号发生重叠,从而引起接收传声器的内部串扰现象[14-15].图4可以很直观地解释内部串扰现象,图4中细实线代表实际测量得到的超声回波信号,虚线表示实际回波信号的包络线.其中回波信号的第一个峰对应于直达波信号,第二个峰对应于反射信号.由于目标较近,反射信号的传播时间较短,直达波信号的尾部,部分会与反射信号发生重叠,从而导致反射信号的峰值前移,引起波达时间的测量误差.通过多次测量发现,对于相同的传感器阵列,左右接收传声器测量得到的直达波信号基本保持不变.基于这个特性,本文先在无反射物体的情况下进行测量,得到直达波信号的混合高斯拟合曲线;而后,在每次正常测量后,将测量信号的包络线减去之前得到的直达波信号的混合高斯拟合曲线,就可以基本消除测量距离过近带来的信号重叠干扰.处理后信号的包络线V c (t )的表达式为:V c (t )=V (t )-V g (t )=V (t )-a 1exp ()-(t -b 1)2c 1- a 2exp ()-(t -b 2)2c 2-a 3exp ()-(t -b 3)2c 3(7)式中:V (t )为实际测量回波信号的包络线;V g (t )为混合高斯拟合的直达波信号包络线.图4中粗实线所示为采用上述方法处理后的超声回波信号,点画线为该信号的包络线,从图中可以发现,通过上述处理后,直达波信号被基本消除,从而消除了因直达波信号引起的回波信号到达时间的判断误差.测量距离过小,会导致反射物体的多重反射.此时,如果一次反射信号的传播时间过短,将导致该回波信号被直达波信号和多重反射信号完全淹没.如图5所示,当超声波传感器侧面靠近墙面时,垂直于墙面的旁瓣信号会经过墙面的反射再次回到接收传声器,从而引起信号串扰.图6中信号代表的是图5中R 1传声器收到的回波信号,由于R 1受到上述信号串扰的影响,信号存在严重的重叠干扰,这种情况下,利用混合高斯拟合方法无法获得准确的波形轮廓,由此导致较大的波达时间误差.为了解决这个问题,本文引入“不确定度”来降低这些误差对实验最终结果的影响,具体实现如下:通过多次实验测量,得到测量距离γ(单位:m )与信号峰值V max (单位:V )的近似关系如式(8)所示:图 4 重叠回波信号及处理后的结果Fig. 4 The overlapping echo signal and the processed signal24第 4 期王刚等:基于超声TOA 的环境感知V max =2.163γ2-2.948 γ+1.188(8)由于接收的超声波传感器R 1、R 2间距相对较小,灵敏度也基本一致,测量信号的能量也就是信号峰值应该相当.同时由于信号衰减,不同的测量距离也应该对应不同的信号峰值能量.因此,在对两接收传感器接收到的信号进行上述处理后,两信号的能量仍具有较大差异,或者处理后的峰值能量与计算得到的测量距离不满足式(8)所示的经验关系,则说明信号的串扰问题未完全消除,表明由该组信号得到的测量结果可能存在较大的误差,准确度和可靠度较低,不确定度较高.将测量距离γ代入式(8)即可得到理想的信号峰值能量V maxi ,该值与实际得到的峰值能量V maxp 相除得到比值ζd ,同时结合接收传声器R 1与R 2之间的峰值能量比ζv ,绘制ζd 、ζv 与实验测量距离相对误差的关系图.如图7所示,图中圆点是在不同距离和不同方向下实测的50组ζd 、ζv 与相对误差关系的数据,其灰度值越小表示测距相对误差越小.根据这些数据,制定对应的不确定度参数φ与ζd 、ζv 的关系如下:φ=ìíîïïïïïï0 , (0.9<ζd ≤1)∪(0.5<ζv ≤1)-5ζd +4.5 , (0.7≤ζd ≤0.9)∩(0≤ζv <0.2)-2.5ζv +1.5 , (0≤ζd <0.7)∩(0.2≤ζv ≤0.5)(-5ζd +4.5)(-2.5ζv +1.5) , (0.7≤ζd ≤0.9)∩(0.2≤ζv ≤0.5)1 , (0≤ζd <0.7)∩(0≤ζv <0.2)(9)其中,ζv ≤1.图7中线条为根据式(9)绘制的相对误差随ζd 、ζv 变化的等高线图.从图7可以看出,式(9)基本上符合实验实际测量的ζd 、ζv 与相对误差的关系.在后续处理中,将φ引入计算,以此提高误差较大的测量结果的不确定度,从而降低其对最终实验测量结果的影响.2.3 不同距离下多个反射物体的探测由于超声波传感器具有一定的波束角,因此只要反射波处于波束角的范围内,接收传声器就能得到对应的回波信号.如图8所示,平面反射物体和曲面反射物体都位于传感器的波束角范围内,发射传声器T 发射的超声信号将在两个物体上分别发生反射,接收传声器将首先收到曲面的回波,之后收到平面的回波.通过比较两次回波的信号能量和传播时间并进行匹配,可以在单次测量后,同时得到曲面和平面的反射点.图9所示为在图8情况下接收传感器获取的超声回波信号.根据波达时间,可以确定先到达的为曲图 5 传声器侧面靠近墙面引起的串扰Fig. 5 Crosstalk caused by microphone side close to wall图 6 传声器侧面靠近墙面的回波信号Fig. 6 The echo signal caused by microphone side close to wall图 7 ζd 、ζv 与相对误差的关系图Fig. 7 The plot of ζd , ζv and relative error25湖南大学学报(自然科学版)2023 年面反射信号,后到达的为平面反射信号.因此,如果在测量范围内存在多个反射物体,且反射物体间距足够的情况下,可通过单次测量,同时计算得到两个及以上的反射物体的距离和角度信息,从而提高探测效率.3 基于DSmT 的栅格信度分配函数建模及地图融合与更新3.1 DSmT 基本原理在采用超声波传感器绘制地图的过程中,获取到的测量信息具有不确定性、不精确性,甚至可能会高度冲突,特别是在栅格地图的绘制中,此现象尤为严重.针对这一问题,提出DSmT [16],即处理不确定、高度冲突和不精确证据源融合的完整理论,它可以将多个主体信息进行融合,并且允许根据信度函数正式组合任何类型的独立信息源.DSmT 具有多种比例冲突再分配规则[17],其中比例冲突再分配规则6(Proportional Conflict Redistrbu⁃tion 6,PCR6)是按照合取规则的逻辑,将冲突质量重新分配到非空集的最精确的数学方法,同时还满足了空信度分配(Vacuous Belief Assignment ,VBA )的中立性,并且对于合并两个以上的源有更好的直观结果[18].PCR6规则如下:∀(X ≠∅)∈D Θ,m PCR6(X )=∑Y 1∩…∩Y M =X ∏j =1Mm j()Y j+∑i =1Mm i (X )2∑∩Y ∩X ≡∅()Y ,…,Y ∈()D æèçççççççöø÷÷÷÷÷÷÷÷÷÷÷÷÷∏j =1M -1m σ(j )()Y σ(j ))m i (X )+∑j =1M -1m σ(j )()Y σ(j )(10)其中,m i (X )+∑j =1M -1mσi (j )(Y σi (j ))≠0(11)式中:Θ为辨识框架,包含一组有限的穷举假设;D Θ为超幂集,即对一个事件所有可能判定结果的集合;M 为源的数目,即测量结果的个数;Y i ∈2Θ称为焦元;m i (Y i )为广义信度分配函数;整数σi 的取值范围为[1,i -1]∪[i +1,M ],具体为:{σi (j )=j , j <iσi (j )=j +1, j ≥i(12)3.2 栅格信度分配函数在进行测量和信号处理后,得到的反射物体的距离信息和角度信息依旧存在一定误差.图10为与图 10 反射物可能存在区域及信度函数参数示意图Fig. 10 Schematic diagram of the possible region of reflectorand the belief assignment function parameter图 8 同时测量不同距离下反射物体示意图Fig. 8 Diagram of simultaneously measuring reflectors with dif⁃ferent distances图 9 不同距离下反射物体的回波信号Fig. 9 The echo signal of reflected objects at different distances26第 4 期王刚等:基于超声TOA 的环境感知超声波传感器的单个测量结果对应的反射物可能存在的区域的模型,其中梯形区域表示物体可能存在的位置,三角区域表示物体不可能存在的位置,ω为超声波传感器的波束角,γ为反射点的测量距离,θ为反射点的测量角度,2ε为测量距离γ的误差范围.针对超声波传感器和栅格地图的特点,本文建立了辨识框架Θ={θ1,θ2},θ1表示栅格被占用,θ2表示栅格没有被占用.根据DSmT 可以得到超幂集D Θ={∅,θ1,θ2,θ1∩θ2,θ1∪θ2}.地图中的每一个栅格存在M (M ≥2)次测量数据,并且把每一次测量数据都作为证据源.由此定义一组针对每个证据源的信度分配函数,m (θ1)定义栅格被占用的概率,主要由图10中的梯形区域决定,并且离测量点越远,占有概率越小.反之,m (θ2)定义栅格未被占用的概率,由图10中的三角区域决定,且与θ的角度差值越大,占有概率越小.m (θ1∩θ2)表示栅格既被占用又未被占用的概率,即冲突.m (θ1∪θ2)表示栅格未知的程度,也就是不确定度,此处指的是由测量结果得到栅格点数据的可靠程度,主要与波束角、测量距离相关.需要说明的是,由于冲突会在PCR6的计算过程中出现,因此无需建立信度分配函数m (θ1∩θ2) [19].由此,本文构建的信度分配函数m (⋅):D Θ→[0,1],如公式(13)所示:m ()θ1=ìíîïïïA /ε⋅()m ∼N ()μ1,Σ1,()0≤||α≤ω2∩()0≤d v ≤ε0 ,其他m ()θ2=ìíîïïïA ⋅()m ∼N ()μ2,Σ2,()0≤|α|≤ω2∩()0≤d <γ∩d v >ε0 ,其他m ()θ1∪θ2=1-m ()θ1-m ()θ2(13)式中:A 为根据测量距离γ与测量角度θ引入的信度函数;μ1、μ2表示正态分布的均值矩阵;Σ1、Σ2表示正态分布的协方差矩阵,上述5个参数的定义为:A =()1-φéëêêùûúú1-()γa 2()1-|α-θ|w μ1=éëêùûúd v d p Σ1=éëêêêêùûúúúú12π00ε μ2=éëêêùûúúd ||α-θ Σ2=éëêêêêùûúúúú1ωw 00w 2(14)式中:φ为不确定度参数;d 为栅格点到发射传声器的距离;d v 为栅格点Q 沿着传感器与测量点的连线TP 的方向到测量点P 的距离;d p 为栅格点Q 到连线TP 的垂直距离,具体如图10所示.图11为当测量点角度θ=15°、测量距离γ=0.5 m时,根据公式(13)得到的栅格不确定度m (θ1∪θ2).从图11中可以看出,在波束角范围内的三角区域内,栅格数据的不确定度与栅格点和测量点角度之间的差值以及离测量点的距离正相关.在波束角以外,是装置无法测量到的区域,处于完全未知的状态,因此这里的不确定度等于最大值1,而最小值出现在发射超声波传感器的位置.由于栅格点存在数据不连续的问题,因此其不确定度最小值趋近于0.通过单次测量可以得到波束角范围内栅格点的占有概率,再图 11 θ=15°,γ=0.5 m 时,由公式(13)得到的不确定度 m (θ1∪θ2)Fig. 11 The uncertainty m (θ1∪θ2) obtained by formula (13)when θ=15°,γ=0.5 m27湖南大学学报(自然科学版)2023 年叠加不同方位的测量结果进行不断融合,可以逐渐减小栅格点的不确定度,最终获得全局的环境栅格地图.4 实验结果为了验证上述方法的有效性,搭建了如图12所示的实验环境,该实验环境是由木板围成的一个矩形区域,其右上方的斜板倾角为45°,右下角存在一开口,在环境中间放置一直径为166 mm 的塑料圆柱体,各点的坐标位置如图所示.超声波传感器的移动路径如图12中的虚线所示,虚线上的圆圈标记表示测量位置.装置从实验环境的右下方开口进入后,在测量路径前进方向上的±90°范围内,间隔45°进行5次测量.实验中有27个测量点,共进行了135次测量.相较于文献[11]所需的456次测量,本文提出的方法大大减少了测量次数,从而减少了计算量.实验装置如图13所示,其中单片机(STM32F103C8T6)用于产生超声波发射传感器所需要的25 kHz 震荡信号,再通过驱动电路(L298N )驱动发射传声器发出超声信号,经反射物反射后,回波信号由接收传声器转化为电信号.该电信号经采集卡(NI USB-6356)采集后,传输给计算机进行信号分析与处理.实验中,传感器波束角ω为60°,接收传声器测量距离误差ε经多次测量确定为15 mm.图14所示为每次测量所得到的反射点位置,实线表示环境的实际轮廓,实心圆圈表示每次测量计算得到的反射点位置.从图14可以看出,由本文方法得到的测量点位置大多比较准确,基本位于环境实际轮廓的附近,但是也存在个别测量误差较大的点,误差主要出现在测量距离过近或者测量装置正对墙角的情况下,是由被测物体的多重反射造成的.但是在本文中测量装置随机游走时,这种情况出现的概率很小,其对建图结果的影响在后续的数据融合过程中逐渐被消除.通过构建每一个测量结果的栅格信度分配函数,并利用PCR6规则将多次测量得到的结果进行融合.环境栅格地图的融合过程及最终结果如图15所示,其中实线为环境的实际轮廓,虚线为测量轨迹,虚线上的圆圈标记表示测量位置,栅格的颜色深度表示栅格的占有概率,图15(a )、15(b )、15(c )分别为测量装置完成轨迹的25%(34次测量)、50%(67次测量)和75%(101次测量)时得到的环境栅格地图,图15(d )为测量装置完成全部轨迹(135次测量)后,最终融合得到的栅格地图.从图15中可以看出,随着测量次数的增加,环境的轮廓逐渐清晰,且误差较大的测量点对地图的影响逐渐减小,最终所得到的栅格占有信度高的区域基本与环境的实际轮廓重合.图15所示结果表明,所提出的方法也能获取到圆柱反射物体较清晰的轮廓信息.图 12 实验环境及测量路径(单位:mm )Fig. 12 The experimental environment and measurementpath (unit :mm)图 13 实验装置Fig. 13 The experimental device图 14 测量得到的反射点Fig. 14 The reflection points obtained by measurements28。

肺癌的诊断分析法[发明专利]

肺癌的诊断分析法[发明专利]

专利名称:肺癌的诊断分析法
专利类型:发明专利
发明人:爱德华·A·希尔施科维奇,钟丽,纳达·H·卡塔,阿诺德·J·斯托姆博格
申请号:CN200680050765.X
申请日:20061110
公开号:CN101374962A
公开日:
20090225
专利内容由知识产权出版社提供
摘要:一种用于测定患者体内存在肺癌的诊断分析法,其部分取决于确定与肺癌相关的抗体的存在。

此分析法在放射照相可检测到的癌组织的证据之前预测肺癌。

申请人:肯塔基大学
地址:美国肯塔基州
国籍:US
代理机构:北京安信方达知识产权代理有限公司
更多信息请下载全文后查看。

编码动态触觉效应[发明专利]

编码动态触觉效应[发明专利]

专利名称:编码动态触觉效应
专利类型:发明专利
发明人:H·达考斯塔,安丰天,C·J·尤尔里奇申请号:CN201810371898.1
申请日:20131011
公开号:CN108803869A
公开日:
20181113
专利内容由知识产权出版社提供
摘要:本公开涉及编码动态触觉效应。

提供了编码一种或多种动态触觉效应的系统。

该系统把动态触觉效应定义为包括多个关键帧,其中每个关键帧都包括一个插入值和对应的触觉效应。

插入值是规定插入在哪里发生的值。

该系统生成触觉效应文件,并且把动态触觉效应存储在该触觉效应文件中。

申请人:意美森公司
地址:美国加利福尼亚
国籍:US
代理机构:中国国际贸易促进委员会专利商标事务所
代理人:边海梅
更多信息请下载全文后查看。

吊孔剪切强度计算方法探讨优先出版

吊孔剪切强度计算方法探讨优先出版

工业技术科技创新导报 Science and Technology Innovation Herald45堆进行换料或维修等连接器承吊杆重量,其板联接,侧板连接,下吊孔通过销轴2 根据《材式中:F 为剪切力;A 为受剪面积;其中、及提。

2.1 确定剪切力西屋公司相关资连该额定载荷大额定载荷,取载荷试验,试验载般为1.4[1]。

为保证试截面的强度进行校定的试验载下的强度计算以西荷为=/2。

可以看出上①作者简介:湛卉(1985,10—),女,湖北襄阳人,机械工程硕士,工程师,研究方向:核电厂换料工艺和专用设备研究。

DOI:10.16660/ k i.1674-098X.2016.02.045吊孔剪切强度计算方法探讨①湛卉 瓮松峰 董岱林(中国核动力研究设计院核反应堆系统设计技术重点实验室 四川成都 610041)摘 要:核电厂各大型设备的安装均需要利用吊具,吊具的吊孔强度校核尤其是剪切强度校核尤为重要。

该文以AP1000核电厂压力容器顶盖吊具起吊连接器为例,通过理论计算和试验数据的对比,证明吊孔剪切强度经典计算模型过于保守,需进行修正。

通过三维软件应力分析结果并结合材料力学相关知识,对计算模型做出了修正,为同类结构的设计计算提供依据。

关键词:吊孔 强度校核 计算对比 三维分析 模型修正中图分类号:图1 起吊连接器侧板结构尺寸图2 西屋轴孔强度校核选取截面A位置图网络出版时间:2016-06-07 15:01:18网络出版地址:/kcms/detail/11.5640.N.20160607.1501.023.html工业技术科技创新导报 Science and Technology Innovation Herald46拉伸许用应力:Pa;剪切许用应力:Pa。

2.4 剪切应力额定载荷下,B-B截面剪切应力为:所以B-B截面在额定载荷下满足强度要求。

试验载荷下,B-B截面剪切应力为:42t 时,B-B截即理论计算不经与2013年完上进行按时出厂。

基于旅行时修正的钻孔雷达层析成像改进

基于旅行时修正的钻孔雷达层析成像改进

基于旅行时修正的钻孔雷达层析成像改进朱自强;彭凌星;密士文【摘要】基于钻孔雷达的波幅采用速度层析成像时,大收发角度雷达波幅因其信噪比低,旅行时提取较困难等问题,钻孔雷达雷达波幅层析成像精度不高.通过计算证明电磁波能量是从发射天线中心点传播至末端,再由接收天线末端传播至其中心.依据此传播路径采用互相关函数对旅行时的提取进行优化,并得到相应的电磁波波速.利用优化后的旅行时与波速得到旅行时的修正值,并根据修正后的旅行时进行速度层析成像,将进行旅行时修正的层析成像图与未进行旅行时修正的层析成像图进行对比.研究结果表明:经过旅行时修正后得到的层析成像结果更加精确,证明对钻孔雷达层析成像的改进方法是可行的.【期刊名称】《中南大学学报(自然科学版)》【年(卷),期】2015(046)007【总页数】7页(P2658-2664)【关键词】钻孔雷达;初至波旅行时;互相关函数;旅行时修正;层析成像【作者】朱自强;彭凌星;密士文【作者单位】中南大学地球科学与信息物理学院,湖南长沙,410083;中南大学地球科学与信息物理学院,湖南长沙,410083;中南大学地球科学与信息物理学院,湖南长沙,410083【正文语种】中文【中图分类】P631.320世纪70年代之后,在地质雷达的基础上,Olhoet[1]为了充分利用钻孔这一已有的通道对地下介质的结构特征等信息进行探测,提出一种新的物探方法即钻孔雷达探测。

钻孔雷达在国内的发展起步较晚,到20世纪末国内才出现有关钻孔雷达的研究,但基本上以介绍为主,之后渐渐对其应用和理论进行研究[2]。

黄家会等[3]应用钻孔雷达对地下深部灰岩地区的裂隙带和水流通道等进行探测,通过对雷达波幅进行成像对高衰减低速区、低衰减高速区与低衰减低速区等进行区分。

刘四新等[4]通过有限差分数值模拟了充水裂缝和矿体在钻孔雷达中的响应特征,证明钻孔雷达在裂缝探测中的可行性。

王飞等[5]通过有限差分模拟证明了钻孔雷达单孔反射探测可以有效确定矿体的位置和形态。

带一个插值点的最小二乘估计和最大似然估计

带一个插值点的最小二乘估计和最大似然估计

带一个插值点的最小二乘估计和最大似然估计
颜宁生
【期刊名称】《北京服装学院学报(自然科学版)》
【年(卷),期】2008(028)003
【摘要】提出了带一个点的最小二乘法,并给出了带一个点的最小二乘法拟合的最小二乘估计和最大似然估计.
【总页数】5页(P56-59,64)
【作者】颜宁生
【作者单位】北京服装学院基础课部,北京,100029
【正文语种】中文
【中图分类】O21
【相关文献】
1.关于一个Bernstein型插值过程收敛阶的点态估计 [J], 于宗文;王淑云
2.带二阶Hermite插值条件的最小二乘估计 [J], 徐艳艳;任静静;陈广贵;罗冰玉
3.带插值条件的拟线性最小二乘估计 [J], 颜宁生;李庆福;刘建筑;张雅琳;史英杰
4.关于一个Bernstein型插值多项式的点态估计 [J], 崔利宏;金明爱
5.带Hermite插值条件的最小二乘估计 [J], 颜宁生
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基因编辑酶在起作用

基因编辑酶在起作用

基因编辑酶在起作⽤摘要:科学家们第⼀次在精确切割DNA链的过程中捕获了酶的⾼分辨率三维图像。

科学家们第⼀次在精确切割DNA链的过程中捕获了酶的⾼分辨率三维图像。

使⽤称为低温电⼦显微镜或低温电⼦技术的技术捕获的图像揭⽰了有关基因编辑⼯具CRISPR-Cas9如何⼯作的新信息,这可能有助于研究⼈员开发出更⾼效,更精确地运⾏的版本。

改变靶基因。

今天发表在“ ⾃然结构与分⼦⽣物学”杂志上的研究结果为未来治疗和预防由DNA突变引起的⼀系列⼈类疾病提供了希望,从癌症到囊性纤维化和亨廷顿病。

“能够如此⾼度详细地了解Cas9究竟是如何切割和编辑DNA链的,这是令⼈兴奋的,”负责冷冻EM研究的UBC研究员Sriram Subramaniam说。

“这些图像为我们提供了宝贵的信息,可以提⾼基因编辑过程的效率,从⽽有望在未来更快,更准确地纠正导致疾病的DNA突变。

”CRISPR,CRISPR-Cas9的缩写,是⼀种基因编辑⼯具,其中Cas9酶就像⼀对能够切割DNA链的分⼦剪⼑。

⼀旦酶在特定位点切割DNA,就可以进⾏插⼊和编辑,从⽽改变DNA序列。

为了更好地理解过程中涉及的事件顺序,Subramaniam及其同事使⽤低温EM技术对Cas9酶进⾏成像。

这些图像提供了Cas9在DNA切割过程中发⽣的逐步分⼦运动的前所未有的⼀瞥,包括在释放之前仍然附着在酶上的切割DNA的快照。

“阻⽌使⽤Cas9开发更好的基因编辑⼯具的主要障碍之⼀就是我们没有任何实际切割DNA的图像,”该研究的共同资深作者,伊利诺伊⼤学研究员Miljan Simonovic说。

“但现在我们有了更清晰的图像,我们甚⾄可以看到酶的主要结构域在反应过程中是如何移动的,这可能是⼀个重要的修改⽬标。

”Subramaniam实验室是第⼀个使⽤cryo-EM实现蛋⽩质和蛋⽩质结合药物分⼦的原⼦分辨率成像的实验室。

在过去⼏年中,他们率先使⽤cryo-EM来显⽰各种蛋⽩质,包括代谢酶,脑受体和DNA-蛋⽩质复合物。

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VN VE
0
A
Introduction
VN and VE are, respectively, the north and east components o the velocity error. aN(t), aE(t), and aD(t) are the north, east, and down components of the sensed acceleration. 4>N, </>£, and <t>D are the north, east, and down components of the misalignment. Q denotes Earth rate, R is the radius of the Earth, and L and X are, respectively, the latitude and longitude of the INS. V N and V E are the north and east accelerometer error terms, whereas eN, eE, and eD are, respectively, the drifts of the north, east, and down gyros. The vertical channel of the INS is decoupled from the horizontal channels, thus its error terms do not appear in Eq. (1). It is assumed that the INS is at a constant altitude, therefore the nominal values of the vertical channel do not appear in Eq. (1) either. Consider the 5 x 5 matrix in Eq. (1) which is the error dynamics matrix that we denote by F5. When ground alignment is performed, that is, when the INS is stationary, the sensed acceleration is in the vertical direction and is equal to the gravity. Thus, only the tilt errors </>N and </>£• are directly coupled into VE and VN through the gravity of f23 and fI>4, respectively (/^ denotes the element in the /th row and the 7th column of F5)'. This coupling is a strong one since the gravity is a relatively large quantity. On the other hand, the azimuth error </>D is not coupled directly into either VN or VE; however, it is coupled indirectly into VN as follows: <t>D is coupled directly into </>£ through f45 which is the north component of Earth rate and, as was just mentioned, </>£ is coupled into VN through the gravity of /,>4\ consequently, VN is linked to <t>D. Because of the difference in the nature of the coupling of (j>D and (j)E into VN, they have different signatures in VN and are
Itzhack Y. Bar-Itzhack* and Boaz Poratf Technion—Israel Institute of Technology, Haifa, Israel
This paper addresses the question whether a constant axial acceleration maneuver is superior to a circular one during the in-flight alignment of an inertial navigation system and whether there exists a simple test or an expression that clearly indicates it. It was found in this work that when the azimuth misalignment at the end of the maneuver is the index of performance, the axial maneuver is not superior to the lateral one in general. There are, however, three classes of alignment problems in which axial maneuver is superior. These cases can be modeled by simple models that yield analytic expressions clearly indicating the superiority of the axial maneuver during the in-flight alignment of an inertial navigation system. These three classes of alignment problems encompass a large number of existing systems.
NY inertial navigation system (INS) has to undergo an initial alignment phase before it starts navigating. During this phase the attitude difference between the axes of the INS coordinate system and those of a chosen reference is estimated and removed. This attitude difference, or misalignment, consists of two tilt angles and an azimuth angle which have a distinct signature in the propagating error in the INS outputs. For this reason a Kalman filter can be successfully used to estimate the tilt and the azimuth errors of the INS. It is well known that the estimation rate of the azimuth misalignment and the final value it reaches are the two factors that determine the performance of the whole alignment process. These factors are particularly important in the initial alignment of the INS of a combat aircraft, where the aircraft has to be ready for takeoff in minimum time. The initial alignment can be performed either when the INS is at rest or while the aircraft is in motion. 1 If the initial alignment is carried out when the INS is airborne, the alignment is referred to as in-flight alignment (IFA). Classically, the INS outputs that are used to estimate the tilt and the azimuth errors are the two horizontal velocity error components. The tilt errors are strongly correlated with these velocity error components, and thus can be easily estimated. An issue of major importance, then, is the "observability magnitude" of the azimuth misalignment angle when the horizontal velocity error components are measured. To present the observability problem, we turn to Eq. (1), which is the propagation equation of the horizontal velocity error and the misalignment components for an INS whose reference coordinate system is the local level north pointing system2:
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