64 Points FFT Processor

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数字信号处理 实验报告 实验二 应用快速傅立叶变换对信号进行频谱分析

数字信号处理 实验报告  实验二 应用快速傅立叶变换对信号进行频谱分析

数字信号处理实验报告实验二应用快速傅立叶变换对信号进行频谱分析2011年12月7日一、实验目的1、通过本实验,进一步加深对DFT 算法原理合基本性质的理解,熟悉FFT 算法 原理和FFT 子程序的应用。

2、掌握应用FFT 对信号进行频谱分析的方法。

3、通过本实验进一步掌握频域采样定理。

4、了解应用FFT 进行信号频谱分析过程中可能出现的问题,以便在实际中正确应用FFT 。

二、实验原理与方法1、一个连续时间信号)(t x a 的频谱可以用它的傅立叶变换表示()()j t a a X j x t e dt +∞-Ω-∞Ω=⎰2、对信号进行理想采样,得到采样序列()()a x n x nT =3、以T 为采样周期,对)(n x 进行Z 变换()()n X z x n z +∞--∞=∑4、当ωj ez =时,得到序列傅立叶变换SFT()()j j n X e x n e ωω+∞--∞=∑5、ω为数字角频率sT F ωΩ=Ω=6、已经知道:12()[()]j a m X e X j T T Tωωπ+∞-∞=-∑ ( 2-6 )7、序列的频谱是原模拟信号的周期延拓,即可以通过分析序列的频谱,得到相应连续信号的频谱。

(信号为有限带宽,采样满足Nyquist 定理)8、无线长序列可以用有限长序列来逼近,对于有限长序列可以使用离散傅立叶变换(DFT )。

可以很好的反映序列的频域特性,且易于快速算法在计算机上实现。

当序列()x n 的长度为N 时,它的离散傅里叶变换为:1()[()]()N knN n X k DFT x n x n W-===∑ 其中2jNN W eπ-=,它的反变换定义为:101()[()]()N knN k x n IDFT X k X k W N --===∑比较Z 变换式 ( 2-3 ) 和DFT 式 ( 2-7 ),令kN z W -=则1()()[()]|kNN nkN N Z W X z x n W DFT x n ---====∑ 因此有()()|kNz W X k X z -==k N W -是Z 平面单位圆上幅角为2kNπω=的点,也即是将单位圆N 等分后的第k 点。

超高速全并行快速傅里叶变换器

超高速全并行快速傅里叶变换器

超高速全并行快速傅里叶变换器陈杰男;费超;袁建生;曾维棋;卢浩;胡剑浩【摘要】设计和实现超高速快速傅里叶变换器(FFT)在雷达与未来无线通信等系统中具有重要意义。

该文提出首个全并行架构的FFT处理器,其避免了复杂的路由寻址以及数据访问冲突等问题,基于较大基进行分解降低运算复杂度。

由于旋转因子已知和固定,大量的乘法转化为了定系数乘法。

同时由于采用了串行的计算单元,在达到全并行结构的高速度同时硬件复杂度相对较低;所有的硬件计算单元处于满载的条件,其硬件效率能达到100%。

根据实际的实现结果,所提出的512点FFT处理器结构能够达到5.97倍速度面积比的提升,同时硬件开销仅占用了Xilinx V7-980t FPGA 30%的查找表资源与9%的寄存器资源。

%The design and implementation of ultra-high-speed FFT processor is imperative in radar system and prospective wireless communication system. In this paper, the fully-parallel-architecture FFT with bit-serial arithmetic is proposed. This method avoids the complexity of data addressing, access and routing. Based on the high-radix factorization, the multiplication number can be reduced. Out of the reason that twiddle factors are fixed in the design, constant coefficient optimization can be used in multiplications. Besides,bit-serial arithmetic cuts down the hardware cost, and makes the computation elements full-load to get a 100% efficiency. As a result, the presented 512-point FFT processer has 5.97 times gain in speed-throughput ratio while its hardware only accounts for 30% LUTs and9%registers resource based on Xilinx V7-980t FPGA.【期刊名称】《电子与信息学报》【年(卷),期】2016(038)009【总页数】5页(P2410-2414)【关键词】快速傅里叶变换;全并行;比特串行计算;常系数乘法【作者】陈杰男;费超;袁建生;曾维棋;卢浩;胡剑浩【作者单位】电子科技大学通信抗干扰国家级重点实验室成都 611731;电子科技大学通信抗干扰国家级重点实验室成都 611731;电子科技大学通信抗干扰国家级重点实验室成都 611731;电子科技大学通信抗干扰国家级重点实验室成都611731;电子科技大学通信抗干扰国家级重点实验室成都 611731;电子科技大学通信抗干扰国家级重点实验室成都 611731【正文语种】中文【中图分类】TN471 引言FFT(Fast Fourier Transform)作为技术核心之一广泛应用于雷达以及无线通信领域。

一种高效的FFT处理器地址快速生成方法

一种高效的FFT处理器地址快速生成方法

Cohen[31提出的方法,他用一个循环移位器来生成所需操作
数地址。定义RL(x,i)函数表示将工旋转左移i位,应用Cohen
的方法,第P级循环计算中第q次基2蝶形运算对应的操作 数地址为:
q。=RL(2q,P一1)
(8)
qt=RL(2q+1,P一1)
(9)
这种方法生成的操作数的低位地址是在高位地址遍历
实际上,虽然各级计算高位地址与低位地址的长度都在 变化,但高位地址与低位地址的长度之和是保持不变的,如 果能在地址产生时将它们结合在一起,不但可以节省一个 M.1位计数器的硬件开销,还可以解决上文中提到的由于地 址分割带来的一系列问题。
3现有的方案与缺陷
目前移动应用的FFT处理器设计中较常采用的是D.
我们知道,在FFr的计算过程中,每级循环计算中各 蝶形运算的先后顺序是任意的,因此地址产生方案并不是一 定要按顺序方式生成地址,例如D.Cohen[31中采用的就不是 完全顺序方式,只要能按蝶形对的约束遍历全部操作数即 可。这样,我们的问题就转变成寻找一种合适的地址产生顺 序,它的地址变化是从a。到a,的变化传递,而且各个地址 位与蝶算次数计数器间存在一种简单的对应关系。
关键词:快速傅立叶变换(R叩);地址产生器;旋转因子:蝶形运算
A Highly Efficient and Fast Address Generation Scheme for FFT Processor
Yang Liang
Hung Jin Liu Hongxia Zhang Kewei
(Lishan Micro-electronics Corp.710054)
lx00 000
0x01 010
lx01 010
OxlO 100

Simplified Control of FFT Wardware

Simplified Control of FFT Wardware
CORRESPONDENCE
EXAMPLE 2-LOW-PASS:
a,
TABLE 1V FINAL DESIGN REPORTED BY
b ,
DUROIS AND
LEICH
a,
b,
-1.4831794 -1.4494845 -1.5038398 -1.4782185 -0.4281718
1 . 8 1 . 0 1 . 0
EXAMPLE 2---LOW-PASS: THE OPTIMIZED DESIGN FROM FLETCHER-POWELL PROCEDURE WITH MATCHING STOP-BAND
a2
1 . 0
al -1.102534 0.812d5472 ,-1.4644795 -8.194671. d.91474971 -1.4829583 -1.407262 -1.338~b3
(8, 9) (10, 11) (12, 13) (14, 15) (8,10) ( 9, 11) (12, 14) (13, 15) ( 3, 7) (8, 12) ( 9, 13) (10, 14) (11, 15) ( 3,11) (4, 12) ( 5 , 13) ( 6, 14) ( 7 , 15)
-1.182534 -8.194671 -1.407262
0.64162667 8.88639a89 0.97502064 0.98668656 0 . 8
1. -1.338983 8
1 . 8 0 . 0
Note: Gain constantk = 0.0078599138.
mEa
IN HZ
Fig. 4 . Example 2: pass-bandsfromDuboisandLeich(D-L)result and from Fletcher-Powell (F-P) procedure; all specifications satisfied, stop-bands matching.

512点FFT算法实现

512点FFT算法实现

512点FFT算法实现N=512 points FFT Program ****************************************************************** ***.title "fft.asm".mmregs.copy "coeff.inc".def _c_int00sine: .usect "sine",512cosine: .usect "cosine",512fft_data: .usect "fft_data",2048d_input: .usect "d_input",2048fft_out: .usect "fft_out",512STACK .usect "STACK",9K_DATA_IDX_1 .set 2K_DATA_IDX_2 .set 4K_DATA_IDX_3 .set 8K_TWID_TBL_SIZE .set 128K_TWID_IDX_3 .set 32K_FLY_COUNT_3 .set 4*** N points FFT ***K_FFT_SIZE .set 256 ;NK_LOGN .set 9 ;LOG(N) =512 则N=9PA0 .set 0PA1 .set 1.bss d_twid_idx,1.bss d_data_idx,1.bss d_grps_cnt,1.sect "fft_prg" ;*** 位码倒序Bit Reversal Routine ***.asg AR2,REORDERED ;AR2中装入第一个位倒序数据指针.asg AR3,ORIGINAL_INPUT ;AR3中放入输入地址.asg AR7,DA TA_PROC_BUF ;AR7中放入处理后输出的地址.textStart:SSBX FRCTSTM #STACK+9,SPSTM #d_input,AR1RPT #2*K_FFT_SIZE-1PORTR PA1,*AR1+STM #sine,AR1 ;正弦系数表RPT #255 ;MVPD sine1,*AR1+STM #cosine,AR1 ;RPT #255 ;MVPD cosine1,*AR1+STM #d_input,ORIGINAL_INPUTSTM #fft_data,DATA_PROC_BUFMVMM DATA_PROC_BUF,REORDERED ;RECORDERED point fft_data too STM #K_FFT_SIZE-1,BRCRPTBD bit_rev_end-1STM #K_FFT_SIZE,AR0 ;this is double words order MVDD *ORIGINAL_INPUT+,*REORDERED+ ;Bit ReversalMVDD *ORIGINAL_INPUT-,*REORDERED+MAR *ORIGINAL_INPUT+0Bbit_rev_end:* * * * FFT Code * * * * *.asg AR1,GROUP_COUNTER ;定义FFT计算的组指针.asg AR2,PX ;AR2指向蝶型运算的第一个数据指针.asgAR3,QX ;AR3指向蝶型运算的第二个数据指针.asg AR4,WR ;AR4指向余弦表的指针.asg AR5,WI ;AR5指向正弦表的指针.asg AR6,BUTTERFL Y_COUNTER ;AR6指向蝶形结的指针.asg AR7,STAGE_COUNTER ;定义数据处理缓冲指针* * * stage 1级蝶形运算,计算2点的FFT * * *STM #0, BK ;让BK=0,使*ARn+0%=*ARn+0 why not=16? LD #-1, ASM ;每步输出时右移一位避免溢出STM #fft_data, PX ;PX指向蝶型运算第一个数的实部LD *PX,16,A ;AH:=Re[x(0)] AH=PRSTM #fft_data+K_DATA_IDX_1,QX ;QX point 蝶形运算第二个数的实部STM #K_FFT_SIZE/2-1,BRC ;stage 1 is N/2-1设置循环块计数器RPTBD stage1end-1STM #K_DA TA_IDX_1+1,AR0SUB *QX,16,A,B ;BH=Re[x(0)]-Re[x(4)] BH=PR-QRADD *QX,16,A ;AH=Re[x(0)]+ Re[x(4)] AH=PR+QRSTH A,ASM,*PX+ ;PRV=(PR+QR)/2ST B,*QX+ ;QRV=(PR-QR)/2||LD *PX,A ;AH=PISUB *QX,16,A,B ;BH=Im[x(0)]-Im[x(4)] BH=PI-QIADD *QX,16,A ;AH=Im[x(0)]+Im[x(4)] AH=PI+QISTH A,ASM,*PX+0 ;PIV=(PI+QI)/2ST B,*QX+0% ;PIV=(PI-QI)/2;BK=0 why here circle access ?||LD *PX,A AH为下一个PRstage1end:* * * Stage 2 第二级计算4点的FFT* * *STM #fft_data,PXSTM #fft_data+K_DATA_IDX_2,QXSTM #K_FFT_SIZE/4-1,BRCLD *PX,16,A ;AH=Re[x(0)]+ Re[x(4)],AH=1RPTBD stage2end-1STM #K_DA TA_IDX_2+1,AR0;1st butterflySUB *QX,16,A,B ;BH={Re[x(0)]+ Re[x(4)]}-{Re[x(2)]+ Re[x(6)]},BH=0 ADD *QX,16,A ;AH={Re[x(0)]+ Re[x(4)]}+{Re[x(2)]+ Re[x(6)]},AH=2 STH A,ASM,*PX+ST B,*QX+||LD *PX,ASUB *QX,16,A,B ;BH={Im[x(0)]+ Im[x(4)]}-{Im[x(2)]+ Im[x(6)]},BH=0 ADD *QX,16,A ;AH={Im[x(0)]+ Im[x(4)]}+{Im[x(2)]+ Im[x(6)]},BH=0 STH A,ASM,*PX+ ;PIV=(PI+QI)/2STH B,ASM,*QX+ ;PIV=(PI-QI)/2;2nd butterflyMAR *QX+ ;QX中地址加1ADD *PX,*QX,A ;AH=PR+QISUB *PX,*QX-,B ;BH=PR-QISTH A,ASM,*PX+ ; PRV=(PI+QI)/2SUB *PX,*QX,A ;AH=PR-QIST B,*QX ;QRV=(PI-QI)/2||LD *QX+,B ;BH=QR very important, " BH= {Re[x(2)]- Re[x(6)]} ",=1 ST A,*PX ; PIV=(PI-QR)/2||ADD *PX+0%,A ; AH=PI+QRST A,*QX+0% ;QIV=(PI+QR)/2||LD *PX,A ;AH=PRStage2end:* * * Stage 3 through Stage logN * * *STM #K_TWID_TBL_SIZE,BK ;为旋转因子表格的大小值ST #K_TWID_IDX_3,d_twid_idx ;初始化旋转表格索引值STM #K_TWID_IDX_3,AR0 ;AR0=旋转表格初始索引值STM #cosine,WR ;初始化WR指针STM #sine,WI ;初始化WI指针STM #K_LOGN-2-1,STAGE_COUNTER ;初始化步骤指针ST #K_FFT_SIZE/8-1,d_grps_cnt ;初始化组指针STM #K_FL Y_COUNT_3-1,BUTTERFL Y_COUNTER ;初始化蝶形结指针ST #K_DATA_IDX_3,d_data_idx ;初始化输入数据的索引stage:STM #fft_data,PX ;PX指向参加蝶形运算第一个数据的实部PR LD d_data_idx,A ;A:=8ADD *(PX),A ;A:=2008STLM A,QX ; QX 指向参加蝶形运算第二个数据的实部QR MVDK d_grps_cnt,GROUP_COUNTERgroup:MVMD BUTTERFLY_COUNTER,BRC ;将每组蝶形结的个数装入BRC RPTBD butterflyend-1LD *WR,T ;T:=1,cos0MPY *QX+,A ;A=QR*WR || QX*QIMACR *WI+0%,*QX-,A ; A=QR*WR +QI*WIADD *PX,16,A,B ;B=A+PRST B,*PX ;PRV=((QR*WR+QI*WI)+PR)/2||SUB *PX+,B ;B=PR-(QR*WR+QI*WI)ST B,*QX ; QRV=PR-(QR*WR+QI*WI)/2||MPY *QX+,A ;A=QR*WR[T=WI] QX指向QIMASR *QX,*WR+0%,A ;AQR*WI-QI*WRADD *PX,16,A,B ;B=QR*WI-QI*WR)+PIST B,*QX+ ;(QIV= QR*WI-QI*WR)+PI)/2 QX指向QR||SUB *PX,B ;B= 皮(QR*WI-QI*WR)B= 0000000000 ,00FFFE0000 LD *WR,T ;T=WRST B,*PX+ ;PIV=(PI-(QR*WI-QI*WR))/2||MPY *QX+,A ;A=QR*WR||QX指向QIbutterflyend:*********************************************************Update pointers for next groupPSHM AR0 ;保存AR0MVDK d_data_idx,AR0 ;AR0中装入该步运算中每组所用蝶形结数目MAR *PX+0MAR *QX+0BANZD group,*GROUP_COUNTER-POPM AR0 ;恢复AR0MAR *QX-;Update 更新计数器和其他索引数据以进入下一步骤LD d_data_idx,A ;A:=8SUB #1,A,B ;B:=7STLM B,BUTTERFL Y_COUNTER ;修改蝶形结个数计数器butterfly_counter:=7STL A,1,d_data_idx ;下一步计算的数据索引翻倍d_data_idx:=4 LD d_grps_cnt,A ;A:=0(8/8-1)STL A,ASM,d_grps_cnt ;下一步计算的组数目减少一半d_grps_cnt=A/2LD d_twid_idx,A ;A:=128STL A,ASM,d_twid_idx ;下一步计算的旋转因子索引减少一半d_twid_idx=A/2BANZD stage,*STAGE_COUNTER- ;stage_counter:=0MVDK d_twid_idx,AR0 ;AR0为旋转因子索引fft_end:* * * 计算功率谱Compute the power spectrum * * *STM #fft_data,AR2STM #fft_data,AR3STM #fft_out,AR4STM #K_FFT_SIZE-1,BRC RPTB power_end-1 SQUR *AR2+,A SQURA *AR2+,ASTH A,*AR4+power_end:STM #fft_out,AR4RPT #K_FFT_SIZE-1 PORTW *AR4+,PA0 here: B here.end。

PowerPC和DSP对比

PowerPC和DSP对比

PowerPC和DSP对比一、主要性能参数对比General-Purpose Algorithm Benchmarks on TI’s C66x DSP Core at 1.25 GHz1主要DSP的浮点性能对比:Speed Scores for floating-point packaged processors BDTImark2000(BDTI认证结果)(BDTI主要是针对DSP的benchmark,没有MPC7410和Powerpc的数据)一些算法,像FFT,可以充分利用7410的矢量数学运算。

1024点,浮点复数FFT可以在27us内完成,相比之下,C6701需要108us。

其他算法,像无线应用中的turbo解码器,VLIW结构处理的更有效率。

很明显,具有AltiVec核的PowerPC G4(74xx)具有较高的核时钟速率与性能。

P O W e r P C 的核时钟速率几乎是目前T i g e r s H A R C的3.3倍(不久更快版本的TigerSHARC将发布)。

AltiVec核每个周期执行单条指令,每128位向量包含4个独立的32位数据单元,这就是众所周知的sIM-D(单指令多数据)结构。

当执行一次乘加(MAC)矢量运算时,达到峰值处理能力,每周期可完成8次浮点操作。

对于1 GHz的MPC7455,峰值处理能力可达8000M 次/s浮点运算。

AltiVec每周期能执行8次整数或定点操作,峰值整数运算能力为8000MOPS(百万次操作/s)。

相反,TigerSHARC有两个独立的32位处理器核,或称MIMD(多指令多数据)结构。

每个计算单元每周期能执行一次乘法以及和差分运算,对于300 MHz ADSPTSl0lS每周期完成6次浮点运算或1800MFLOPS峰值运算能力。

当执行16位整数运算时,TigerSHARC 可以利用它的超标量体系结构,分离两个独立3 2位计算单元成2个单独的16位S1MD单元。

计算机专用术语英文及中文翻译

计算机专用术语英文及中文翻译

计算机术语大全1、CPU3DNow!(3D no waiting,无须等待的3D处理)AAM(AMD Analyst Meeting,AMD分析家会议)ABP(Advanced Branch Prediction,高级分支预测)ACG(Aggressive Clock Gating,主动时钟选择)AIS(Alternate Instruction Set,交替指令集)ALA T(advanced load table,高级载入表)ALU(Arithmetic Logic Unit,算术逻辑单元)Aluminum(铝)AGU(Address Generation Units,地址产成单元)APC(Advanced Power Control,高级能源控制)APIC(Advanced rogrammable Interrupt Controller,高级可编程中断控制器)APS(Alternate Phase Shifting,交替相位跳转)ASB(Advanced System Buffering,高级系统缓冲)A TC(Advanced Transfer Cache,高级转移缓存)A TD(Assembly Technology Development,装配技术发展)BBUL(Bumpless Build-Up Layer,内建非凹凸层)BGA(Ball Grid Array,球状网阵排列)BHT(branch prediction table,分支预测表)Bops(Billion Operations Per Second,10亿操作秒)BPU(Branch Processing Unit,分支处理单元)BP(Brach Pediction,分支预测)BSP(Boot Strap Processor,启动捆绑处理器)BTAC(Branch Target Address Calculator,分支目标寻址计算器)CBGA (Ceramic Ball Grid Array,陶瓷球状网阵排列)CDIP (Ceramic Dual-In-Line,陶瓷双重直线)Center Processing Unit Utilization,中央处理器占用率CFM(cubic feet per minute,立方英尺秒)CMT(course-grained multithreading,过程消除多线程)CMOS(Complementary Metal Oxide Semiconductor,互补金属氧化物半导体)CMOV(conditional move instruction,条件移动指令)CISC(Complex Instruction Set Computing,复杂指令集计算机)CLK(Clock Cycle,时钟周期)CMP(on-chip multiprocessor,片内多重处理)CMS(Code Morphing Software,代码变形软件)co-CPU(cooperative CPU,协处理器)COB(Cache on board,板上集成缓存,做在CPU卡上的二级缓存,通常是内核的一半速度))COD(Cache on Die,芯片内核集成缓存)Copper(铜)CPGA(Ceramic Pin Grid Array,陶瓷针型栅格阵列)CPI(cycles per instruction,周期指令)CPLD(Complex Programmable Logic Device,複雜可程式化邏輯元件)CPU(Center Processing Unit,中央处理器)CRT(Cooperative Redundant Threads,协同多余线程)CSP(Chip Scale Package,芯片比例封装)CXT(Chooper eXTend,增强形K6-2内核,即K6-3)Data Forwarding(数据前送)dB(decibel,分贝)DCLK(Dot Clock,点时钟)DCT(DRAM Controller,DRAM控制器)DDT(Dynamic Deferred Transaction,动态延期处理)Decode(指令解码)DIB(Dual Independent Bus,双重独立总线)DMT(Dynamic Multithreading Architecture,动态多线程结构)DP(Dual Processor,双处理器)DSM(Dedicated Stack Manager,专门堆栈管理)DSMT(Dynamic Simultaneous Multithreading,动态同步多线程)DST(Depleted Substrate Transistor,衰竭型底层晶体管)DTV(Dual Threshold V oltage,双重极限电压)DUV(Deep Ultra-Violet,纵深紫外光)EBGA(Enhanced Ball Grid Array,增强形球状网阵排列)EBL(electron beam lithography,电子束平版印刷)EC(Embedded Controller,嵌入式控制器)EDB(Execute Disable Bit,执行禁止位)EDEC(Early Decode,早期解码)Embedded Chips(嵌入式)EM64T(Extended Memory 64 Technology,扩展内存64技术)EPA(edge pin array,边缘针脚阵列)EPF(Embedded Processor Forum,嵌入式处理器论坛)EPL(electron projection lithography,电子发射平版印刷)EPM(Enhanced Power Management,增强形能源管理)EPIC(explicitly parallel instruction code,并行指令代码)EUV(Extreme Ultra Violet,紫外光)EUV(extreme ultraviolet lithography,极端紫外平版印刷)FADD(Floationg Point Addition,浮点加)FBGA(Fine-Pitch Ball Grid Array,精细倾斜球状网阵包装)FBGA(flipchip BGA,轻型芯片BGA)FC-BGA(Flip-Chip Ball Grid Array,翻转芯片球形网阵包装)FC-LGA(Flip-Chip Land Grid Array,翻转接点网阵包装)FC-PGA(Flip-Chip Pin Grid Array,翻转芯片球状网阵包装)FDIV(Floationg Point Divide,浮点除)FEMMS:Fast EntryExit Multimedia State,快速进入退出多媒体状态FFT(fast Fourier transform,快速热欧姆转换)FGM(Fine-Grained Multithreading,高级多线程)FID(FID:Frequency identify,频率鉴别号码)FIFO(First Input First Output,先入先出队列)FISC(Fast Instruction Set Computer,快速指令集计算机)flip-chip(芯片反转)FLOPs(Floating Point Operations Per Second,浮点操作秒)FMT(fine-grained multithreading,纯消除多线程)FMUL(Floationg Point Multiplication,浮点乘)FPRs(floating-point registers,浮点寄存器)FPU(Float Point Unit,浮点运算单元)FSUB(Floationg Point Subtraction,浮点减)GFD(Gold finger Device,金手指超频设备)GHC(Global History Counter,通用历史计数器)GTL(Gunning Transceiver Logic,射电收发逻辑电路)GVPP(Generic Visual Perception Processor,常规视觉处理器)HL-PBGA表面黏著,高耐热、轻薄型塑胶球状网阵封装HTT(Hyper-Threading Technology,超级线程技术)Hz(hertz,赫兹,频率单位)IA(Intel Architecture,英特尔架构)IAA(Intel Application Accelerator,英特尔应用程序加速器)IA TM(Intel Advanced Thermal Manager,英特尔高级热量管理指令集)ICU(Instruction Control Unit,指令控制单元)ID(identify,鉴别号码)IDF(Intel Developer Forum,英特尔开发者论坛)IDMB(Intel Digital Media Boost,英特尔数字媒体推进指令集)IDPC(Intel Dynamic Power Coordination,英特尔动态能源调和指令集)IEU(Integer Execution Units,整数执行单元)IHS(Integrated Heat Spreader,完整热量扩展)ILP(Instruction Level Parallelism,指令级平行运算)IMM Intel Mobile Module, 英特尔移动模块Instructions Cache,指令缓存Instruction Coloring(指令分类)IOPs(Integer Operations Per Second,整数操作秒)IPC(Instructions Per Clock Cycle,指令时钟周期)ISA(instruction set architecture,指令集架构)ISD(inbuilt speed-throttling device,内藏速度控制设备)ITC(Instruction Trace Cache,指令追踪缓存)ITRS(International Technology Roadmap for Semiconductors,国际半导体技术发展蓝图)KNI(Katmai New Instructions,Katmai新指令集,即SSE)Latency(潜伏期)LDT(Lightning Data Transport,闪电数据传输总线)LFU(Legacy Function Unit,传统功能单元)LGA(land grid array,接点栅格阵列)LN2(Liquid Nitrogen,液氮)Local Interconnect(局域互连)MAC(multiply-accumulate,累积乘法)mBGA (Micro Ball Grid Array,微型球状网阵排列)nm(namometer,十亿分之一米毫微米)MCA(Machine Check Architecture,机器检查架构)MCU(Micro-Controller Unit,微控制器单元)MCT(Memory Controller,内存控制器)MESI(Modified, Exclusive, Shared, Invalid:修改、排除、共享、废弃)MF(MicroOps Fusion,微指令合并)mm(micron metric,微米)MMX(MultiMedia Extensions,多媒体扩展指令集)MMU(Multimedia Unit,多媒体单元)MMU(Memory Management Unit,内存管理单元)MN(model numbers,型号数字)MFLOPS(Million Floationg PointSecond,每秒百万个浮点操作)MHz(megahertz,兆赫)mil(PCB 或晶片佈局的長度單位,1 mil = 千分之一英寸)MIMD(Multi Instruction Multiple Data,多指令多数据流)MIPS(Million Instruction Per Second,百万条指令秒)MOESI(Modified, Owned, Exclusive, Shared or Invalid,修改、自有、排除、共享或无效)MOF(Micro Ops Fusion,微操作熔合)Mops(Million Operations Per Second,百万次操作秒)MP(Multi-Processing,多重处理器架构)MPF(Micro processor Forum,微处理器论坛)MPU(Microprocessor Unit,微处理器)MPS(MultiProcessor Specification,多重处理器规范)MSRs(Model-Specific Registers,特别模块寄存器)MSV(Multiprocessor Specification V ersion,多处理器规范版本)MVP(Mobile V oltage Positioning,移动电压定位)IVNAOC(no-account OverClock,无效超频)NI(Non-Intel,非英特尔)NOP(no operation,非操作指令)NRE(Non-Recurring Engineering charge,非重複性工程費用)OBGA(Organic Ball Grid Arral,有机球状网阵排列)OCPL(Off Center Parting Line,远离中心部分线队列)OLGA(Organic Land Grid Array,有机平面网阵包装)OoO(Out of Order,乱序执行)OPC(Optical Proximity Correction,光学临近修正)OPGA(Organic Pin Grid Array,有机塑料针型栅格阵列)OPN(Ordering Part Number,分类零件号码)PA T(Performance Acceleration Technology,性能加速技术)PBGA(Plastic Pin Ball Grid Array,塑胶球状网阵排列)PDIP (Plastic Dual-In-Line,塑料双重直线)PDP(Parallel Data Processing,并行数据处理)PGA(Pin-Grid Array,引脚网格阵列),耗电大PLCC (Plastic Leaded Chip Carriers,塑料行间芯片运载)Post-RISC(加速RISC,或后RISC)PPE(Power Processor Element,Power处理器元件)PPU(Physics Processing Unit,物理处理单元)PR(Performance Rate,性能比率)PIB(Processor In a Box,盒装处理器)PM(Pseudo-Multithreading,假多线程)PPGA(Plastic Pin Grid Array,塑胶针状网阵封装)PQFP(Plastic Quad Flat Package,塑料方块平面封装)PSN(Processor Serial numbers,处理器序列号)QFP(Quad Flat Package,方块平面封装)QSPS(Quick Start Power State,快速启动能源状态)RAS(Return Address Stack,返回地址堆栈)RAW(Read after Write,写后读)REE(Rapid Execution Engine,快速执行引擎)Register Contention(抢占寄存器)Register Pressure(寄存器不足)Register Renaming(寄存器重命名)Remark(芯片频率重标识)Resource contention(资源冲突)Retirement(指令引退)RISC(Reduced Instruction Set Computing,精简指令集计算机)ROB(Re-Order Buffer,重排序缓冲区)RSE(register stack engine,寄存器堆栈引擎)RTL(Register Transfer Level,暫存器轉換層。

ADAMS后处理—曲线图

ADAMS后处理—曲线图

ADAMS/PostProcessor绘制仿真结果的曲线图将仿真结果用曲线图的形式表达出来,能更深刻地了解模型的特性。

ADAMS/PostProcessor能够绘制仿真自动生成结果的曲线图,包括间隙检查等,还可将结果以用户定义的量度或需求绘制出来,甚至可以将输入进来的测试数据绘制成曲线。

绘制出的曲线由数据点组成,每个数据点代表在仿真中每个输出步长上创建的输出点的数据。

在创建了曲线之后,可以在曲线上进行后处理操作,比如通过信号处理进行数据过滤,以及数学运算等。

也可以手动改变数值或者写表达式来定义曲线上的数值。

7.4.1 由仿真结果绘制曲线图的类型ADAMS提供了由几种不同类型仿真结果绘制曲线图的功能。

对象(Object)—模型中物体的特性,如某个构件的质心位置等。

如果要察看物体的特性曲线图,必须先运行ADAMS/View后再进入ADAMS/PostProcessor,或者导入一个命令文件(.cmd)。

量度(Measure)—模型中可计量对象的特性,如施加在弹簧阻尼器上的力或者物体之间的相互作用。

也可以直接在ADAMS产品中创建量度,或者导入测试数据作为量度。

要察看量度的话,需要先运行ADAMS/View后运行ADAMS/PostProcessor,或者导入一个模型和结果文件(.res)。

结果(Result)—ADAMS在仿真过程中计算出的一套基本状态变量。

ADAMS在每个仿真输出步长上输出数据。

一个结果的构成通常是以时间为横坐标的特定量(比如,构件的x方向位移或者铰链上y方向的力矩)。

请求(Request)—要求ADAMS/Solver输出的数据。

可以得到要考察的位移、速度、加速度、或者力的信息。

系统模态—察看线性化仿真得到的离散特征值。

间隙分析—察看动画中的物体之间的最小距离。

在绘制曲线图模式下,用控制面板选择需要绘制的仿真结果。

在选择了仿真结果以绘制曲线后,可以安排结果曲线的布局,包括增加必要的轴线、确定量度单位的标签、曲线的标题、描叙曲线数据的标注等等。

PowerPC和DSP对比

PowerPC和DSP对比

PowerPC和DSP对比一、主要性能参数对比ASDP tigersharp主要参数Word 资料Word 资料主要DSP的浮点性能对比:Speed Scores for floating-point packaged processors BDTImark2000(BDTI认证结果) Word 资料(BDTI主要是针对DSP的benchmark,没有MPC7410和Powerpc的数据)一些算法,像FFT,可以充分利用7410的矢量数学运算。

1024点,浮点复数FFT可以在27us内完成,相比之下,C6701需要108us。

其他算法,像无线应用中的turbo解码器,VLIW结构处理的更有效率。

很明显,具有AltiVec核的PowerPC G4(74xx)具有较高的核时钟速率与性能。

P O W e r P C 的核时钟速率几乎是目前T i g e r s H A R C的3.3倍(不久更快版本的TigerSHARC将发布)。

AltiVec核每个周期执行单条指令,每128位向量包含4个独立的32位数据单元,这就是众所周知的sIM-D(单指令多数据)结构。

当执行一次乘加(MAC)矢量运算时,达到峰值处理能力,每周期可完成8次浮点操作。

对于1 GHz的MPC7455,峰值处理能力可达8000M 次/s浮点运算。

AltiVec每周期能执行8次整数或定点操作,峰值整数运算能力为8000MOPS(百万次操作/s)。

相反,TigerSHARC有两个独立的32位处理器核,或称MIMD(多指令多数据)结构。

每个计算单元每周期能执行一次乘法以及和差分运算,对于300 MHz ADSPTSl0lS每周期完成6次浮点运算或1800MFLOPS峰值运算能力。

当执行16位整数运算时,TigerSHARC 可以利用它的超标量体系结构,分离两个独立3 2位计算单元成2个单独的16位S1MD单元。

这样每个操作在两个数据单元,每个周期总共12次操作。

基于GPU的MTD性能优化

基于GPU的MTD性能优化

火控雷达技术Fie Control Radar Technology第50卷第1期(总第195期)2021年3月Vol. 50 Na 1( Series 195)Mar. 2021基于GPU 的MTD 性能优化杨千禾袁子乔扈月松(西安电子工程研究所 西安 710100)摘 要:为了解决传统雷达信号处理机在研发阶段面临的调试困难,计算能力受硬件限制及程序复用性差等问题,本文提出了使用GPU 作为雷达计算核心的方案。

在使用GPU 实现雷达信号处理算法的过程中,动目标检测(MTD )部分的优化效果远低于脉冲压缩和恒虚警检测。

经过分析, MTD 过程中的矩阵转置与向量点乘占据了算法的大量时间。

本文从GPU 的数据读取方式和CU-DA 函数特性入手,优化快速傅里叶变换实现MTD 的过程,并在GPU 上使用CUBLAS 矩阵运算实现有限脉冲响应滤波器组对脉冲压缩之后数据的滤波,实现了更具灵活性的MTD 。

最终得到的 GPU 计算结果与CPU 平台实现的结果相比,误差不超过0.05%,同时实现了相比CPU 平台优化实现最多200余倍的性能提升。

关键词:动目标检测;GPU ;异构处理平台;CUBLAS中图分类号:TN95 文献标志码:A 文章编号:1008 -8652(2021)01 -086 -08引用格式:杨千禾,袁子乔,扈月松.基于GPU 的MTD 性能优化[J ].火控雷达技术,2021,50 (1):86 -93.DOI :10.19472/j. oki. 1008 -8652.2021.01.016Performance Optimization of MTD Basee on GPUYANG Qianhe $ YUAN Ziqiao $ HU Yuesong(Xiin Electronic Engineering Research Institute $ Xiin 710100 )Abstract : In order to solve the problems of adjustwent , hardware limitation and program reusability of traditional ra ­dar signal processor in the research and development stage , this paper proposes a scheme of using GPU as the compu ­ting core of radar. In the process of using GPU to realize radar signal processing algorithms , the improvement in mov ­ing target detection ( MTD ) is far les s than that in PC and CFAR. Our anCysis reveals that the matne transpose and vector point multiplication occupy a lot of time in the MTD process. This paper starts with the data reading mode ofGPU and the characteristics of CUD A function , optimizes the process of fast Fourier transform based MTD, and uses CUBLAS matne opvation on GPU to enable data filteUng after pulse ompnsion by finite impulse response filter bank , so as to realize more flexible MTD. Compared with the results of a CPU plaVorm , the error of the final GPU cal ­culation results is less than 0.05% , and the performance improvement is 200 times of that of the CPU platform.Keyworit : MTD ; GPU ; heterogeneous computing platform ; CUBLAS节。

智能融合cSoC:多通道FFT共享处理器使用FPGA纤维说明书

智能融合cSoC:多通道FFT共享处理器使用FPGA纤维说明书

Application Note AC381February 20121© 2012 Microsemi Corporation SmartFusion cSoC: Multi-Channel FFT Co-Processor Using FPGA FabricTable of ContentsIntroductionThe SmartFusion ® customizable system-on-chip (cSoC) device integrates FPGA technology with a hardened ARM ® Cortex™-M3 processor based microcontroller subsystem (MSS) and programmable high-performance analog blocks built on a low power flash semiconductor process. The MSS consists of hardened blocks such as a 100 MHz ARM Cortex-M3 processor, peripheral direct memory access (PDMA), embedded nonvolatile memory (eNVM), embedded SRAM (eSRAM), embedded FlashROM (eFROM), external memory controller (EMC), Watchdog Timer, the Philips Inter-Integrated Circuit (I 2C),serial peripheral interface (SPI), 10/100 Ethernet controller, real-time counter (RTC), GPIO block, fabric interface controller (FIC), in-application programming (IAP), and analog compute engine (ACE).The SmartFusion cSoC device is a good fit for applications that require interface with many analog sensors and analog channels. SmartFusion cSoC devices have a versatile analog front-end (AFE) that complements the ARM Cortex-M3 processor based MSS and general-purpose FPGA fabric. The SmartFusion AFE includes three 12-bit successive approximation register (SAR) ADCs, one first order sigma-delta DAC (SDD) per ADC, high performance signal conditioning blocks, and comparators. The SmartFusion cSoCs have a sophisticated controller for the AFE called the ACE. The ACE configures and sequences all the analog functions using the sample sequencing engine (SSE) and post-processes the results using the post processing engine (PPE) and handles without intervention of Cortex-M3 processor.Refer to the SmartFusion Programmable Analog User’s Guide for more details.This application note describes the capability of SmartFusion cSoC devices to compute the Fast Fourier Transform (FFT) in real time. The Multi Channel FFT example design can be used in medical applications, sensor network applications, multi channel audio Spectrum analyzers, Smart Metering, and sensing applications (such as vibration analysis).This example design uses the Cortex-M3 processor in the SmartFusion MSS as a master and the FFT processor in the FPGA fabric as a slave. All three of the SmartFusion cSoC A2F500’s ADCs are used for data acquisition. The example design uses Microsemi’s CoreFFT IP and the advanced peripheral bus interface (CoreAPB3). A custom-made APB3 interface has been developed to connect CoreFFT with the MSS via CoreAPB3. The Cortex-M3 processor uses the PDMA controller in the MSS for the data transfer and thus helps to free up the Cortex-M3 processor instruction bandwidth.A basic understanding of the SmartFusion design flow is assumed. Refer to Using UART with SmartFusion - Microsemi Libero ® SoC and SoftConsole Flow Tutorial to understand the SmartFusion design flow.Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1Design Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2Design Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2Implementing Multi Channel FFT on EVAL KIT BOARD . . . . . . . . . . . . . . . . . . . . . . . . . 7Running the Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9Appendix A – Design Files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10SmartFusion cSoC: Multi-Channel FFT Co-Processor Using FPGA Fabric2Design OverviewThis design example demonstrates the capability of the SmartFusion cSoC device to compute the FFT for multiple data channels. The FFT computation is a complex task that utilizes extensive logic resources and computation time. In general, for N number of channels, N number of FFT IP’s are needed to be instantiated, which in turn utilize more logic resources on the FPGA. A way to avoid this limitation is to use the same FFT logic for multiple input channels.This design illustrates the implementation of a Multichannel FFT to process multiple data channels through a single FFT and store FFT points in a buffer. The FFT computes the input data read from each channel and stores the N-point result in the respective channel’s allocated buffer. The channel multiplexing is done once each channel buffer has been loaded with the FFT length.Computing frequency components for a real time data of six channels is described in this application note. For sampling the input signals the AFE is used and the complex FFT computation is implemented in the fabric of the SmartFusion cSoC device. The Cortex-M3 processor in the MSS of the SmartFusion cSoC handles the buffer management and channel muxing.Figure 1 depicts the block diagram of six channel FFT co-processor in FPGA fabric.Design DescriptionThe design uses CoreFFT for computing the FFT results. You can download the core generator for CoreFFT at /soc/portal/default.aspx?r=4&p=m=624,ev=60.The design example uses a 512-point and 16-bit FFT. A custom-made APB3 interface has been developed to connect CoreFFT IP with the MSS’s FIC. The CoreFFT output data is stored in a 512x32FIFO within the fabric. The FIFO status signals are given in Table 1 on page 3. The status signals indicate that FFT is ready to receive data and data is available in the output of FIFO. These status signals are mapped to the GPIOs in the MSS. The Cortex-M3 processor can read the GPIOs to handle flow control in the data transfer process from the MSS to CoreFFT.Figure 1 • Multi Channel FFT Block DiagramDesign Description3Figure 2 shows the block diagram of logic in the fabric with custom-made APB3 bus.The data valid signal (ifiD_valid) is generated in custom logic whenever the master needs to write data into the input buffer of the FFT to process through the APB3 interface. The FFT_IP_RDY signal indicates the status of the input buffer of the FFT. If the input buffer is full, the FFT_IP_RDY goes low. The master can read the FFT_IP_RDY signal to get the FFT input buffer status. The FFT generates the processed data with a data valid signal (ifoY_valid). The processed data is stored in the FIFO. When FIFO is not ready to receive output data, it can stop the data fetching from the FFT by pulling down the ifiRead_y signal. The status signal FFT_OP_RDY is used to indicate to the master that processed data is available in the FIFO. FFT_OP_RDY goes High whenever processed data is available in the FFT output buffer.The master can use AEMPTY_OUT or EMPTY_OUT to determine whether the FIFO is empty and all the processed data has been read. Refer to the CoreFFT Handbook for more details on architecture and interface signal descriptions.Three ADCs are configured to have two channels, each channel with 100 ksps sampling rate. The external memory is used for input and output buffers. For each channel, one input buffer having length double to the length of FFT i.e. 1024 words and one output buffer having length equal to the length of FFT i.e. 512 words are used. After each channel's input buffer has 512 points required for the full length of the FFT, each channel, one after the other, streams its points from the FIFO through the FFT. During the FFT computational period, the sampled data values of each channel are stored in the second half of the input buffer. Once the FFT computations for the First half of input buffer completes then the points in the second half of the input buffer will be streamed to FFT. This operation utilizes a ping-pong method. The Cortex-M3 processor is used for data management, that is, buffering the sampled points and data routing or muxing of these values to the FFT computation block. Sampling of the real time data is done by the ACE. The PDMA handles the data transfer between the external SRAM (eSRAM) buffers and CoreFFT logic in FPGA fabric.Figure 2 • CoreFFT with APB Slave InterfaceTable 1 • FIFO Status Signals with DescriptionsSignalDescription FFT_IP_RDYFFT is ready to receive the Input from the master processor FFT_OP_RDYProcessed data is ready in output buffer of FFT AEMPTY_OUTOutput FIFO is almost empty EMPTY_OUT Output FIFO is emptySmartFusion cSoC: Multi-Channel FFT Co-Processor Using FPGA Fabric4Figure 3 shows the implementation of multi channel FFT on the SmartFusion cSoC device.Hardware ImplementationThe MSS is configured with an FIC, clock conditioning circuit (CCC), GPIOs, EMC and a UART. The CCC generates 80 MHz clock, which acts as the clock source. The FIC is configured to use a master interface with an AMBA APB3 interface. Four GPIOs in the MSS are configured as inputs that are used to handle flow control in data transfer from MSS to FFT coprocessor. The EMC is configured for Region 0as Asynchronous RAM and port size as half word. The UART_0 is configured for printing the FFT values to the PC though a serial terminal emulation program.ADC0, ADC1, and ADC2 are configured with 12-bit resolution, two channels and the sampling rate is set to approximately 100 KHz. Figure 4 on page 5 shows the ACE configuration window.Figure 3 • Implementation of Multi Channel FFT on the SmartFusion cSoCDesign Description5The APB wrapper logic is implemented on the top of CoreFFT and connected to CoreAPB3. A FIFO of size 512*32 is used to connect to CoreFFT output.CoreAPB3 acts as a bridge between the MSS and the FFT coprocessor block. It provides an advanced microcontroller bus architecture (AMBA3) advanced peripheral bus (APB3) fabric supporting up to 16APB slaves. This design example uses one slave slot (Slot 0) to interface with the FFT coprocessor block and is configured with direct addressing mode. Refer to the CoreAPB3 Handbook for more details on CoreAPB3 IP .For more details on how to connect FPGA logic MSS, refer to the Connecting User Logic to the SmartFusion Microcontroller Subsystem application note.The logic in the FPGA fabric consumes 18 RAM blocks out of 24. We cannot use eSRAM blocks for implementing CoreFFT as the transactions between these SRAM blocks and FFT logic are very high and are time critical.Figure 5 on page 6 illustrates the multi channel FFT example design in the SmartDesign.Figure 4 • Configure ACESmartFusion cSoC: Multi-Channel FFT Co-Processor Using FPGA Fabric6Table 2 summarizes the logic resource utilization of the design on the A2F500M3F device.Software ImplementationThe Cortex-M3 processor continuously reads the values from ACE and stores the values into the input buffers. If the first 512 points are filled then the processor initiates the FFT process. In the FFT process,the input buffers are streamed one after other to the CoreFFT with the help of PDMA. Using another channel of PDMA the output of FFT is moved to the corresponding channel output buffers.During the FFT process the Cortex-M3 processor stores the sampled values into the second half of the input buffers. Once the FFT process completes the first half of input buffer, then the second half of the input buffer are streamed to CoreFFT.Figure 5 • SmartDesign Implementation of Multi Channel FFTTable 2 • Logic Utilization of the Design on A2F500M3FCoreFFTOther Logic in Fabric Total Ram Blocks14418 (75%)Tiles 78424718313 (72.1%)Implementing Multi Channel FFT on EVAL KIT BOARD7The CALL_FFT(int *) application programmable interface (API) initiates the PDMA to transfer input buffer data to the FFT in the fabric. Before initiating PDMA it checks for FFT whether or not it is ready to read the data. The CALL_FFT(int *) API also checks if the output FIFO is empty so that all the FFT out values have been already read. When the input buffer has points equal to the full length of FFT, then it will be called.The Read_FFT() API initiates the PDMA for reading the FFT output values from FIFO in fabric to the corresponding output buffer. After reading all the values it calls the CALL_FFT() API with the next channel buffer to compute the FFT for next channel. This is done for all channels. After completion of FFT computation for all channels, if the continuous variable is not defined, it will print the FFT output values on the serial terminal. When FFT_OP_READY interrupt occurs then this API will be called.The GPIO1_IRQHandler() interrupt service routine occurs on the positive edge of FFT_OP_READY signal. It calls Read_FFT() API. This interrupt mechanism is used to read the sample values continuously while computing the FFT.If continuous variable is defined, then the FFT is computed without any loss of data samples. If #define continuous line is commented then after every completion of FFT computation of all channels the FFT output is printed on serial terminal. The printed values are in the form of complex numbers.The ping-pong mechanism is used for input data buffer to store the samples continuously. For each channel the input buffer length is double of the full FFT length. While computing the FFT for the first half of the buffer, the new sample values are stored in the second half of the input buffer and while computing the FFT for second half of buffer, the new sample values are stored in first half of the input buffer.Customizing the Number of ChannelsYou can change the design depending on your requirement. Configure the ADC (Figure 4 on page 5)with the required number of channels and required sampling rate. In SoftConsole project change the parameter value NUM_CHANNELS according to the ADC configuration. Edit the main code for reading ADCs data into buffers according to ACE configuration.Throughput CalculationsThe actual time to get 512 samples with 100 ksps is 5.12 ms. Each channel is configured to 100 ksps, so for every 5.12 ms we will have 512 samples in the input buffers.The actual time taken to compute the FFT for each channel is the sum of time taken to transfer 512points to CoreFFT, FFT computation time, and time to read FFT output to the output buffer.•Total time for computing FFT = (time taken to receive 512 data + computational latency for 512points + time taken to store 512 data) = 512*5 + 23292 + 512*5 =28412 clks •Time to compute FFT for 6 channels = 28412*6 = 170472 clksTime to compute FFT for six channels is 2.1309 ms (If CLK is 80 MHz). It is less than half the sample rate of 5.12 ms.If only one channel is configured with maximum sampling rate (600 ksps) then time to get 512 samples with 600 ksps is 0.853 ms. Time to compute FFT for these 512 samples is 0.355 ms. If you configure three ADCs with maximum sampling rate (1800 ksps) then time to compute the FFT for these three channels will be 1.065 ms which is higher than the sampling time. In this there is a loss of some samples.The design works fine up to 1440 ksps.Implementing Multi Channel FFT on EVAL KIT BOARDTo implement the design on the SmartFusion Evaluation Kit Board the FFT must be 256 point and 8 bit because the A2F200 device has less RAM blocks and logic cells. The ADC channels must be selected for only ADC0 and ADC1. Figure 6 on page 8 shows the implementation of multi channel FFT on the SmartFusion cSoC (A2F200M3F) device.SmartFusion cSoC: Multi-Channel FFT Co-Processor Using FPGA Fabric8Table 3 summarizes the logic resource utilization of the design with 256 points 8-bit FFT on A2F200M3F device.Running the DesignProgram the SmartFusion Evaluation Kit Board or the SmartFusion Development Kit Board with the generated or provided *.stp file (refer to "Appendix A – Design Files" on page 10) using FlashPro and then power cycle the board.For computing continuous FFT values for the all six signals sampled through the ADCs, uncomment the line #define continuous in the main program. The FFT output values are stored in the rdata buffer. This buffer is updated for every computation of FFT.For printing the FFT values on serial terminal (HyperTerminal or PuTTy), comment the line #define continuous in the main program.Figure 6 • Implementation of Multi Channel FFT on the SmartFusion Evaluation Kit BoardTable 3 • Logic Utilization of the Design on A2F200M3F DeviceCoreFFTOther Logic in Fabric Total Ram Blocks718 (100%)Tiles 3201853286 (66%)Conclusion9Connect the analog inputs to the SmartFusion Kit Board with the information provided in Table 4.Invoke the SoftConsole IDE, by clicking on Write Application code under Develop Firmware in Libero ®System-on-Chip (SoC) project (refer to "Appendix A – Design Files") and launch the debugger. Start HyperTerminal or PuTTY with a baud rate of 57600, 8 data bits, 1 stop bit, no parity, and no flow control.If your PC does not have the HyperTerminal program, use any free serial terminal emulation program such as PuTTY or Tera Term. Refer to the Configuring Serial Terminal Emulation Programs Tutorial for configuring the HyperTerminal, Tera Term, or PuTTY .ConclusionThis application note describes the capability of the SmartFusion cSoC devices to compute the multi channel FFT. The Cortex-M3 processor, AFE, and FPGA fabric together gives a single chip solution for real time multi channel FFT system. This design example also shows the 6-channel data acquisition system.Table 4 • SettingsChannelEvaluation Kit Development Kit Channel 173 of J21 (signal header)ADC0 of JP4Channel 274 of J21 (signal header)ADC1 of JP4Channel 377 of J21 (signal header)77 of J21 (signal header)Channel 478 of J21 (signal header)78 of J21 (signal header)Channel 585 of J21 (signal header)Channel 686 of J21 (signal header)Figure 7 • FFT Output Data for 1 kHz Sinusoidal Signal on PUTTYSmartFusion cSoC: Multi-Channel FFT Co-Processor Using FPGA Fabric10Appendix A – Design FilesThe Design files are available for download on the Microsemi SoC Product Groups website:/soc/download/rsc/?f=A2F_AC381_DF.The design zip file consists of Libero SoC projects and programming file (*.stp) for A2F200 and A2F500.Refer to the Readme.txt file included in the design file for directory structure and description.51900249-0/02.12© 2012 Microsemi Corporation. All rights reserved. Microsemi and the Microsemi logo are trademarks of Microsemi Corporation. All other trademarks and service marks are the property of their respective owners.Microsemi Corporation (NASDAQ: MSCC) offers a comprehensive portfolio of semiconductor solutions for: aerospace, defense and security; enterprise and communications; and industrial and alternative energy markets. Products include high-performance, high-reliability analog and RF devices, mixed signal and RF integrated circuits, customizable SoCs, FPGAs, and complete subsystems. Microsemi is headquartered in Aliso Viejo, Calif. Learn more at .Microsemi Corporate HeadquartersOne Enterprise, Aliso Viejo CA 92656 USAWithin the USA: +1 (949) 380-6100Sales: +1 (949) 380-6136Fax: +1 (949) 215-4996。

脉冲多普勒雷达动目标检测的设计与实现

脉冲多普勒雷达动目标检测的设计与实现

摘要摘要动目标检测技术作为雷达数字信号处理中的关键环节之一,使得雷达具有在频域上分辩不同目标的能力。

随着雷达技术和微电子技术的不断发展,雷达信号处理器向着数字化、集成化、通用化方向发展。

专用集成电路(ASIC)相比FPGA和DSP来说有着更快的速度和更小的面积、功耗,对于导弹、无人机等载体有着重要的意义。

本论文的研究工作源自国家部委雷达信号处理器项目,主要完成了雷达信号处理系统中动目标检测处理器的ASIC设计与实现,动目标检测处理器位于脉冲压缩之后,包含多普勒滤波通道和零频抑制滤波通道,其中脉冲积累个数32~128可配置。

多普勒滤波通道用于对回波进行脉冲多普勒处理,在频域上区分不同目标,零频抑制滤波通道用于检测低速目标。

首先本文对动目标检测的原理做了研究,研究了快慢时间维采样、动目标显示、多普勒滤波器组和零频抑制滤波器的相关算法。

采用有限冲击响应(FIR)横向滤波器实现多普勒滤波器组,其加权系数可随不同的应用场景而设计,可以在不同频段设计相应频率的滤波器来抑制各种不同的杂波,但是直接使用FIR滤波器实现多普勒滤波器组硬件资源消耗大,针对这一问题,采用了10组滤波单元复用的方式实现可配置的滤波器组,减少了硬件资源的消耗,可以对脉冲压缩后脉冲占空比1/16以下的数据进行脉冲多普勒处理。

对于零频抑制滤波器,直接在时域使用共轭离散傅里叶变换(DFT)滤波器相减来实现,无法判断低速目标的运动方向,针对这一问题,本文首先对慢时间维采样数据进行FFT处理变换到频域,再在频域上进行滤波,可以得到低速目标运动速度的正负。

对于慢时间维采样数据的FFT,采用基2的方式完成了基于SDF结构的存储迭代FFT处理器设计,能够实现8~1024点FFT处理。

最终完成了动目标检测整体电路的设计。

随后采用Matlab建模搭建验证平台并产生相应的测试激励,将Modelsim仿真与Matlab对比,验证了不同配置情况下的动目标检测电路,并对仿真结果做了误差分析,相对误差在10-3数量级。

FFT算法及IIR、FIR滤波器的设计资料

FFT算法及IIR、FIR滤波器的设计资料

《DSP原理及其应用》实验设计报告实验题目:FFT算法及滤波器的设计摘要随着信息科学的迅猛发展,数据采集与处理是计算机应用的一门关键技术,它主要研究信息数据的采集、存储和处理。

而数字信号处理器(DSP)芯片的出现为实现数字信号处理算法提供了可能。

数字信号处理器(DSP)以其特有的硬件体系结构和指令体系成为快速精确实现数字信号处理的首选工具。

DSP芯片采用了哈佛结构,以其强大的数据处理功能在通信和信号处理等领域得到了广泛应用,并成为研究的热点。

本文主要研究基于TI的DSP芯片TMS320c54x的FFT算法、FIR滤波器和IIR滤波器的实现。

首先大概介绍了DSP和TMS320c54x的结构和特点并详细分析了本系统的FFT变换和滤波器的实现方法。

关键词:DSP、TMS320c54x、FFT、FIR、IIRAbstractWith the rapid development of information science, data acquisition and processing is a key technology of computer applications, the main research of it is collection, storage and processing of information data. The emergence of the digital signal processor (DSP) chip offers the potential for the realization of the digital signal processing algorithm. Digital signal processor (DSP), with its unique hardware system structure and instruction system become the first tool of quickly and accurately realize the digital signal processing.DSP chip adopted harvard structure, with its powerful data processing functions in the communication and signal processing, and other fields has been widely applied, and become the research hot spot.This paper mainly studies the FFT algorithm based on TMS320c54x DSP chip of TI, the realization of FIR filter and IIR filter. First introduced the DSP and TMS320c54x briefly, then analyzed in detail the structure and characteristics of the system of the realization of FFT transform and filter method.Keyword: DSP、TMS320c54x、FFT、FIR、IIR1.绪论1.1课题研究的目的和意义数字信号处理器(DSP)已经发展了多20多年,最初仅在信号处理领域内应用,近年来随着半导体技术的发展,其高速运算能力使很多复杂的控制算法和功能得以实现,同时将实时处理能力和控制器的外设功能集于一身,在控制领域内也得到很好的应用。

PowerPC和DSP对比

PowerPC和DSP对比

PowerPC和DSP对比一、主要性能参数对比ASDP tigersharp主要参数Word 资料Word 资料主要DSP的浮点性能对比:Speed Scores for floating-point packaged processors BDTImark2000(BDTI认证结果) Word 资料(BDTI主要是针对DSP的benchmark,没有MPC7410和Powerpc的数据)一些算法,像FFT,可以充分利用7410的矢量数学运算。

1024点,浮点复数FFT可以在27us内完成,相比之下,C6701需要108us。

其他算法,像无线应用中的turbo解码器,VLIW结构处理的更有效率。

很明显,具有AltiVec核的PowerPC G4(74xx)具有较高的核时钟速率与性能。

P O W e r P C 的核时钟速率几乎是目前T i g e r s H A R C的3.3倍(不久更快版本的TigerSHARC将发布)。

AltiVec核每个周期执行单条指令,每128位向量包含4个独立的32位数据单元,这就是众所周知的sIM-D(单指令多数据)结构。

当执行一次乘加(MAC)矢量运算时,达到峰值处理能力,每周期可完成8次浮点操作。

对于1 GHz的MPC7455,峰值处理能力可达8000M 次/s浮点运算。

AltiVec每周期能执行8次整数或定点操作,峰值整数运算能力为8000MOPS(百万次操作/s)。

相反,TigerSHARC有两个独立的32位处理器核,或称MIMD(多指令多数据)结构。

每个计算单元每周期能执行一次乘法以及和差分运算,对于300 MHz ADSPTSl0lS每周期完成6次浮点运算或1800MFLOPS峰值运算能力。

当执行16位整数运算时,TigerSHARC 可以利用它的超标量体系结构,分离两个独立3 2位计算单元成2个单独的16位S1MD单元。

这样每个操作在两个数据单元,每个周期总共12次操作。

ASIC后端设计中的时钟树综合

ASIC后端设计中的时钟树综合

ASIC后端设计中的时钟树综合周广;何明华【摘要】Clock tree synthesis is an important part in integrated circuit design nowadays. Therefore, the method of timing-driven placement and limitation of placement density are adopted to achieve good layout effect during the layout design of FFT processor chip. The optimal method of clock tree automatic synthesis and manually modification are employed to reduce clock skew. The strategy of specifying clock tree constraint file, chosing the buffer and modifying clock tree is put forward.The clock tree synthesis of FFT processor chip is completed and the design meets the requirements of design.%时钟树综合是当今集成电路设计中的重要环节,因此在FFT处理器芯片的版图设计过程中,为了达到良好的布局效果,采用时序驱动布局,同时限制了布局密度;为了使时钟偏移尽可能少,采用了时钟树自动综合和手动修改相结合的优化方法,并提出了关于时钟树约束文件的设置、buffer的选型及手动修改时钟树的策略,最终完成了FFT处理器芯片的时钟树综合并满足了设计要求.【期刊名称】《现代电子技术》【年(卷),期】2011(034)008【总页数】3页(P137-139)【关键词】FFT处理器芯片;布局布线;时钟树综合;时钟偏移【作者】周广;何明华【作者单位】福州大学物理与信息工程学院,福建,福州,350002;福州大学物理与信息工程学院,福建,福州,350002【正文语种】中文【中图分类】TN492-340 引言在大规模高性能的ASIC设计中,对时钟偏移(Clock Skew)的要求越来越严格,时钟偏移是限制系统时钟频率的主要因素。

LabVolt系列雷达处理器 显示器(基本雷达培训系统的附加设备)数据手册说明书

LabVolt系列雷达处理器 显示器(基本雷达培训系统的附加设备)数据手册说明书

LabVolt Series DatasheetRadar Processor/Display (add-on to the Basic Radar Training System)8112498 (8097-20)* The product images shown in this document are for illustration purposes; actual products may vary. Please refer to the Specifications section of each product/item for all details. Festo Didactic reserves the right to change product images and specifications at any time without notice.Festo Didactic en12/2023Radar Processor/Display (add-on to the Basic Radar Training System), LabVolt SeriesTable of ContentsGeneral Description_________________________________________________________________________________3 List of Equipment___________________________________________________________________________________8 List of Manuals____________________________________________________________________________________8 Table of Contents of the Manual(s)____________________________________________________________________8 Additional Equipment Required to Perform the Exercises (Purchased separately) _____________________________9 System Specifications_______________________________________________________________________________9 Equipment Description_____________________________________________________________________________10 Optional Equipment Description_____________________________________________________________________14Radar Processor/Display (add-on to the Basic Radar Training System), LabVolt SeriesGeneral DescriptionThe Radar Processor/Display is used in conjunction with the Basic Radar Training System to form a complete and modern pulse radar system. The Radar Processor/Display adds the following elements to the Basic Radar Training System: radar echo signal processing functions, PPI display functions, on-screen block diagrams of the complete radar and radar processor/display subsystem, and computer-based (i.e., on-screen) instruments (oscilloscope and data monitoring system). Two major types of radar echo signal processing function areavailable: Moving Target Indication (MTI) and Moving Target Detection (MTD). The Radar Processor/Display also provides computer-controlled generation of clutter and interference to allow study of the MTI processingfunction. The following types of clutter and interference can be generated: sea clutter, rain clutter, second-trace echo, noise, and pulse interference.The Radar Processor/Display consists of a reconfigurable training module (RTM), a power supply for the RTM, three interface modules, a set of accessories including the Radar Training System Software, two comprehensive student manuals, and a user guide. A Windows ® based host computer (to be purchased separately) is requiredwith the RTM. The Festo Radar Host Computer is recommended.Example of a PPI display obtained with the Radar Processor/Display.The RTM is the cornerstone of theRadar Processor/Display. This module, which uses state-of-the-art digitalsignal processor (DSP) technology, can be programmed to act as either an analog pulse radar (i.e., a pulse radar with MTI processing) or a digital pulse radar (i.e., a pulse radar using MTD, correlation and interpolation, and surveillance processing). Interface modules that students install in the RTM allow connection of the various signals coming from the Basic Radar Training System, as shown in Figure 1. The RTM can also be programmed to act as a tracking radar when used with the Radar Tracking Training System,Model 8096-3.Radar Processor/Display (add-on to the Basic Radar Training System), LabVolt Series•••••••••Figure 1. Simplified connection diagram of the Basic Radar Training System and Radar Processor/Display.The RTM processes the signals from the Basic Radar Training System to detect targets, and sends data to the radar host computer via a high-speed data link (Ethernet link with TCP/IP protocol). The RTM can also generate clutter and interference which are added to the I- and Q-channel echo signals from the radar receiver, before signal processing takes place. The radar host computer, which runs the LVRTS software, uses the dataproduced by the RTM to display the detected targets on a PPI display. TheLVRTS software is a Windows ®-basedapplication used to download programs into the DSP memory of theRTM, to select the type of radar which is implemented (see Figure 2). It also has an intuitive user interface to:Select the radar processing functions and adjust other parameters of the radar, such as the video gain, detection threshold, etc. (see Figure 3)Control the radar display functions such as the PPI display mode selection, Variable Range Marker (VRM), Electronic Bearing Line (EBL), etc. (see Figure 4)Display diagrams that show how to connect the equipment (see Figure 5).Display the functional block diagrams of the complete radar and radar processor/display subsystem (see Figure 6).Connect virtual probes to test points in the aforementioned block diagrams to observe real signals using the built-in oscilloscope (see Figure 7).Use the Data Monitor to observe and analyze the signal processing sequence involved in Moving Target Detection (see Figure 8).Insert faults in the system (password-protected feature) for troubleshooting purposes (see Figure 9).Set the parameters that control the generation of clutter and interference (see Figure 10).Obtain on-line help screens (see Figure 11).Figure 2. On-screen selection of the type of radar which is implemented.Radar Processor/Display (add-on to the Basic Radar Training System), LabVolt SeriesFigure 3. Computer-based control of the radar processing functions and operating parameters.Figure 4. Computer-based control of the radar display functions.Radar Processor/Display (add-on to the Basic Radar Training System), LabVolt SeriesFigure 5. Window showing the interconnections to the RTM.Figure 6. On-screen block diagram of the Moving Target Indicator (MTI)processor.Figure 7. Real signals can be observed on the built-in oscilloscope byconnecting virtual probes to test points in the on-screen block diagrams.Radar Processor/Display (add-on to the Basic Radar Training System), LabVolt SeriesFigure 8. The Data Monitor is a powerful tool designed to study the various stages (FFT Doppler filtering, thresholding, alarm generation) of Moving Target Detection (MTD).Figure 9. Faults window in the LVRTS software.Figure 10. Computer-based control of clutter and interference generation.Radar Processor/Display (add-on to the Basic Radar Training System), LabVolt Series••••••••List of EquipmentQty Description Model number1Analog MTI Processing (Student Manual) ___________________________________________ 580412 (38543-00)1Radar Processor/Display (User Guide) _____________________________________________ 580414 (38543-E0)1Digital MTD Processing (Student Manual) ___________________________________________ 580418 (38544-00)1RTM Power Supply _____________________________________________________________ 8112514 (9408-2X)1Reconfigurable Training Module (RTM) _____________________________________________ 8094635 (9431-30)1Analog/Digital Signal Combiner ___________________________________________________ 8112776 (9630-10)1Data Acquisition Interface _______________________________________________________ 8112777 (9631-10)1Radar Analog/Digital Output Interface _____________________________________________ 8093433 (9635-00)1Accessories for the Radar Processor/Display ________________________________________ 8112516 (9688-A0)List of ManualsDescriptionManual numberAnalog MTI Processing (Workbook) ___________________________________________________580412 (38543-00)Radar Processor/Display (User Guide) _________________________________________________580414 (38543-E0)Digital MTD Processing (Workbook) __________________________________________________580418 (38544-00)Radar Training System (User Guide) ___________________________________________________________8112390Table of Contents of the Manual(s)Analog MTI Processing (Workbook) (580412 (38543-00))1-1 Familiarization with the Analog Pulse Radar 1-2 The PPI Display 2-1 Phase-Processing MTI 2-2 Vector-Processing MTI 2-3 Staggered PRF 2-4 MTI Limitations 3-1 Threshold Detection3-2 Pulse IntegrationFigure 11. On-line help screens are available through a few clicks of the mouse button.Radar Processor/Display (add-on to the Basic Radar Training System), LabVolt Series•••••••••••••••3-3 Sensitivity Time Control3-4 Instantaneous Automatic Gain Control 3-5 The Log-FTC Receiver3-6 Constant False-Alarm Rate4-1 Troubleshooting the MTI Processor4-2 Troubleshooting the Display Processor 4-3 Troubleshooting an MTI Radar SystemDigital MTD Processing (Workbook) (580418 (38544-00))1-1 Familiarization with the Digital Pulse Radar1-2 The PPI Display2-1 Cell Mapping2-2 Fast Fourier Transform (FFT) Processing2-3 Constant False-Alarm Rate (CFAR)3-1 Correlation and Interpolation (CI) Processing3-2 Surveillance (Track-While-Scan) Processing4-1 Troubleshooting the Digital MTD/PPI ProcessorAdditional Equipment Required to Perform the Exercises (Purchased separately)Qty Description Model number1Function Generator 5 MHz / Frequency Counter ______________________________________ 8125246 (9409-00) 1Radar Host Computer ___________________________________________________________ 587465 (9695-00)1System SpecificationsParameter ValueMTI Processor (Analog)Functions Functions Sensitivity Time Control (STC), moving target cancellation, logarithmic amplification, Fast Time Constant (FTC), Constant False-Alarm Rate (CFAR), Instantaneous Automatic Gain Control (IAGC), antilog conversion, 4- and 8-pulse video integration (non-coherent)I- and Q-Channel Input Voltage Range-1.5 to +1.5 VVideo Output Voltage Range-10 to +10 VOn-Screen Test Points15Faults12Display Processor (Analog)PPI Outputs X and Y, Voltage Range-8 to +8 VPPI Output Z TTLAzimuth Input TTLOn-Screen Test Points8Faults4MTD Processor (Digital)Functions Moving Target Detection (MTD), Correlation and Interpolation, Surveillance Coherent Processing Intervals (CPI)2, 4/3 ratio, synchronized in azimuthTarget Tracking Capability up to 8 targets simultaneouslyI- and Q-Channel Input Voltage Range-1.5 to +1.5 VPPI Outputs X and Y, Voltage Range-8 to +8 VPPI Output Z TTLAzimuth Input TTLOn-Screen Test Points15Faults13PPI Display (Digital)Number of Sectors60Sector Width6°1 Comes with the software pre-installed. Can be replaced by a PC running Windows with a Ethernet port and2 screens.Radar Processor/Display (add-on to the Basic Radar Training System), LabVolt SeriesParameter ValueNumber of Range Segments16, 32, and 64 on 1.8-m (5.9-ft), 3.6-m (11.8-ft), and 7.2-m (23.6-ft) ranges, respectivelyRange Segment Length11.25 cm (4.4 in)Number of Cells960, 1920, and 3840 on 1.8-m (5.9-ft), 3.6-m (11.8-ft), and 7.2-m (23.6-ft) range, respectively Equipment DescriptionRTM Power Supply8112514 (9408-2X)The RTM Power Supply is the power source for theReconfigurable Training Module (RTM) used in the radar trainingsystems. It has a multi-pin connector output, located on theback panel, that provide regulated dc voltages. Hiccup modeprotection protects the outputs of the RTM Power Supply againstshort-circuits.Front ViewRear ViewSpecificationsParameter ValuePower RequirementsService Installation Standard single-phase ac outletVoltage100-240 V acCurrent 2.5 AFrequency50/60 HzRating of DC Power Outputs+5 V 2 A+3.3 V 2.5 A+12 V - A 1.25 A+12 V - B 1.25 A-12 V0.85 A-5 V 1 APhysical CharacteristicsDimensions (H x W x D)165 x 250 x 250 mm (6.5 x 9.8 x 9.8 in)Net Weight 5.6 kg (12.2 lb)Reconfigurable Training Module (RTM)8094635 (9431-30)The Reconfigurable Training Module (RTM) consists mainly of apowerful digital signal processor (DSP), with three slots on themodule front panel for installing interface modules. An Ethernetport (RJ-45) connector, located on the back panel, allowsconnection of the RTM to the host computer. The functionality ofthe training system is determined by downloading a programinto the DSP memory using the host computer that runs thesoftware. Electrical power is supplied to the RTM by the PowerSupply, Model 9408, through a multipin cable that connects to the back panel.SpecificationsParameter ValueInterface Card SlotsAnalog/Digital2Digital1Data LinkData Link to Host Computer10 Mb/s (Ethernet) or 100 Mb/s (Fast Ethernet), TCP/IP ProtocolPhysical CharacteristicsDimensions (H x W x D)215 x 430 x 280 mm (8.5 x 16.9 x 11.0 in)Net Weight9.8 kg (21.6 lb)Analog/Digital Signal Combiner8112776 (9630-10)The Analog/Digital Signal Combiner is a compact moduledesigned to be installed into one of the slots on the RTM of theRadar Processor/Display. This module converts the clutter andinterference generated by the DSP of the RTM to analog format,and adds it to the I- and Q-channel echo signals coming from theRadar Receiver.The Analog/Digital Signal Combiner has two BNC-connectorinputs to receive the I- and Q-channel echo signals. It also hasfour BNC-connector outputs. Two outputs provide the clutter andinterference signals added to the I- and Q-channel echo signals.The other two outputs provide the I- and Q-channel, perturbedecho signals. All these inputs and outputs are protected frommisconnections within the system. Test points are available onthe module's front panel to observe all these signals using a conventional oscilloscope.DC power is automatically supplied to the Analog/Digital Signal Combiner when it is installed into the RTM. SpecificationsParameter ValueAnalog Inputs (2)Voltage Range-10 to +10 VImpedance10 kΩAnalog Outputs 3 and 4Voltage Range-1 to +1 VImpedance600 ΩAnalog Outputs 5 and 6Voltage Range-11 to +11 VImpedance600 ΩTests PointsTest Points6Physical CharacteristicsDimensions (H x W x D)114 x 110 x 209 mm (4.5 x 4.3 x 8.2 in)Net Weight0.6 kg (1.4 lb)Data Acquisition Interface8112777 (9631-10)The Data Acquisition Interface is a compact module designed tobe installed into one of the slots on the RTM of the RadarProcessor/Display. This module receives the I- and Q-channelecho signals of the radar, perturbed or not, and converts them todigital format. It also receives the PRF and synchronizationsignals as well as azimuth information from the RadarSynchronizer / Antenna Controller. All these signals are thenrouted to the RTM for digital signal processing.The Data Acquisition Interface has two BNC-connector analoginputs to receive the I- and Q-channel echo signals. It also hastwo BNC-connector digital inputs where the PRF andsynchronization signals are injected. A DB15 connector isprovided as a digital input for the azimuth information. All theseinputs are protected from misconnections within the system.Test points are available on the module's front panel to observe the input signals using a conventional oscilloscope.DC power is automatically supplied to the Data Acquisition Interface when it is installed into the RTM. SpecificationsParameter ValueAnalog Inputs (2)Voltage Range-1.5 to +1.5 VImpedance10 kΩDigital Inputs (2)Parallel Digital Input TTL, 10 bitsTest Points4Physical CharacteristicsDimensions (H x W x D)114 x 110 x 209 mm (4.5 x 4.3 x 8.2 in)Net Weight0.6 kg (1.4 lb)Radar Analog/Digital Output Interface8093433 (9635-00)The Analog/Digital Output Interface is a compact moduledesigned to be installed into one of the slots on the RTM of theRadar Processor/Display. This module provides analog anddigital output signals generated by the RTM. The nature of thesignals generated depends on the type of radar processing thatthe RTM performs.The Analog/Digital Output Interface has four BNC-connectoranalog outputs and four BNC-connector digital outputs. All theseoutputs are protected from misconnections within the system.Test points are available on the module's front panel to observethe output signals using a conventional oscilloscope.DC power is automatically supplied to the Analog/Digital OutputInterface when it is installed into the RTM.SpecificationsParameter ValueAnalog Outputs (4)Voltage Range-10 to +10 VImpedance600 ΩDigital Outputs (4)TTLTest Points8Physical CharacteristicsDimensions (H x W x D)114 x 110 x 209 mm (4.5 x 4.3 x 8.2 in)Net Weight0.6 kg (1.4 lb)Accessories for the Radar Processor/Display8112516 (9688-A0)The Accessories for the Radar Processor/Display contains aDB15 cable, a USB port cable, an RJ-45 connector crossovercable, an Ethernet adapter (network card) to be installed in theradar host computer, two semi-circular targets, a multiple targetholder to be used with the Target Positioning System and theLVRTS software CD-ROM.Optional Equipment DescriptionFunction Generator 5 MHz / Frequency Counter (Optional)8125246 (9409-00)Direct digital synthesized arbitrary function generator with anembedded frequency counter, perfect to complementtelecommunication or radar training systems.Radar Host Computer (Optional)587465 (9695-00)The Radar Host Computer is a Windows® based computer withthe LVRTS software installed, two monitors, and a dual-outputdisplay adapter (video card) compatible with Microsoft DirectX®version 9 or later.The Radar Host Computer is used to run the LVRTS software andis linked to the RTM of the Radar Processor/Display through ahigh-speed data link (Ethernet link with TCP/IP protocol). Itprovides the radar's PPI display and allows control of the radarprocessing and display functions, and much more as describedin the General Description of the Radar Processor/Display.The Radar Host Computer is not included in the Radar Processor/Display. It must be purchased separately or replaced with an equivalent personal computer. The Windows® 7 or later operating system is required to run the LVRTS software.Reflecting the commitment of Festo Didactic to high quality standards in product, design, development, production, installation, and service, our manufacturing and distribution facility has received the ISO 9001 certification.Festo Didactic reserves the right to make product improvements at any time and without notice and is not responsible for typographical errors. Festo Didactic recognizes all product names used herein as trademarks or registered trademarks of their respective holders. © Festo Didactic Inc. 2023. All rights reserved.Festo Didactic SERechbergstrasse 373770 DenkendorfGermanyP. +49(0)711/3467-0F. +49(0)711/347-54-88500Festo Didactic Inc.607 Industrial Way WestEatontown, NJ 07724United StatesP. +1-732-938-2000F. +1-732-774-8573Festo Didactic Ltée/Ltd675 rue du CarboneQuébec QC G2N 2K7CanadaP. +1-418-849-1000F. +1-418-849-1666。

基于DC结构的基-2的64点FFT处理器的设计

基于DC结构的基-2的64点FFT处理器的设计

基于DC 结构的基-2的64点FFT 处理器的设计(于春云 200810123021)摘要: 针对当前数字信号处理领域对快速傅里叶变换应用的广泛需求, 在对算法原理分析的基础上, 给出了64 点基—2按时间抽选FFT 处理器的实现方案; 并综合Xilinx x c3s1500系列芯片, 通过Mode lsim SE 6. 0对程序进行仿真。

实验结果表明, 该处理器功能实现正确, 并且具有较高的运算速度和精度。

关键词:快速傅里叶变换; 基—2;蝶形运算0 引言DFT 作为DSP 领域中时域和频域转换的基本运算,存在运算量太大的缺点,导致其应用受到局限。

DFT 快速算法FFT 的提出,简化了DFT 的运算过程,使其在实时信号处理领域中得到广泛应用。

FFT 实现的方法包括软件实现和硬件实现两种。

采用软件实现FFT 的方法存在计算慢,实现过程复杂等缺点,所以目前比较流行的方式是采用硬件实现FFT 。

硬件实现的具体方法可以分为ASIC 方法、FPGA 方法、 DSP 方法和通用处理机方法等。

FPGA 是20世纪80年代中期出现的一种新的电子设计自动化技术,具有集成度高,逻辑实现能力强,设计灵活等优势。

在FPGA 上实现数字信号处理,即用纯数字逻辑进行DSP 模块设计,为高速数字信号处理算法提供了实现途径。

在此,采用FPGA 方法设计64点FFT 处理器。

1 FFT 算法基本原理设x( n)为N 点有限长序列, 其DFT 为:(1)其中。

先设序列点数为N = 2L, L 为整数, 如不满足此条件可以加上若干零值点使之达到这一要求。

将N = 2L的序列x ( n) ( n= 0, 1, …, N-1)先按n 的奇偶分成两组,再利用系数的可约性和周期性,可以得到:X(2)64点FFT 运算的数据流图2 FFT 运算器设计2.1 系统的整体结构对于一个完整的FFT 运算单元而言,应该包括以下几个组成部分:全局控制单元:包括控制器和地址产生单元,用于调控整个FFT运算系统,生成蝶形运算单元以及其他子单元所需的地址,控制各子单元时序,保证其正常有序地工作;蝶形运算器单元:由蝶形运算器和旋转因子存储单元(ROM)组成,负责将送入的输入数据进行蝶形运算,是FFT运算器的核心单元;存储寄存器单元:采用两个RAM乒乓通信,通过通信接口单元接受总线控制信号,负责存储输入数据、中间数据和运算所得最终结果。

基于STM32的全相位FFT相位差测量系统

基于STM32的全相位FFT相位差测量系统

理后做64个点的FFr,实现了信号相位差的测量。测试结果表明有效分辨精度为1度。
关键词:相位测量;STM32;全相位FFr;仿真测试
中图分类号:Tlr23
文献标识码:A 文章编号:1005-9490(2010)03-0357-05
在各种军用和民用工程领域,存在大量的测量 信号相位问题。例如在激光测距中,只有精确测出 发出和返回的激光调制波的相位值才可实现精确测 距;在GPS导航中,只有测出载波相位值,才可实现 精确目标定位等。
pl:而而 屯而五屯

p2:
五 黾毛五毛
I p3
x2 x,xl x2
J兰主区间求和
P:3x2 2x3+xo 2x.十_
图2全相位数据处理流程图

xo xl X2 X3■
上上对应项相j
WN





比阱
P 【3x;3x,帆2x.帆
图3全相位数据处理等效框图
则当Ⅳ=3时,WN=[1 1 1].[1 l 1]=[1 2 3 2 1] 即为图2的三角加权窗。双窗时/=b=熙(砜为 任何对称窗,如汉宁窗等)。
3试验方法与结果
原本系统通过AD采样,将采样结果保存到数 组中,然后通过算法计算相位差,由于较难获得已知 相位差的输入信号,所以这里才用一种折中的方法, 即AD采样由计算机完成,采样的结果以数组的方 式保存到STM32MCU中作为AD实际的采样结果, 由此数据来测试系统的误差。
在MATLAB中采样信号为: 戈=2·cos(2·面·[一(Ⅳ一1):(Ⅳ一1)]·厶ZC+ alp/180·1r)+0.1·cos(2·订·[一(J7\r一1):(Ⅳ一1)]· 五·1.1组+alp/180·订)+3; 上式中2·COS(2·霄·[一(N一1):(Ⅳ一1)]. 工组+alp/180·叮r)为输入信号采样。 0.1·cos(2·订·[一(Ⅳ一1):(N一1)]呒·1.1/f.+ alp/180·1T)+3为干扰信号采样。考虑到实际情况, 加入此于扰信号。 各变量含义如下: 2N一1:采样个数,五:输入频率,工:采样频率, alp:相位差 考虑到实际12bitAD采样的分辨率为:3.3/ 212=0.0008056640625,至少3位有效数字。 所以最终采样值sample=floor(菇·100),即取2 位有效数字,并放大100倍. 取N=64,fo=1 000Z=8 000,改变alp的值,产生 一系列的sample. 例如alp=149.5时sample采样值为 跗mple={106,206,359,477,490,392,241,125,112,208, 357,471,485,391,245,131,115,206,351,465,483,395,
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64 Points FFT Processor目录目录 (1)一算法分析 (2)二硬件结构设计 (4)2.1 系统结构设计 (4)2.2 基2蝶形单元的设计 (5)2.2.1 复数乘法器的设计 (5)2.2.2 旋转因子的存取 (5)2.3 数据转接器的设计 (6)2.4 延时单元设计 (7)2.5 控制单元设计 (7)2.6 系统的数据流图 (7)三功能验证与仿真综合 (8)3.1 系统模块 (8)3.2 功能验证 (9)3.3 综合结果 (9)四总结 (9)附录: (10)一算法分析离散傅立叶变换(DFT )由一组信号的采样值确定信号的频谱分量,使数字信号处理也可以在频域上采用数字运算进行,作为一种数学工具来描述离散信号时域和频域之间的转换关系。

一维DFT 中,长为N 的序列()x n 的DFT 定义为:∑∑-=--===1/21)()()(N n knN Nnk j N n W n x en x k X π 10-≤≤N k (1) FFT 的实质是将较长序列的DFT 运算逐次分解为较短序列的DFT 运算, 这些短序列的DFT 重新组合成原序列的DFT ,而总的运算次数比直接的DFT 少的多,从而达到提高运算速度的目的。

在直接计算一个N 点DFT 的过程中,总共需要N 2次复数乘法和N 2-N 次复数加法。

正是基于将输入或者输出进行重新分组的思想,FFT中所需要进行的复数乘法运算的次数为NN2log 2次,运算强度的大大减小,FFT 算法的引进,使得当点数变得很大时,傅立叶变换仍然能够用硬件的方式来实现。

FFT 的算法多种多样,按数据组合方式不同一般分为按时间抽取盒按频率抽取,按数据抽取方式的不同又可以分为基2,基4,基8等。

在本设计中,采用按频率抽取的基2算法。

在DFT 的定义式(1)中,旋转因子n N W kn N W 具有周期性和对称性,可以利用此来减少DFT 运算次数。

按频率抽取的Cooley-Tukey 快速算法就是利用旋转因子的特殊性质在频域内将序列逐次分解为一组子序列进行运算。

旋转因子具有如下的性质: ① 旋转因子以N 为周期:)()(N k n N n N k N kn N W W W ++==② 旋转因子具有对称性:knN kn N kn N N kn NW W W W -+=-=*2)(,③ 旋转因子具有可约性:mkn m N kn N knm mN kn N W W W W //,-== (N/M 为正整数)将式(1)采用基2的方法,在频域上按奇偶抽取可以分解为:(/2)1/20(2)[()()]2N kn N n N X k x n x n W -==++∑0,1,2,...,12N k =- (/2)1/20(21){[()()]}2N n knN N n N X k x n x n W W -=+=-+∑0,1,2,...,12N k =- (2)定义N/2点的序列1()g n 和2()g n 为1()()()2N g n x n x n =++2()[()()]2nNN g n x n x n W =-+ 0,1,2,...,12N n =- (3) 则有(/2)11/20(2)()N knN n X k g n W -==∑0,1,2,...,12Nk =- (/2)12/20(21)()N knN n X k g n W -=+=∑0,1,2,...,12Nk =- (4) 通过抽取N/2点DFT (2)X k 和(21)X k +,可以重复上述计算过程,整个过程包含2log N 级抽取,其中每一级包含N/2个基2的蝶形运算单元。

以8点为例说明基2的按频率抽取过程中信号的流程。

其中图1为分解的整个流程图,图2为每一级的蝶形运算单元。

由图1可以看到,输入数据()x n 按自然顺序出现,但输出数据是按倒序出现的。

图1 8点按频率抽取算法信号流程图-1nN W a bA=a+bB=(a-b)nNW图2 按频率抽取的基2的蝶形运算单元二硬件结构设计2.1 系统结构设计FFT 处理器按结构可以划分为单内存、双内存、流水线以及并行结构。

单内存结构,只含有一个内存,该内存同时存储输入和输出数据。

双内存结构含有两个内存,分别存储蝶形运算单元的输入和输出数据,当每一级的蝶形运算完成以后,两个内存的功能则进行交换。

这两种结构占用的硬件资源较少,但数据吞吐量低,因此要达到相同的性能指标则会需要较高的时钟频率。

为了提高FFT 处理器的运算速度,采用流水线结构和并行结构。

这两种结构分别通过串行和并行输入来增加运算处理单元,从而可以极大地提高速度。

FFT 处理器流水线结构有两种较为成熟的流水线架构:延迟连接结构(DC)和单一路径延迟反馈结构(SDF)。

其中延迟连接结构包括多路径延迟连接架构(Math Path Delay Commutator,MDC)和单一路径延迟连接架构(Signal Path Delay Commutator,SDC)。

本设计中采用多路径延迟连接结构,系统结构图如图3所示。

图3 系统结构图其工作原理为:在RAM块中保存两帧数据,依次输入到第一级的运算单元。

为了保证数据的并行性,RAM之后的运算单元的时钟频率为数据输入时钟频率(即系统时钟频率)的一半。

在系统开始工作的前64个时钟内,运算单元取第二帧的数据,因此在前64个时钟是没有数据输入到运算单元。

取完第二帧的数据,第一帧的数据输入完,系统开始进入正常的运算阶段,由图3可以看出,所有运算单元经过了62个时钟周期的延时后开始流水输出计算结果。

选用此结构的优点是控制简单,经过一帧数据的等待之后可以实现数据的连续处理,运算器的利用率可以达到100%。

缺点是相比基4等高基数的结构使用的存储结构偏多。

在最后输出是倒序输出,还需要一个数据输出单元进行处理。

由算法分析可以得到,到第五级时,乘法运算的旋转因子为(-j),通过手动计算可知,可以采用条件选择的反相器实现,因此本系统结构包含4个复数乘法器和6个蝶形运算单元。

2.2 基2蝶形单元的设计基2按频率抽取(DIF)的蝶形运算单元是由一个加法器、一个减法器和一个实例化的复数乘法器实现的。

其结构图如图4所示。

图4 基2蝶形运算单元结构图2.2.1 复数乘法器的设计两个复数的乘法一般包括4次实数乘法和2次加/减运算实现。

通过表达式的变换可以只用3次实数乘法和3次加/减法运算构造复数乘法器来实现的,因为有一个操作数可以预先计算。

其运算过程如下。

(a+jb)(c+jd)=ac-bd+j(bc+ad)其中ac-bd=ac-ad+ad-bd=(c-d)a+(a-b)d bc+ad=bc+bd-bd+ad=(c+d)b+(a-b)d其实现框图如图5所示,乘法器采用Booth 编码乘法器。

减法器减法器加法器a c 乘法器乘法器加法器加法器乘法器RI图5 复数乘法器实现框图2.2.2 旋转因子的存取在每一级的运算中,输入数据的后面一个数据需要与旋转因子相乘。

采用存储单元将旋转因子的值预先保存,待使用时,通过地址发生器取出所需的旋转因子。

按一分析的算法可以知道,每一级所需的旋转因子为N/2m 个,m=1,2,3,4。

首先分析FFT算法,计算出每一级对应的旋转因子的值并进行量化为一定精度的二级制数,将量化后的旋转因子计算出来,分成实部和虚部保存。

本设计中采用定点的十位二进制补码表示。

保存的数据中利用旋转因子的周期性和对称性,可以只要保存8个点的数据就可以映射出所需的所有点的数据。

2.3数据转接器的设计在图3所示的系统结构中包含5个数据转接单元(SW),每个转接器的功能是将前一级计算的结果重新排序,得到的下一级蝶形运算的正确序列数据。

图3中的转接器的顺序依次为switch16,switch8,switch4,switch2,switch1。

每个数据转接器的数据流图如图6所示。

各个图的上面为输入数据流,下面为输出数据流。

(a) switch16的数据流图(b) switch8的数据流图(c) switch4的数据流图(d) switch2的数据流图(e) switch1的数据流图图6各级数据转接单元的数据流图2.4 延时单元设计图3中每一级的延时器分别采用D 触发器级联实现正确的延时。

2.5 控制单元设计在此系统中,控制器的主要作用是保证在每个时钟周期提取到正确的旋转因子。

64点FFT 中每一级都有32个蝶形处理单元,不同在于蝶形单元的旋转因子不同。

第一级的旋转因子为064W ,164W ,264W ,…, 3164W ,第二级的旋转因子为064W ,264W ,464W ,664W ,…,3064W ,第三级的旋转因子为064W ,464W ,864W ,1264W ,…,2864W ,第四级的旋转因子为064W ,864W ,1664W ,2464W ,第五级原本的旋转因子为064W ,1664W ,即为1和(-j),因此采用条件选择的反相器实现。

由上面的旋转因子可以发现地址单元每一级以2的倍数递增,因此采用一个32进制的计数器来控制地址位。

第一级为计数器的五位计数输出,选择32个旋转因子,第二级为计数器的低四位输出,然后在最低位添0,第三级为计数器的低三位输出,然后在低2位添0,第四级为计数器的低两位输出,然后在低3位添0,第五级选择计数器的最低位作为控制位。

这样可以控制旋转因子的正确提取。

2.6 系统的数据流图图7表示了系统处理数据的流程,由图可以看出,此系统处理数据的顺序是倒序输入,顺序输出。

输入数据流输出数据流 图7 系统的数据流图三功能验证与仿真综合3.1 系统模块RTL级电路设计采用verilog语言,通过Modelsim软件进行仿真。

系统顶层模块如图7所示,表1为输入输出端口说明。

图8 系统顶层模块表1 输入输出端口说明3.2功能验证在本设计中,数据的表示采用定点的二进制表示方法,定点的位数为9位,最高位是符号位。

旋转因子的预值采用matlab计算后转换成二进制补码。

验证时取一组数据计算,通过matlab计算比较。

由于在运算单元的处理过程中,加法和乘法的结果位宽始终保持10位,因此每经过一次加法操作,都有一次截尾的量化过程,一共经过了六级蝶形运算,最后得到的结果是实际值的1/64,将计算的结果与matlab计算的值对比有一定的误差。

图8是计算结果的波形图。

按系统结构,经过62个延迟单元后开始流水顺序输出结果,由于前64个周期内取第二帧的初始数据,全为0,第一帧输入数据的计算结果在126个周期后流水输出。

因此选取此时为输出数据有效。

图8 仿真波形图3.3综合结果采用synopsys公司的Design Compiler对系统综合,综合采用smic0.18工艺库,综合后的结果如表2所示。

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