10频谱分析仪设计外文资料翻译
天津德力电子仪器 DS8810A B 频谱分析仪 说明书 Ver.1.2
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10频谱分析仪计划外文资料翻译
MATLAB的关键特性介绍MATLAB 是一种应用于算法开发、数据显示、数据分析、数值计算方面的高级计算机语言和交互式开发环境。
使用MATLAB软件，你能比例如C、C++, 或者Fortran更快的解决技术上的问题。
你能在很多领域使用MATLAB，例如信号或者图像处理、通讯、控制、测量、金融建模和生物学计算等。
可以通过添加某些收集了特殊用途函数的工具箱来将MATLAB专门用于解决某一应用领域的问题。
MATLAB 为编排和分享你的功能提供了一系列的功能。
你可以将MALAB代码与其他语言整合，并且区别开算法与应用程序。
关键特性(1)高级的计算语言。
(2)开发环境支持代码、文件、数据的管理。
(3)采用了为重复研究、设计和解决问题的交互式的工具。
(4)为线性代数、统计学、傅立叶分析、滤波器设计、最优化设计、数值综合等设计了相关的数学函数。
(5)为显示数据而准备了2-D 和3-D 图形功能。
(6)有个性化的用户接口工具。
(7)有外部语言（例如C, C++,Fortran, Java, COM,和Microsoft Excel）集成在Matlab中的函数。
开发算法和应用MATLAB 提供了一个高级语言和开发工具，这些允许让你能迅速的开发和分析你的算法和应用。
MATLAB 语言MATLAB 语言支持向量和矩阵，而这些是工程和特殊问题的基本。
它允许快速的开发和执行。
有了MATLAB 语言，你可以比其他传统的语言在编写和开发算法方面更加快速。
因为你不再需要去执行一些低级的操作，例如定义变量、s制定数据类型和分配内存。
在许多例子中，MATLAB 可以不用‘for’语句. 结果是一行MATLAB语句可以替代许多行的 C or C++ 代码.同时，MATLAB 提供传统编程语言的所有特性，包括算法操作、流控制、数据结构、数据类型、面向对象(OOP)和调试特性。
MATLAB 允许你在执行一个命令或者一组命令时不去编译和链接，确保你能够迅速的重试而得到最优的解决方案。
简易频谱分析仪设计资料
摘要该简易频谱分析仪以单片机AT89S52为控制核心，控制高中频的二次变频扫频接收机进行频谱分量分析，同时在示波器屏幕上显示频谱分量，具有分析范围宽、高镜像抑制比和高分辨力的特点。
该作品很好地达到了设计目标。
一、方案设计与论证1、总体设计方案方案一：将被测信号放大后直接用DSP或单片机经A/D转换后进行傅立叶展开等数字处理，将得到的结果送到示波器等显示器件进行显示。
这个方案的优点是比较容易从软件上进行各种数字运算的处理，因为本题目要求的指标并不高，采用这个方案将会极大提高设计成本和增加开发难度；方案二：参考题目推荐的方法，该题目可设计成一扫频接收机，在扫频范围内能检测到每个频点上的信号幅度，此方案的优点是电路比较简单，不需要DSP等专用芯片处理就可以满足设计要求，缺点是实时性比较差。
比较两种方案，考虑制作难度、性价比和时间等因素，我们选用了方案二，参考专业短波通讯中的接收机电路，采用二次变频法将会得到比较高的镜像抑止比、灵敏度和选择性。
2、输入调谐回路方案一：采用变容二极管和电感线圈组合成的压控可变中心频率的LC调谐回路进行选频，这种电路的优点是可以得到良好的选频特性，缺点是在1－30MHZ的覆盖范围内单个LC 回路难以实现，需要用到频段切换等技术处理，难以做到比较好的一致性；方案二：采用非调谐宽带滤波的办法，输入级不设选频电路，只设置一个通频带为1－30MHZ的带通滤波器，缺点是没有选频特性，但是电路简单可靠；综合比较后选择方案二，选频的实现是在一次变频后用中心频率为45.499MHZ的LC滤波器选频。
3、混频器混频器是外差式接收电路必不可少的。
方案一：用分立元件如三极管和二级管组成，显然电路比较简单，但是在混频增益和性能一致性上有所欠缺；方案二：用集成电路混频器，虽然一般的器件存在动态范围小的缺点，但是混频增益高和性能稳定；本作品需要用到两个混频器，要求比较高，综合比较后选择方案二，采用性价比很高的NE602作为混频器件，事实证明有很好的效果。
频谱分析仪的实用方法和操作流程
频谱分析仪的实用方法和操作流程英文回答：Spectrum analyzers are widely used in various fields such as telecommunications, audio engineering, and RF testing. They are essential tools for analyzing and measuring the frequency spectrum of signals. In this response, I will explain the practical methods and operating procedures of a spectrum analyzer.To begin with, the first step in using a spectrum analyzer is to connect the device to the signal source. This can be done using a coaxial cable or other appropriate connectors. Once the connection is established, the next step is to power on the spectrum analyzer and set the desired frequency range. This can be done by using the frequency control knob or entering the specific frequency range through the keypad or touchscreen.After setting the frequency range, it is important toadjust the resolution bandwidth (RBW) and video bandwidth (VBW) parameters. The RBW determines the frequencyresolution of the spectrum analyzer, while the VBW affects the displayed video output. These parameters can beadjusted based on the specific requirements of the analysis.Once the basic settings are configured, the spectrum analyzer can be used to measure and analyze the signal.This can be done by selecting the appropriate measurement mode, such as peak hold, average, or normal mode. The spectrum analyzer will then display the frequency spectrumof the signal in real-time.In addition to basic measurements, spectrum analyzers also offer advanced features such as marker functions,which allow users to measure specific frequencies or bandwidths of interest. This can be useful for identifying and analyzing specific signal components.Furthermore, spectrum analyzers often provide various display options such as logarithmic or linear scale, amplitude or power measurement, and different windowingfunctions. These options can be adjusted to enhance the visibility and accuracy of the displayed spectrum.In summary, the practical methods and operating procedures of a spectrum analyzer involve connecting the device to the signal source, setting the frequency range, adjusting the RBW and VBW parameters, selecting the measurement mode, and utilizing advanced features anddisplay options. By following these steps, users can effectively analyze and measure the frequency spectrum of signals.中文回答：频谱分析仪在电信、音频工程和射频测试等各个领域广泛应用。
基于matlab的频谱分析仪设计
Frequency AnalyzerYangXiao M2013705103HuaZhong University of Science and TechnologySchool of Mechanical Science and Engineering Abstract: Matlab Is a numerical analysis, matrix calculation, scientific data visualization and nonlinear dynamic state system modeling and simulation, and other functions of practical software engineering.It’s easy to use the windows environment and cast off a tradition on the interactive programming language (such as C, Fortran) Edit mode In large range.In this report,The task is to design a frequency analyzer by using matlab.Keyword:frequency analyzer;Matlab;time-domainanalysis;frequency-domain analysis;1.PrefaceMATLAB is called Matrix Laboratory，which is designed by the United States MathWorks company.It’s a commercial mathematical software. Matlab can be use for Matrix operations, mapping functions and data, algorithm, creating the user interface, connect to other programming languages procedures, mainly used in engineering calculations, control design, signal processing and communications, image processing, signal detection, design and financial modeling analysis and other fields. GUI (Graphical User Interface, referred to as GUI, known Graphical User Interface) is displayed using the graphical user interface of computer operations.. Matlab has a powerful GUl tool. In this report, by using matlab GUI tool we could design a frequency analyzer.Frequency analyzer is the instrument which could be used to study the structure of the electrical signal spectrum, and used to measure the signal parameters of signal distortion, modulation, frequency stability and spectral purity.Frequency analyzer could be used to measure some parameters of amplifier and filter circuit system , and it is a kind of multipurpose electronic measuring instrument.FFT (Fast Fourier Transformation) is the fast algorithm of DFT(discrete Fourier transformtion), which is based on discrete Fourier transform.By using FFT we could get the answer faster than DFT.2.IntroduceThe frequency analyzer which is designed by using matlab have three models:record,play wav file and generator some waves .Every model could make three kinds of waveforms:the time domain figure,the frequency spectrum domain figure and the power spectrum figure.We could get the message we want from the frequency analyzer.The interface is that:2.1 Interface3. Design PrinciplesThe task is to design the frequency analyzer which can record,open wav file and play it,generator some kinds of waveforms . Each waveform could do FFT analysis and draw its frequency spectrum figure and power spectrum figure.3.1 signal input3.1.1 choose signal inputWhen we start using the frequency analyzer,we should first set the sampling frequency,sampling numbers and the model of inputting signal.The frequency analyzer has three model of inputting:it’s the record,open and play wav file,signal generator.The program is(just the record):val=get(handles.model,'Value');switch valcase 1h=findobj('Tag','recordtime');set(h,'enable','on');h=findobj('Tag','startrecord');set(h,'enable','on');h=findobj('Tag','filename');set(h,'enable','off');h=findobj('Tag','openfile');set(h,'enable','off');h=findobj('Tag','wave');set(h,'enable','off');h=findobj('Tag','amplitude');set(h,'enable','off');h=findobj('Tag','frequency');set(h,'enable','off');h=findobj('Tag','phase');set(h,'enable','off');h=findobj('Tag','add');set(h,'enable','off');h=findobj('Tag','generatorwave');set(h,'enable','off');When we choose one model ,the others couldn’t work.3.1.2 The recordWe could input the sound signal by using the microphone.Matlab provides the wavecord function,which can be used to get the signal of microphone.The program of record is :Fs=str2double(get(handles.samplefrequency,'String'));N=str2double(get(handles.recordtime,'String'))*Fs;handles.y=wavrecord(N, Fs,'double');handles.inputtype=1;guidata(hObject,handles);plot(handles.axes1,handles.y);ysize=size(handles.y);set(handles.samplenumber,'String',num2str(ysize(1)));3.1.3 Read the wav fileWe use the function of wavread to open the wav file and play it. Theprogram is:[fname,filepath]=uigetfile('*.wav','wav');set(handles.filename,'string',fname);[handles.y,Fs,bit]=wavread(fname);temp = wavread(get(findobj('Tag','filename'),'String'));handles.inputtype=2;guidata(hObject,handles);plot(handles.axes1,(1:length(handles.y))/Fs,handles.y);ysize=size(handles.y);set(handles.samplenumber,'String',num2str(ysize(1)));set(handles.samplefrequency,'string',Fs);wavplay(temp,Fs);3.1.4 Signal generatorMatlab has the general functions which can generator the general waveform directly.We judge the signals should add or not.The program is:Fs=str2double(get(handles.samplefrequency,'String'));N=str2double(get(handles.samplenumber,'String'));x=linspace(0,N/Fs,N);t=get(handles.wave,'Value');f=str2double(get(handles.frequency,'String'));a=str2double(get(handles.amplitude,'String'));p=str2double(get(handles.phase,'String')); switch tcase 1y=a*sin(2*pi*x*f+p);case 2y=a*square(sin(2*pi*x*f+p));case 3y=a*sawtooth(2*pi*x*f+p,0.5);case 4y=a*sawtooth(2*pi*x*f+p);case 5y=a*(2*rand(size(x))-1);endif get(handles.add,'Value')==0.0handles.y=y;elsehandles.y=handles.y+y;endhandles.inputtype=3;guidata(hObject,handles);plot(handles.axes1,handles.y);xlim([0 200]);3.2 Time domain analysisMatlab provides the functions of mean and std,which can easily calculate the mean and variance.The program is :Fs=str2double(get(handles.samplefrequency,'String'));N=str2double(get(handles.samplenumber,'String'));set(handles.vpp,'String',(max(handles.y)-min(handles.y)));set(handles.average,'String',mean(handles.y));set(handles.variance,'String',std(handles.y)^2);3.3 Frequency domain analysisMatlab provide the function of FFT,which can easily achieve the fast Fourier transform algorithm.The program is:Fs=str2double(get(handles.samplefrequency,'String'));N=str2double(get(handles.samplenumber,'String'));temple=handles.y;f=linspace(0,Fs/2,N/2);P=2*fft(temple,N)/N;Pyy=sqrt(P.* conj(P));plot(handles.axes2,f,Pyy(1:N/2));plot(handles.axes3,f,abs(P(1:N/2)).^2);3.4 Simulation3.4.1 The recordWe select the record ,set the record time and sampling frequency,pushthe start record button to begin recording.We can get the waveform of the sound in the graphic area axes1.If we push the time analysis button ,we could get the parameter of vpp,average variance.If we push the fft button,we could get the frequency spectrum figure and power spectrum figure in the graphic area axes2 and axes3.The result is shown:3.1 Image of record3.4.2 Read the wav fileThe result is shown:3.2 wav file amplitude-frequency characteristic3.4.3 Signal generatorWe set the waveform, amplitude, frequency, phase and other information to generate the waveform.The time domain analysis and frequency domain analysis is shown:3.3 amplitude-frequency characteristic of sin wave3.4 amplitude-frequency characteristic of square waveWe can add some waves and analysis3.5 phase frequency characteristics of Superposition signalOther waveform analysis:3.6 amplitude-frequency characteristic of noise4 .Exist problemWhen using the signal generator to generator the wave,the picture ofaxes3 (power spectrum)would change.I can’t solve this problem.And Ifail to build the window function.5.ConclusionIn the future study, I will learn MATLAB this powerful engineering software more harder and try to solve some common engineering problems.References[1] 薛山. MATLAB基础教程. [M] 北京：清华大学出版社，2011.3。
频谱分析仪测量和噪声(AN 1303)
AgilentSpectrum and Signal Analyzer Measurements and NoiseApplication Note 1303Measuring Noise and Noise-like DigitalCommunications Signals with Spectrum and Signal Analyzers3 3 3 3 6 7 8 8 9 101214 14 14 16 16 17 18 18 19 19 19 19 19 20 21 2223 23 24 25 27 28Table of ContentsPart I: Noise Measurements IntroductionSimple noise—Baseband, Real, Gaussian Bandpassed noise—I and QMeasuring the power of noise with an envelope detector Logarithmic processingMeasuring the power of noise with a log-envelope scale Equivalent noise bandwidth The noise markerSpectrum analyzers and envelope detectorsCautions when measuring noise with spectrum and Signal analyzersPart II: Measurements of Noise-like Signals The noise-like nature of digital signalsChannel-power measurements Adjacent-Channel Power (ACP)Carrier power Peak-detected noise and TDMA ACP measurements Part III: Averaging and the Noisiness of Noise MeasurementsVariance and averagingAveraging a number of computed resultsSwept versus FFT analysis Zero spanAveraging with an average detectorMeasuring the power of noise with a power envelope scale The standard deviation of measurement noise ExamplesThe standard deviation of CW measurements Part IV: Compensation for Instrumentation Noise CW signals and log versus power detectionPower-detection measurements and noise subtraction Log scale ideal for CW measurements Bibliography Glossary of Terms2IntroductionNoise. It is the classical limitation of electronics.In measurements, noise and distortion limit the dynamic range of test results.In this four-part paper, the characteristics of noise and its direct measurement are discussed in Part I. Part II contains a discussion of the measurement of noise-like signals exemplified by digital CDMA and TDMA signals. Part III discusses using averaging techniques to reduce noise. Part IV is about compensating for the noise in instrumentation while measuring CW (sinusoidal) and noise-like signals.Simple noise—Baseband, Real, GaussianNoise occurs due to the random motion of electrons. The number of electrons involved is large, and their motions are independent. Therefore, the variation in the rate of current flow takes on a bell-shaped curve known as the Gaussian Probability Density Function (PDF) in accordance with the central limit theorem from statistics. The Gaussian PDF is shown in Figure 1.The Gaussian PDF explains some of the characteristics of a noise signal seen on a baseband instrument such as an oscilloscope. The baseband signal is a real signal; it has no imaginary components.Bandpassed noise—I and QIn RF design work and when using spectrum analyzers, we usually deal with signals within a passband, such as a com-munications channel or the resolution bandwidth (RBW, the bandwidth of the final IF) of a spectrum analyzer. Noise in this bandwidth still has a Gaussian PDF, but few RF instruments display PDF-related metrics.Instead, we deal with a signal’s magnitude and phase (polar coordinates) or I/Q components. The latter are the in-phase (I) and quadrature (Q) parts of a signal, or the real and imaginary components of a rectangular-coordinate representation of a signal. Basic (scalar) spectrum analyzers measure only the magnitude of a signal. We are interested in the characteristics of the magnitude of a noise signal.Part I: Noise Measurements3Figure 1. The Gaussian PDF is maximum at zero current and falls off away from zero,as shown (rotated 90 degrees) on the left. A typical noise waveform is shown on the right.We can consider the noise within a passband as being made of independent I and Q components, each with Gaussian PDFs. Figure 2 shows samples of I and Q com-ponents of noise represented in the I/Q plane. The sig-nal in the passband is actually given by the sum of the I magnitude, v I , multiplied by a cosine wave (at the center frequency of the passband) and the Q magnitude, v Q , mul-tiplied by a sine wave. But we can discuss just the I and Q components without the complications of the sine/cosine waves.Spectrum analyzers respond to the magnitude of the signal within their RBW passband. The magnitude, or envelope, of a signal represented by an I/Q pair is given by:v env =√(v I 2+v Q 2)Graphically, the envelope is the length of the vector from the origin to the I/Q pair. It is instructive to draw circles of evenly spaced constant-amplitude envelopes on the samples of I/Q pairs as shown in Figure 3.Figure 2. Bandpassed noise has a Gaussian PDF independently in both its I and Q components.–3–2–10123–3–2–1123–3–2–10123–3–2–101234If one were to count the number of samples within each annular ring in Figure 3, we would see that the area near zero volts does not have the highest count of samples. Even though the density of samples is highest there, this area is smaller than any of the other rings.The count within each ring constitutes a histogram of the distribution of the envelope. If the width of the rings were reduced and expressed as the count per unit of ring width, the limit becomes a continuous function instead of a histo-gram. This continuous function is the PDF of the envelope of bandpassed noise. It is a Rayleigh distribution in the envelope voltage, v, that depends on the sigma of the sig-nal; for v greater than or equal to 0PDF (v)= (v–σ2)exp (–1—2 (v–σ)2)The Rayleigh distribution is shown in Figure 4.Figure 3. Samples of I/Q pairs shown with evenly spaced constant-amplitude envelope circlesFigure 4. The PDF of the voltage of the envelope of a noise signal is a Rayleigh distribution.The PDF is zero at zero volts, even though the PDFs of the individual I and Q components aremaximum at zero volts. It is maximum for v=sigma.5Measuring the power of noise with an envelope detectorThe power of the noise is the parameter we usually want to measure with a spectrum analyzer. The power is the heating value of the signal. Mathematically, it is the time-average of v2(t)/R, where R is the impedance and v(t) is the voltage at time t.At first glance, we might like to find the average enve-lope voltage and square it, then divide by R. But finding the square of the average is not the same as finding the average of the square. In fact, there is a consistent under-measurement of noise from squaring the average instead of averaging the square; this under-measurement is 1.05 dB The average envelope voltage is given by integrating the product of the envelope voltage and the probability that the envelope takes on that voltage. This probability is theThe average power of the signal is given by an analogous expression with v2/R in place of the "v" part:p–= ∫∞(v–R2)PDF(v)dv =2σ–R2We can compare the true power, from the average power integral, with the voltage-envelope-detected estimate ofv2/R and find the ratio to be 1.05 dB, independent of s andThus, if we were to measure noise with a spectrum analyzer using voltage-envelope detection (the linear scale) and averaging, an additional 1.05 dB would need to be added to the result to compensate for averaging voltage instead of voltage-squared.6Logarithmic processingSpectrum Analyzers are most commonly used in their logarithmic (log) display mode, in which the vertical axis is calibrated in decibels. Let us look again at our PDF for the voltage envelope of a noise signal, but let’s mark the x-axis with points equally spaced on a decibel scale, in this case with 1 dB spacing. See Figure 5. The area under the curve between markings is the probability that the logof the envelope voltage will be within that 1 dB interval. Figure 6 represents the continuous PDF of a logged signal which we predict from the areas in Figure 5.Figure 6. The PDF of logged noise is about 30 dB wide and tilted toward the high end.7Measuring the power of noise with alog-envelope scaleWhen a spectrum analyzer is in a log (dB) displaymode, averaging of the results can occur in numerous ways. Multiple traces can be averaged, the envelope can be aver-aged by the action of the video filter, or the noise marker (more on this below) averages results across the x-axis. Some recently introduced analyzers also have a detector that averages the signal amplitude for the duration of a measurement cell.When we express the average power of the noise in deci-bels, we compute a logarithm of that average power. When we average the output of the log scale of a spectrum analyzer, we compute the average of the log. The log of the average is not equal to the average of the log. If we go through the same kinds of computations that we did com-paring average voltage envelopes with average power envelopes, we find that log processing causes an under-response to noise of 2.51 dB, rather than 1.05 dB.1The log amplification acts as a compressor for large noise peaks; a peak of ten times the average level is only 10 dB higher. Instantaneous near-zero envelopes, on the other hand, contain no power but are expanded toward negative infinity decibels. The combination of these two aspects of the logarithmic curve causes noise power to measure lower than the true noise power.Equivalent noise bandwidthBefore discussing the measurement of noise with a spec-trum analyzer noise marker, it is necessary to understand the RBW filter of a spectrum analyzer.The ideal RBW has a flat passband and infinite attenuation outside that passband. But it must also have good time domain performance so that it behaves well when signals sweep through the passband. Most spectrum analyzers use four-pole synchronously tuned filters for their RBW filters. We can plot the power gain (the square of the voltage gain) of the RBW filter versus frequency as shown in Figure 7. The response of the filter to noise of flat power spectral density will be the same as the response of a rectangular filter with the same maximum gain and the same areaunder their curves. The width of such a rectangular filter is the equivalent noise bandwidth of the RBW filter. The noise density at the input to the RBW filter is given by the output power divided by the equivalent noise bandwidth.1. Most authors on this subject artifi cially state that this factor is due to1.05 dB from envelope detection and another 1.45 dB from logarithmicamplifi cation, reasoning that the signal is fi rst voltage-envelopedetected, then logarithmically amplifi ed. But if we were to measure the voltage-squared envelope (in other words, the power envelope, which would cause zero error instead of 1.05 dB) and then log it, we wouldstill fi nd a 2.51 dB under-response. Therefore, there is no real point in separating the 2.51 dB into two pieces.8The ratio of the equivalent noise bandwidth to the –3 dB bandwidth (An RBW is usually identified by its –3 dB BW) is given by the following table:Filter type Application NBW/–3 dB BW4-pole sync Most SAs analog 1.128 (0.52 dB)5-pole sync Some SAs analog 1.111 (0.46 dB)Typical FFT FFT-based SAs 1.056 (0.24 dB)The noise markerAs discussed above, the measured level at the out put of a spectrum analyzer must be manipulated in order to repre-sent the input spectral noise density we wish to measure. This manipulation involves three factors, which may be added in decibel units:1. Under-response due to voltage envelope detection (add1.05 dB) or log-scale response (add2.51 dB).2. Over-response due to the ratio of the equivalent noisebandwidth to the –3 dB bandwidth (subtract 0.52 dB). 3. Normalization to a 1 Hz bandwidth (subtract 10 timesthe log of the RBW, where the RBW is given in unitsof Hz).Most spectrum analyzers include a noise marker that accounts for the above factors. To reduce the variance of the result, the Agilent 8590 and 8560 families of spectrum analyzers compute the average of 32 trace points cen-tered around the marker location. The Agilent ESA family, which allows you to select the number of points in a trace, compute the average over one half of a division centeredat the marker location. For an accurate measurement, you must be sure not to place the marker too close to a discrete spectral component.The final result of these computations is a measure of the noise density, the noise in a theoretical ideal 1 Hz band-width. The units are typically dBm/Hz.Figure 7. The power gain versus frequency of an RBW filter can be modeled by a rectangular filterwith the same area and peak level, and a width of the “equivalent noise bandwidth.”9Spectrum analyzers and envelope detectorsA simplified block diagram of a spectrum analyzer is shown in Figure A.The envelope detector/logarithmic amplifier block is shown configured as they are used in the Agilent 8560 E-Series spectrum analyzers. Although the order of these two cir-cuits can be reversed, the important concept to recognize is that an IF signal goes into this block and a baseband signal (referred to as the “video” signal because it was used to deflect the electron beam in the original analog spectrum analyzers) comes out.Notice that there is a second set of detectors in the block diagram: the peak/pit/sample hardware of what is normally called the detector mode of a spectrum analyzer. These display detectors are not relevant to this discussion, and should not be confused with the envelope detector.The salient features of the envelope detector are two:1. The output voltage is proportional to the input voltage envelope.2. The bandwidth for following envelope variationsis large compared to the widest RBW.Figure A. Simplified spectrum analyzer block diagramFigure B. Detectors: a) half-wave, b) full-wave implemented as a “product detector,” c) peak. Practical implementations usually have their gain terms implemented elsewhere, and implement buffering after the filters that remove the residual IF carrier and harmonics. The peak detector must be cleared; leakage through a resistor or a switch with appropriate timing are possible clearing mechanisms.10Figure B shows envelope detectors and their associated waveforms in (a) and (b). Notice that the gain required to make the average output voltage equal to the r.m.s. voltage of a sinusoidal input is different for the different topologies. Some authors on this topic have stated that “an envelope detector is a peak detector.” After all, an idealized detector that responds to the peak of each cycle of IF energy inde-pendently makes an easy conceptual model of ideal behav-ior. But real peak detectors do not reset on each IF cycle. Figure B, part c, shows a typical peak detector with its gain calibration factor. It is called a peak detector because its response is proportional to the peak voltage of the signal. If the signal is CW, a peak detector and an envelope detec-tor act identically. But if the signal has variations in its envelope, the envelope detector with the shown LPF (low pass filter) will follow those variations with the linear, time-domain characteristics of the filter; the peak detector will follow nonlinearly, subject to its maximum negative-going limit, as demonstrated in Figure C. The nonlinearity will make for unpredictable behavior for signals with noise-like statistical variations. A peak detector may act like an envelope detector in the limit as its resistive load dominates and the capacitive load is minimized. But practically, the nonideal voltage drop across the diodes and the heavy required resistive load make this topology unsuitable for envelope detection. All spectrum analyzers use envelope detectors, some are just misnamed.Figure C. An envelope detector will follow the envelope of the shown signal, albeit with the delay and filtering action of the LPF used to remove the carrier harmonics. A peak detector is subject to negative slew limits, as demonstrated by the dashed line it will follow across a response pit. This drawing is done for the case in which the logarithmic amplification precedes the envelope detection, oppositeto Figure A; in this case, the pits of the envelope are especially sharp.Cautions when measuring noise with spectrum and signal analyzersThere are three ways in which noise measurements can look perfectly reasonable on the screen of a spectrum ana-lyzer, yet be significantly in error.Caution 1, input mixer level. A noise-like signal of very high amplitude can overdrive the front end of a spectrum ana-lyzer while the displayed signal is within the normal display range. This problem is possible whenever the bandwidth of the noise-like signal is much wider than the RBW. The power within the RBW will be lower than the total power by about ten times the log of the ratio of the signal band-width to the RBW. For example, an IS-95 CDMA signal with a 1.23 MHz bandwidth is 31 dB larger than the power in a 1 kHz RBW. If the indicated power with the 1 kHz RBW is –20 dBm at the input mixer (i.e., after the input attenuator), then the mixer is seeing about +11 dBm. Most spectrum analyzers are specified for –10 dBm CW signals at their input mixer; the level below which mixer compression is specified to be under 1 dB for CW signals is usually 5 dB or more above this –10 dBm. The mixer behavior with Gaussian noise is not guaranteed, especially because its peak-to-average ratio is much higher than that of CW signals.Keeping the mixer power below –10 dBm is a good practice that is unlikely to allow significant mixer nonlinearity. Thus, caution #1 is: Keep the total power at the input mixer at or below –10 dBm.Figure D. In its center, this graph shows three curves: the ideal log amp behavior, that of a log amp that clips at its maximum and minimum extremes, and the average response to noise subject to that clipping. The lower right plot shows, on expanded scales, the error in average noise response due to clipping at the positive extreme. The average level should be kept 7 dB below the clipping level for an error below 0.1 dB. The upper left plot shows, with an expanded vertical scale, the corresponding error for clipping against the bottom of the scale. The average level must be kept 14 dB above the clipping level for an error below 0.1 dB.Caution 2, overdriving the log amp. Often, the level dis-played has been heavily averaged using trace averaging or a video bandwidth (VBW) much smaller than the RBW. In such a case, instantaneous noise peaks are well above the displayed average level. If the level is high enough that the log amp has significant errors for these peak levels, the average result will be in error. Figure D shows the error due to overdriving the log amp in the lower right corner, based on a model that has the log amp clipping at the topof its range. Typically, log amps are still close to ideal for a few dB above their specified top, making the error model conservative. But it is possible for a log amp to switch from log mode to linear (voltage) behavior at high levels,in which case larger (and of opposite sign) errors to those computed by the model are possible. Therefore, caution #2 is: Keep the displayed average log level at least 7 dB below the maximum calibrated level of the log amp.Caution 3, underdriving the log amp. The opposite of the overdriven log amp problem is the underdriven log amp problem. With a clipping model for the log amp, the results in the upper left corner of Figure D were obtained. Caution #3 is: Keep the displayed average log level atleast 14 dB above the minimum calibrated levelof the log amp.In Part I, we discussed the characteristics of noise and its measurement. In this part, we will discuss three different measurements of digitally modulated signals, after showing why they are very much like noise.The noise-like nature of digital signalsDigitally modulated signals can be created by clocking a Digital-to-Analog Converter (DAC) with the symbols (a group of bits simultaneously transmitted), passing the DAC output through apre-modulation filter (to reduce the trans-mitted bandwidth), and then modulating the carrier with the filtered signal. See Figure 8. The resulting signal is obvi-ously not noise-like if the digital signal is a simple pattern. It also does not have a noise-like distribution if the band-width of observation is wide enough for the discrete nature of the DAC outputs to significantly affect the distribution of amplitudes.But, under many circumstances, especially test conditions, the digital signal bits are random. And, as exemplified by the channel power measurements discussed below, the observation bandwidth is narrow. If the digital update period (the reciprocal of the symbol rate) is less than one-fifth the duration of the majority of the impulse response of the resolution bandwidth filter, the signal within the RBW is approximately Gaussian according to the central limit theorem.A typical example is IS-95 CDMA. Performing spectrum analysis, such as the adjacent-channel power ratio (ACPR) test, is usually done using the 30 kHz RBW to observe the signal. This bandwidth is only one-fortieth of the symbol clock rate (1.23 Msymbols/s), so the signal in the RBW is the sum of the impulse responses to about forty pseudo-random digital bits. A Gaussian PDF is an excellent approxi-mation to the PDF of this signal.Channel-power measurementsMost modern spectrum analyzers allow the measurement of the power within a frequency range, called the channel bandwidth. The displayed result comes from the computa-tion:P ch =(B s–B n)(1–N) n2i=n1∑10(p i/10)Pch is the power in the channel, Bs is the specified bandwidth (also known as the channel bandwidth), Bnis the equivalent noise bandwidth of the RBW used, Nis the number of data points in the summation, pi is the sample of the power in measurement cell i in dB units (if pi is in dBm, Pch is in milliwatts). n1 and n2 are the end-points for the index i within the channel bandwidth, thus N=(n2 – n1) + 1.Part II: Measurements of Noise-like Signals Figure 8. A simplified model for the generation of digital communications signals.The computation works well for CW signals, such as from sinusoidal modulation. The computation is a power-sum-ming computation. Because the computation changes the input data points to a power scale before summing, there is no need to compensate for the difference between the log of the average and the average of the log as explained in Part I, even if the signal has a noise-like PDF (probability density function). But, if the signal starts with noise-like statistics and is averaged in decibel form (typically with a VBW filter on the log scale) before the power summation, some 2.51 dB under-response, as explained in Part I,will be incurred. If we are certain that the signal is of noise-like statistics, and we fully average the signal before per-forming the summation, we can add 2.51 dB to the result and have an accurate measurement. Furthermore, the aver-aging reduces the variance of the result.But if we don’t know the statistics of the signal, the best measurement technique is to do no averaging before power summation. Using a VBW ≥ 3RBW is required for insignifi-cant averaging, and is thus recommended. But the band-width of the video signal is not as obvious as it appears.In order to not peak-bias the measurement, the detector must be used. Spectrum analyzers have lower effective video bandwidths in sample detection than they do in peak detection mode, because of the limitations of the sample-and-hold circuit that precedes the A/D converter. Examples include the Agilent 8560E-Series spectrum analyzer family with 450 kHz effective sample-mode video bandwidth, and a substantially wider bandwidth (over 2 MHz) in the Agilent ESA-E Series spectrum analyzer family.Figure 9 shows the experimentally determined relationship between the VBW:RBW ratio and the under-response of the partially averaged logarithmically processed noise sig-nal.However, the Agilent PSA is an exception to the relation-ship illustrated by Figure 9. The Agilent PSA allows us to directly average the signal on a power scale. Therefore, if we are not certain that our signal is of noise-like statistics, we are no longer prohibited from averaging before power summation. The measurement may be taken by either using VBW filtering on a power scale, or using the average detec-tor on a power scale.Figure 9. For VBW ≥ 3 RBW, the averaging effect of the VBW filter does not significantly affect power-detection accuracy.Adjacent-Channel Power (ACP)There are many standards for the measurement of ACP with a spectrum analyzer. The issues involved in most ACP measurements are covered in detail in an article in Microwaves & RF, May, 1992, "Make Adjacent-Channel Power Measurements." A survey of other standards is available in "Adjacent Channel Power Measurements in the Digital Wireless Era" in Microwave Journal, July, 1994.For digitally modulated signals, ACP and channel-power measurements are similar, except ACP is easier. ACP is usually the ratio of the power in the main channel to the power in an adjacent channel. If the modulation is digital, the main channel will have noise-like statistics. Whether the signals in the adjacent channel are due to broadband noise, phase noise, or intermodulation of noise-like signals in the main channel, the adjacent channel will have noise-like statistics. A spurious signal in the adjacent channelis most likely modulated to appear noise-like, too, but a CW-like tone is a possibility.If the main and adjacent channels are both noise-like, then their ratio will be accurately measured regardless of whether their true power or log-averaged power (or any partially averaged result between these extremes) is mea-sured. Thus, unless discrete CW tones are found in the signals, ACP is not subject to the cautions regarding VBW and other averaging noted in the section on channel power above.But some ACP standards call for the measurement of abso-lute power, rather than a power ratio. In such cases, the cautions about VBW and other averaging do apply.Carrier powerBurst carriers, such as those used in TDMA mobile sta-tions, are measured differently than continuous carriers. The power of the transmitter during the time it is on is called the "carrier power."Carrier power is measured with the spectrum analyzerin zero span. In this mode, the LO of the analyzer doesnot sweep, thus the span swept is zero. The display then shows amplitude normally on the y axis, and time on the x axis. If we set the RBW large compared to the bandwidth of the burst signal, then all of the display points include all of the power in the channel. The carrier power is computed simply by averaging the power of all the display points that represent the times when the burst is on. Depending on the modulation type, this is often considered to be any point within 20 dB of the highest registered amplitude. (A trig-ger and gated spectrum analysis may be used if the carrier power is to be measured over a specified portion of a burst-RF signal.)Using a wide RBW for the carrier-power measurement means that the signal will not have noise-like statistics. It will not have CW-like statistics, either, so it is still wise to set the VBW as wide as possible. But let’s consider some examples to see if the sample-mode bandwidthsof spectrum analyzers are a problem.For PDC, NADC and TETRA, the symbol rates are under25 kb/s, so a VBW set to maximum will work well. It will also work well for PHS and GSM, with symbol rates of 380 and 270 kb/s. For IS-95 CDMA, with a modulation rate of 1.23 MHz, we could anticipate a problem with the 450 kHz effective video bandwidth discussed in the section on chan-nel power above. Experimentally, an instrument with 450 kHz BW experienced a 0.6 dB error with an OQPSK (mobile) burst signal.。
频谱分析仪
频谱分析仪频谱分析仪英文全称: Spectrum Analyzer系统主要的功能是在频域里显示输入信号的频谱特性.频谱分析仪依信号处理方式的不同,一般有两种类型;即时频谱分析仪(Real-Time Spectrum Analyzer)与扫描调谐频谱分析仪(Sweep-Tuned Spectrum Analyzer).即时频率分析仪的功能为在同一瞬间显示频域的信号振幅,其工作原理是针对不同的频率信号而有相对应的滤波器与检知器(Detector),再经由同步的多工扫描器将信号传送到CRT或液晶等显示仪器上进行显示,其优点是能显示周期性杂散波(Periodic Random Waves)的瞬间反应,其缺点是价昂且性能受限于频宽范围,滤波器的数目与最大的多工交换时间(Switching Time).最常用的频谱分析仪是扫描调谐频谱分析仪,其基本结构类似超外差式接收器,工作原理是输入信号经衰减器直接外加到混波器,可调变的本地振荡器经与CRT同步的扫描产生器产生随时间作线性变化的振荡频率,经混波器与输入信号混波降频后的中频信号(IF)再放大,滤波与检波传送到CRT的垂直方向板,因此在CRT的纵轴显示信号振幅与频率的对应关系.影响信号反应的重要部份为滤波器频宽,滤波器之特性为高斯滤波器(Gaussian-Shaped Filter),影响的功能就是量测时常见到的解析频宽(RBW,ResolutionBandwidth).RBW代表两个不同频率的信号能够被清楚的分辨出来的最低频宽差异,两个不同频率的信号频宽如低于频谱分析仪的RBW,此时该两信号将重叠,难以分辨,较低的RBW固然有助於不同频率信号的分辨与量测,低的RBW将滤除较高频率的信号成份,导致信号显示时产生失真,失真值与设定的RBW密切相关,较高的RBW固然有助於宽频带信号的侦测,将增加杂讯底层值(Noise Floor),降低量测灵敏度,对於侦测低强度的信号易产生阻碍,因此适当的RBW宽度是正确使用频谱分析仪重要的概念.频谱分析仪的使用一、什么是频谱分析仪在频域内分析信号的图示测试仪。
10MHz~30MHz频谱分析仪的设计与实现
• 113•本文设计了一种采用TI公司的浮点DSP控制器作为控制核心的频谱分析仪，它可以用于分析输入信号的幅频特性。
本设计主要由本振源模块、混频器模块、滤波器模块、ADC模块和显示器等组成。
系统通过DSP芯片控制本振源模块输出扫频信号，将其与输入信号通过混频电路及滤波电路得到最终输出信号，再由ADC模块将采集后的数据送入DSP进行快速傅里叶变换（FFT），分析处理数据后再显示输入信号的频率、幅度和频谱图。
经过测量，所测数据除了幅度有点波动外，其他参数基本没有误差，系统还设计了友好的人机界面，实现了频谱分析仪的实时性和准确性。
1.引言随着电子技术的发展，世界各国加速了对电子领域的研究，具体体现在竞相提高通信、雷达、遥控、导航等无线电电子设备的威力和效能等方面（邓斌，电子测量仪器：国防工业出版社，2008）。
利用频谱分析仪不仅可以准确快速地显示信号的频谱、提供大范围的动态测量，而且能够利用其所具有的各种测试功能对信号的频率、幅度、抗干扰特性以及信号频谱纯度进行数据的分析处理（李振华，基于DSP的频谱分析系统的设计：哈尔滨工程大学硕士论文，2012）。
频谱分析仪是针对信号频域特征进行分析的一种仪器。
其作用是分析处理一个信号所包含的各个频率，和各个频率的强弱关系。
传统的频谱分析仪一般都很复杂，它是由一些模拟电路组建起来的测试系统，如程控放大器、滤波器等等。
因此此类仪器一般需要特别专业的人士来操作，而且测量精度会因环境的变化而存在很大的影响，一旦出现毛病就很难排查出问题所在。
但随着微电子技术的高速发展，DSP的出现让这个问题有了解决的办法。
DSP具有很高的数据处理速度，可以快速的完成大量的数据运算，结合对频谱分析的各种算法，能够从数字领域对模拟信号进行频谱分析。
这样做不仅能够排除传统频谱分析仪由于模拟电路的误差而造成的影响，而且通过数字算法的优化能够很大限度的提高处理结果的保障性与真实性。
2.系统设计方案本文由快速傅里叶变换法所设计的频谱分析仪，外围电路简10MHz～30MHz频谱分析仪的设计与实现玉林师范学院数学与统计学院 广西高校复杂系统优化与大数据处理重点实验室 黄小津玉林师范学院物理与电信工程学院 罗扬静玉林师范学院数学与统计学院 邓 勋单、频率切换速度快、信号分辨率高而且便于集成。
频谱分析仪使用说明(中文)
目录频谱分析仪操作指南 (1)第一节仪表板描述 (1)一、前面板 (1)二、后面板(略) (6)第二节基本操作 (6)一、菜单操作和数据输入 (6)二、显示频谱和操作标记 (8)三、测试窗口和显示线 (12)四、利用横轴测试频率 (16)五、自动调整 (19)七、UNCAL信息 (22)第三节菜单功能描述 (24)频谱分析仪操作指南JV手机维修处频谱分析仪操作指南第一节仪表板描述一、前面板这部分包括前面控制板详细的视图、按键解释和显示在那些图片上的连接器，这可从频谱仪的前部面板看到，共分为九个部分，如下所述：1、显示部分23、软盘驱动部分4、MEASUREMENT部分124□5STOP65、DATA 部分6、MARKER 部分47、CONTROL 部分168、SYSTEM部分□REMOTE1PRESET□SHIFT349、混杂的部分10、屏幕注释312图1屏幕注释二、后面板(略)第二节基本操作一、菜单操作和数据输入用面板按键和选项去操作频谱分析仪。
使用面板键时，一个常见的菜单会显示在屏幕的右边。
但是，有一些键没有相关的软菜单，如AUTO TUNE和COPY键。
每菜单选项与功能键一一对应。
选择一个菜单，需要按相应的功能键。
在一些情形中，按功能键显示附加选项。
下面的例子指出了仪表板和软按键功能的多少。
1、选择菜单按LEVEL键显示用于安装测试的菜单。
参考线值显示在活动区域中，电平菜单显示在屏幕的右边，显示如下Ref LevelATT AUTO/MNLdB/divLinearUnitsRef Offset ON/OFF2、输入数据当一个值显示在激活区时，你可利用数字键、步进键或数据旋钮改变它。
●利用数字键输入数据可利用下面的键输入数据：数字键（0到9），小数点键，和退格（BK SP）或减号（－）键。
如果你使用数字键时出错，你可用退格（BK SP）键删除最近输入的数字。
如果你没有输入任何数据，按BK SP键输入一个减号（－）。
基于matlab简易声音信号频谱分析仪设计说明书
（4）MATLAB提供的声音文件读取函数和录音函数的利用问题。MATLAB顶用于声音读取的函数是wavread，该函数输入参数为文件名，输出结果有双声道的声音信号矩阵和音频采样率值。MATLAB中基于PC的录音函数是wavrecord，利用该函数时发觉，必需先设定好录音的时刻。关于该问题，我想过用多种方式来解决，但仍是没有找到十分好的解决方法。
N = size;
guidata(hObject,handles);
t=0:1/fs:(N(1)-1)/fs;
plot,t,;
xlabel,'Time (s)','fontweight','bold');
ylabel,'Amplitude','fontweight','bold');
grid;
上面代码为文件打开按钮的回调函数中的一部份，第一句打开文件对话框，限定选择.wav文件，返回选择的文件名。第二句读取打开的声音文件，并获取音频采样率的值。接着将取得的信号数据存入handles句柄。然后，依照获取到的音频采样率和数据长度还原出时刻轴序列。最后将信号波形输出到axes1坐标轴上。
实际应历时，能够通过利用截断函数(窗函数)来减小栅栏效应。下面仅以汉宁窗函数为例，说明其工作原理。
汉宁窗函数是余弦平方函数，又称为升余弦函数，它的时域形式能够表示为：
（2-9）
它的频率幅度特性函数为：
（2-10）
虚拟频谱分析仪的设计
虚拟频谱分析仪的设计The Design of the Virtual Spectrum Analysis Instrument摘要：本文介绍了虚拟频谱分析仪的设计方案，设计了该系统的硬件部分与软件部分。
该系统以数据采集卡，PC机为硬件开发平台，以图形化编程语言LabVIEW为软件开发平台，将虚拟仪器技术运用到频谱分析中来，增强了仪器的功能，节省了仪器的开发时间。
关键词：虚拟仪器； LabVIEW；频谱分析Abstract：This article introduced the design proposal of virtual spectrum analysis instrument，designing the systematic hardware part and software part. This system regards the data collecting card, computer as the hardware developing platform, and it takes figure programming language LabVIEW as the software developing platform .The system apply the technology of the virtual instrument to spectrum analysis and enhance the function of instruction and short the developing time of instrument.Keywords：virtual instrument；LabVIEW；Spectrum analysis0前言频谱分析是信号处理中非常重要的分析手段，通常的频谱分析主要依靠传统的频谱分析仪来完成，但这种频谱分析仪价格昂贵，体积庞大，功能单一。
实时频谱分析仪 RSTA (英文)
Keysight TechnologiesReal-Time Spectrum Analyzer (RTSA)X-Series Signal AnalyzersN9040B/N9030A/N9020A-RT1 & -RT2Technical OverviewFeatures–D etect signals as short as 3.33 ns with 100% POI–S can with up to ~510-MHz real-time bandwidth–P erform real-time signal analysis for frequencies up to THz with external mixing–M onitor a wide span of spectrum up to the full frequency range of the analyzer with stepped densitydisplay–F ocus on the signal of interest in a complex signal environment with effective triggering mechanismssuch as frequency mask trigger (FMT) and/or time qualified trigger (TQT)–S ee small signals in the presence of large ones with up to 78 dB spurious-free dynamic range–E liminate the need for a dedicated instrument: RTSA is an upgrade option for new and existing UXAs/PXAs/MXAs–G o deeper and thoroughly analyze complex signals with 89600 VSA softwareExperience Real-Time Spectrum Analysis– the Keysight WayThe UXA, flagship of Keysight X-Series signal analyzers, brings wideband real-time analysis with unmatched dynamic range. The PXA and MXA are the first mainstream signal analyzers to be upgradable to real-time capabilities. You can readily convert an existing analyzer in-place without re-calibration. With UXA, PXA or MXA as the founda-tion, you get new levels of performance, flexibility and usability in real-time spectrum analysis.With our real-time spectrum analyzer (RTSA) option, the UXA, PXA and MXA deliver excellent sensitivity, analysis bandwidth, frequency range and, most important, prob-ability of intercept (POI). In addition, a real-time UXA, PXA or MXA provides continuous acquisition of RF signals, including low-level signals occurring close to larger ones. Its conditional triggering capabilities can watch for transient or intermittent events and initiate signal capture, measurement and display. The ultimate result: you can see more, capture more and understand more.Summary of Key SpecificationsKnow You’ve Got ItEven at the extremes of signal analysis, your analyzer should be ready for anything.That’s why we’re offering real-time spectrum analysis (RTSA) as an upgrade option for new and existing UXA, PXA and MXA signal analyzers.Adding RTSA lets you see, capture and understand the most elusive signals—known or unknown. To go deeper, you can combine a real-time UXA, PXA or MXA with the 89600 VSA software to create a solution that lets you thoroughly characterize complex signals.Inside signal-rich systems and environments, go real-time with Keysight Technologies,Inc. and know you’ve got it.Frequency-hopping LTE-Advanced uplink signal Defining real-time analysis In a spectrum or signal analyzer with a digital intermediate frequency (IF) section, real-time operation is a state in which all signal samples are processed for some sort of measurement result or triggering operation. In most cases the measurement results are scalar—power or magnitude— corresponding to traditional spectrum measurements.In addition to gap-free analysis, a real-time RF analyzer may be defined as having four more key attributes: high-speed measure-ments, consistent measurement speed, frequency-mask triggering and advanced composite displays.In general, the stream of spectra from real-time processing can be used in one of two ways: The spectra can be combined into a composite spectrum display or successively compared to a limit mask to implement frequency-mask triggering. Both of these capabilities are present in theRTSA option.See, Capture and Understand the Most Elusive SignalsThe real-time X-Series include four key innovations: wider bandwidth and better dynamicrange, optimum detection and integrated analysis capabilities. Individually and col-lectively, these capabilities bring you a host of important benefits.See more with wider bandwidth and better dynamic rangeThe UXA, has the required combination of IF bandwidth, signal sampling and signalprocessing to handle ~510 MHz continuously. This gap-free bandwidth applies not onlyto real-time spectrum analysis but also to frequency-mask trigger (FMT), gap-free timecapture and real-time magnitude calculations for IF magnitude triggering.To help you detect small signals in the presence of large ones, the UXA, PXA and MXAprovide 78, 75, or 72 dB of SFDR, respectively, across the full analysis bandwidth.Dynamic range is enhanced by the low noise floor and excellent distortion performanceof the analyzers. When dealing with very small signals above 3.6 GHz, the low noise path (LNP), which is standard for the UXA and optional for the PXA, further improves sensitiv-ity while still handling high-level signals.Detect the smallest infrequent eventsThe X-Series analyzers’ advanced processing architecture combines with its wideanalysis bandwidth and wide dynamic range to provide 100 percent POI for signals withdurations as short as 3.517 µs with full amplitude accuracy. Consistently detect signalsthat are only 3.3 ns in duration. Gap-free analysis is just one element of signal detection.Within the instrument, other contributing factors are processor and analyzer dynamicrange (including sensitivity), sampling bandwidth, processing continuity and FFTprocessing overlap (which compensates for windowing functions).Figure 1. See small signals in the presence of large ones Figure 2. View a fast-hopping radar signalUnderstand more withintegrated analysis capabilitiesIn some cases, simply finding an elusive signal is enough. In other situations, finding the signal is just the first step toward a thorough understanding of what’s happening. This is when the combination of a real-time UXA, PXA or MXA, real-time FMT and the 89600 VSA software is especially useful.The real-time trigger can start any VSA measurement—one or many—in any measure-ment mode, including demodulation. The trigger can be initiated when a specificspectrum mask is entered or exited, or with more complex sequences such as exitfollowed by re-entering. Pre- and post-trigger delays are also available, letting you make measurements of signals prior to the trigger event.Time qualified triggering can also be used in conjunction with the FMT or with a leveltrigger. This gives another tool to help find specific signals of interest.These capabilities make the real-time UXA, PXA or MXA plus VSA a great combination for measuring modulated transients, frequency-hopping signals, frequency settling, andundesired transients in signal sources such as VCOs or YIG oscillators.Figure 3. Use FMT to identify signals in frequency hopping pulses. UXA's multi-touch user interface significantly simplifies setting up the FMT.Figure 4. Real-time FMT trigger in the VSA software to demodulate a frequency hopping signalGo deeper with the 89600 VSA The 89600 VSA software is a comprehensive set of tools for demodulation and vector signal analysis. These tools enable you to explore virtually every facet of a signal and optimize your most advanced designs.You can use the 89600 VSA to measure more than 75 modula-tion types, from custom OFDM or APSK to standard-based signals such as MIL-STD, GSM and LTE. With frequency-mask triggering, you can capture intermittent sig-nals for detailed characterization,and then use them as stimulussignals by playing them back withan Keysight signal generator orin simulation software such asKeysight SystemVue.Characterize Highly Elusive Radar and EW SignalsFrom simple to complex, all radar, EW and ELINT systems pose a variety of challenges whether you’re testing components, subsystems or systems. When deployed, these sys-tems operate in cluttered spectral environments filled with intentional and unintentional interferers. In the lab or in the field, a real-time X-Series lets you see more, capture more and understand more.Maximize the performance of radar and EW systems during developmentAdding RTSA creates a cost-effective solution that combines real-time analysis with traditional spectrum measurements such as noise figure, phase noise and power. For example, you can use a real-time PXA to identify spurious signals using traditional swept analysis then switch modes to see pulsed spurs using real-time analysis and displays. The PXA will detect all signals with durations greater than 3.57 µs—the best POI cur-rently available—with full amplitude accuracy. For signals with a large signal-to-noise ratio (> 60 dB), the PXA will detect signals with durations as short as 5 ns.Using a UXA, performance is further enhanced with very wideband analysis. Find signals that are only 3 or 4 ns of duration. In addition, the UXA adds a very large multi-touch screen that helps quickly zoom and visually identify interesting signal activity. Usingthe UXA's metrology grade ADC ensures that a wide dynamic range of signals can be measured without distortion from the analyzer. When creating or analyzing jamming techniques, you can use FMT with the 89600 VSA software and its record/playback capabilities.Capture, catalog and understand highly elusive signals in the field Being able to identify intentional and unintentional interferers requires a variety of powerful signal-analysis tools. To help you view faint return signals in transient or dynamic antenna scans, the real-time UXA enhances POI with a noise floor of –157 dBm (10 GHz, no preamp).Capabilities such as simultaneous display of real-time spectrogram and power-versus-time enable you to capture radar and communication jamming and interference. By combining FMT with the 89600 VSA software, you can easily identify, capture and play back portions of EW techniques.Figure 5. Multi-measurement with a pulsed signal (screen image from UXA) Figure 6. Radar mode switching Figure 7. Narrow band frequency domain analysis of a pulse signal changing frequency over time whilesimultaneously maintaining a wider span for accurate pulse timing measurementsAnalyze dynamic signals simultaneously in frequency and timedomainThe UXA and PXA X-Series signal analyzers, with option B5X installed, can independent-ly adjust the spans of each 255 MHz digitizer with the addition of option DUA (DuplexIF). By utilizing this dual architecture, you can optimize each digitizer for accurate timedomain analysis while maintaining good frequency resolution.Accelerate Development of Communication Systems Whether you’re focused on transmitters, transceivers or whole radios, today’s systems rely on signals that are agile, wide and complex. Adding RTSA to an X-Series analyzer creates a cost-effective solution that combines traditional spectrum measurements with real-time capabilities, including the highest performance in transient real-time analysis.Enhance performance in wireless communication and connectivity With a real-time MXA, you can capture and analyze complete transmitter-channel char-acteristics at gap-free bandwidths of up to 160-MHz within a 26.5-GHz frequency range. In highly integrated multimode multiband devices (MMMDs), you can identify intermittent interoperability issues with the ability to capture signals as short as 7 ns, the bestreal-time analyzer performance available. You can also observe base station function using wideband persistence displays, which help pinpoint problems such as intermittent pre-distortion issues. FMT capabilities enable you to characterize frequency switching, verify overall system operation and find system violations or interfering signals. The time qualified triggers allow you to pick specific bursted signals out of dense spectral environments. For deeper analysis, add the 89600 VSA software: with support for dozens of standards-based signals and custom waveforms, chances are good it can demodulate the signals you’re working with. To reveal greater detail, you can check PLL settling and identify LO issues by combining FMT, VSA software and real-time spectrogram displays. Push performance higher in MILCOM and SATCOM systemsIn today’s crowded signal environment, multi-format, high-rate communication systems are more likely to experience interoperability issues. To verify system performance, you can use a real-time PXA to perform fast pre-scans up to 50 GHzwith swept-tuned capabilities, then zoom in using real-time mode with up to 75 dB of dynamic range.RTSA provides the performance you need to observe radio function using wideband persistence and pinpoint possible issues caused by errors in baseband algorithms.You can also review cognitive radio algorithms and dynamic spectrum management scenarios with wideband real-time persistence across 160-MHz spans.In the field, easily measure small signals in the presence of powerful transmitters with industry-leading performance in noise floor and distortion. Multi-domain triggers allow you to pick out a specific frequency hop as well as specific durations. These capabilities let you sift through a dense environment and easily find previously undetected intermit-tent interferers or “signals within signals.”Figure 8. A transition analysis for various WLAN signals showing the frequency-switching performance when in the presence of a pulsed signal (DFS).Figure 9. Spectral analysis of an LTE signal where, without demodulation, you can see the signal, control and synch structures are present.Eliminate the need for a Dedicated Real-Time Analyzer With the availability of RTSA as an upgrade option, you can eliminate the need for a spe-cialized or dedicated instrument. A real-time UXA/PXA/MXA retains all the functionality of a traditional signal analyzer. Utilize integrated applications for power measurements and communications standards and, when needed, shift to real-time capabilities in the same unit 1.See the real performance with the UXA signal analyzerThe UXA is the flagship of Keysight's X-Series signal analyzers, leveraging proprietary technologies and a streamlined, touch-driven interface. By providing a wider, deeperview of elusive and wideband signals -- known or unknown -- the UXA enables you to see more and take your design farther.–See your signals of interest more clearly with spurious-free dynamic range (SFDR) of > 78 dB across the 510 MHz analysis bandwidth–Understand the purity of your design with industry-leading phase noise of -136 dBc/Hz at 1 GHz (10 kHz offset)–Simplify the complex measurements with a 14.1" capacitive touchscreen userinterface1. At present, the only X-Series measurement application software available to UXA is the N9068Cphase noise measurement.Drive your evolution with the PXA signal analyzerThe future-ready PXA is the evolutionary replacement for your current high-performancesignal analyzer. It helps you sustain your past achievements, enhance current designsand accelerate future innovation with industry-leading performance:–Reduce measurement uncertainty with ± 0.19 dB absolute amplitude accuracy–See more with excellent sensitivity: DANL is –157 dBm/Hz at 10 GHz (no preamp)–Characterize high-precision signals with phase noise of –132 dBc/Hz at1 GHz (10 kHz offset)Accelerate in wireless with the MXA signal analyzerThe MXA is the accelerator as you develop new wireless devices. It has the versatility toeasily adapt to your evolving test requirements, today and tomorrow:–Accurately measure your designs across 160 MHz bandwidth with 0.3% (–50 dB)EVM for 802.11ac WLAN–Characterize signals with phase noise of –114 dBc/Hz at 1 GHz (10 kHz offset)–Address multiple formats, generations and devices with a broad library of one-button standard-specific measurement applications for WLAN, LTE, MSR, andmore.Figure 10. Noise figure measurementFigure 11. 5-carrier LTE-Advanced signal with in-band and out-of-bandinterferenceKey SpecificationsValues in this table describe the key performance of RTSA parameters. Refer to the UXA, PXA or MXA specifications guide for more details. Note: Data subject to changeMaximum Span85 MHz: Option B85For PXA/MXA120 MHz: Option B1A For MXA only160 MHz: Option B1X For PXA/MXA255 MHz: Option B2X or B5X For UXA onlySupported Detectors Max Peak, Min Peak, Sample, AverageNumber of Markers1212Maximum Time 40 s40 s Maximum time refers to the highest time value settable for theX-axis.Minimum Time 202 µs202 µs Minimum time refers to the lowest value settable for the X-axis.Resolution is ~200 ns. Number of points is 1024.1. This maximum RBW is for Option RT2 only. Option RT1 has a maximum RBW of 10 MHz.2. Option RT1 limits BW to less than 10 MHz.Display's available Density, Spectrogram, NormalTrigger resolution0.5 dBTrigger conditions Enter, Leave, Inside, Outside, Enter->Leave, Leave->Enter Minimum detectable signal duration with> 60 dB signal to mask (StM)Option RT2With Option B2X/B5X (for UXA only) 3.33 nsWith Option B1X (for PXA/MXA) 5 nsWith Option B1A (for MXA only)8 nsWith Option B85 (for PXA/MXA)11.42 nsMinimum duration for 100% trigger with max/min RBWs Option RT2Duration (µs)Span (MHz)RBW 4RBW 6 509.47 3.837NA 255 3.837 3.51 160 4.05 3.57 120 4.26 3.62 85 4.61 3.709Ordering InformationThe real-time spectrum analyzer is available as an option for the following X-Series signal analyzers. For complete ordering and configuration information, please refer to the respective configuration guides found on the “Options and Accessories” tab on the product web pages.UXA signal analyzerModel-Option Description NotesN9040B-RT1Real-time analysis up to ~510 MHzBW, basic detection For frequency mask trigger: minimum 17.3 μs signal duration for 100% POI; requires Option B2X or B5X, the analysis BW option determines maximum real-time BWN9040B-RT2Real-time analysis up to ~510MHzBW, optimum detection For frequency mask trigger: minimum 3.517 μs signal duration for 100% POI; requires Option B2X or B5X, the analysis BW option determines maximum real-time BWPXA signal analyzerModel-Option Description NotesN9030A-RT1Real-time analysis up to 160 MHzBW, basic detection For frequency mask trigger: minimum 17.3 μs signal duration for 100% POI; requires Option B85 or B1X, the analysis BW option determines maximum real-time BWN9030A-RT2Real-time analysis up to 160 MHzBW, optimum detection For frequency mask trigger: minimum 3.57 μs signal duration for 100% POI; requires Option B1X or B85, the analysis BW option determines maximum real-time BWN9030A-RTR Real-time spectrum recorder andanalyzer application(Option RTR)Enables recording, analyzing and playback of signal and spectrum density data for detecting and analyzing signal anomalies, and for viewing the evolution of signals and spectrum density over time.MXA signal analyzerModel-Option Description NotesN9020A-RT1Real-time analysis up to 160 MHzBW, basic detection For frequency mask trigger: minimum 17.3 μs signal duration for 100% POI; requires Option B85, B1A or B1X, the analysis BW option determines maximum real-time BWN9020A-RT2Real-time analysis up to 160 MHzBW, optimum detection For frequency mask trigger: minimum 3.57 μs signal duration for 100% POI; requires Option B1X, B1A, or B85, the analysis BW option determines maximum real-time BWN9020A-RTR Real-time spectrum recorder andanalyzer application(Option RTR)Enables recording, analyzing and playback of signal and spectrum density data for detecting and analyzing signal anomalies, and for viewing the evolution of signals and spectrum density over time.You Can Upgrade!Options can be added after yourinitial purchase.All of our X-Seriesapplication optionsare license-keyupgradeable.UPGRADEAdditional ResourcesApplication notes and videosMeasuring Agile Signals and Dynamic Signal Environments:/find/AgileSignals_ANYouTube playlist for real-time spectrum analyzer:h ttps:///playlist?list=PLmqzNmmPZGY_mqc74YxFw_huUNV7JkLgN ProductsReal-time spectrum analyzer: /find/RTSAUXA signal analyzer: /find/UXAPXA signal analyzer: /find/PXAMXA signal analyzer: /find/MXA89600 VSA software: /find/89600vsaApplicationsAerospace and defense: /find/ADCellular: /find/cellular802.11 WLAN: /find/WLAN16 | Keysight | Real-Time Spectrum Analyzer (RTSA) X-Series Signal Analyzers N9040B/N9030A/N9020A-RT1 & -RT2 - Technical OverviewThis information is subject to change without notice.© Keysight Technologies, 2017Published in USA, December 1, 20175991-1748EN/find/RTSAFor more information on KeysightTechnologies’ products, applications or services, please contact your local Keysight office. The complete list is available at: /find/contactusFor other unlisted countries:/find/contactus (BP-9-7-17)/go/quality Keysight Technologies, Inc.DEKRA Certified ISO 9001:2015Quality Management SystemEvolving Since 1939Our unique combination of hardware, software, services, and people can help you reach your next breakthrough. We are unlocking the future of technology. From Hewlett-Packard to Agilent to Keysight.myKeysight/find/mykeysightA personalized view into the information most relevant to you. /find/emt_product_registrationRegister your products to get up-to-date product information andfind warranty information.Keysight Services/find/serviceKeysight Services can help from acquisition to renewal across your instrument’s lifecycle. Our comprehensive service offerings—one-stop calibration, repair, asset management, technology refresh, consulting, training and more—helps you improve product quality and lower costs.Keysight Assurance Plans/find/AssurancePlansUp to ten years of protection and no budgetary surprises to ensure your instruments are operating to specification, so you can rely on accurate measurements.Keysight Channel Partners/find/channelpartnersGet the best of both worlds: Keysight’s measurement expertise and product breadth, combined with channel partner convenience.。
频谱分析仪
惠普8594E频谱分析仪8594E SPECTRUM ANALYZER使用说明：●此手册从英文版中选择按键及其子菜单进行翻译●在‘按键详细说明’部分以空格数表示目录等级仪器面板总览――――――――――――――――――――――――――――――――1 按键详细功能――――――――――――――――――――――――――――――――2仪器面板总览―――――――――――――――――――――――――――――――――――――――Figure 2-1 Front Pannel1.液晶显示器 7.数据设置区2.独立按键 8.步进微调区3.显示窗口设置区 9.测试端口区4.标记区 10.软驱5.设备状态区 11.开关6.控制设置区INDEPENDENT Button： MARKER Block：Frenquency：频率 MKR：设置标志点Span：设置扫描范围 MKR→下一个标志点Amplitude：设置幅度 MKR FCTN：标记功能WINDOWS Block：Peak Search：搜索峰值点ON：设置S参数CONTROL Block：Next：设置格式 Sweep：扫描Zoom：设置比例尺 BW：带宽INSTRUMENT STATE Block：Trig：触发Preset：预设置值 Auto Couple：自动耦合Config：配置 Trace：跟踪Cal：校准 Display：显示Aux CTRL辅助设备设置DATA Block：Copy：复制 GHz/＋dBm/dB：单位输入Mode：模式选择MHz/－dBm/sec：单位输入Save：保存KHz/mV/ms：单位输入Recall：调用Hz/uV/uS：单位输入Meas/User：设置特殊参数Enter：输入确认SGL SWP：单次扫描****************************************************************************** 按键详细功能：―――――――――――――――――FREQUENCY：（频率设定）Center Freq：设置中心频率Start Freq：设置起始频率Stop Freq：设置终止频率CF Step：中心频率步进AUTO：自动设置MAN：手动设置Freq Offset：频率偏置设置------------------------------------------------SPAN：（扫描范围）Span：扫描范围设置Span Zoom：扫描范围扩大Full Span：全范围扫描Zero Span：零扫描Last Span：最近的扫描Peak Zoom：峰值附近扫描范围扩大------------------------------------------------AMPLITUDE：（幅度设置）Ref LVL：设定参考标准ATTEN：衰减设置AUTO：自动设置MAN：手动设置Scale：比例设置LOG：取10为底的对数显示LIN：直接线性显示------------------------------------------------ PRESET：（初始复位）Spectrum Analyzer：频谱仪复位------------------------------------------------ CONFIG：（设置）Copy DEV：复制设备设置PRNT：打印机PLT：显示图Plot Config：图区设置PLTS/PG：每页显示多少图1．2．4：1个图，或2个图，或4个图PLT/LOC：选择哪一个图PL T→LJT：绘图到激光打印机ON：开启OFF：关闭PLT Port Config：绘图端口设置PRN PORT：打印端口设置HPIB：HPIB端口PAR：并行端口PLT PORT：绘图端口HPIB：HPIB端口PAR：并行端口Previous Menu：前一个菜单PLT Menu：绘图菜单ON：打开OFF：关闭Previous Menu：前一个菜单Print Config：打印设置Set B&W Printer：设置黑白打印HP B&W Printer：惠普黑白打印HP B&W Expand：惠普黑白打印扩展EP MX80：爱普生MX80打印机SML：单面打印LRG：双面打印EP LQ570：爱普生LQ570打印机SML：单面打印LRG：双面打印Previous Menu：前一个菜单Set Color Printer：设置彩色打印机Paint Jet Printer：设置喷墨打印Desk Jet Color：设置喷墨色彩Desk Jet Expand：喷墨扩展Previous Menu：前一个菜单Prn Port Config：打印端口设置PRN Port：打印端口HPIB：HPIB端口PAR：并行端口PLT Port：绘图端口HPIB：HPIB端口PAR：并行端口Previous Menu：前一个菜单PRT Menu：打印菜单ON：打开OFF：关闭Printer Setup：打印机安装Previous Menu：前一个菜单Time Date：时间设定TMEDate：日期显示ON：打开OFF：关闭Date Mode：日期显示格式MDY：月日年DMY：日月年Set Time：设置时间Set Date：设置日期Previous：前一个菜单Change Prefix：改变名称ABCDEF：选取字符GHIJKL：选取字符MNOPQR：选取字符。
频谱分析仪
摘要本频谱分析仪是一种基于Matlab的波形分析、频谱分析的虚拟仪器，可以实现数字信号发生器的功能、录音、打开wav类型的声音文件，能实现数字信号的时域分析和频域分析，并绘制波形、频谱图，对信号加窗函数，以及其他的附加功能。
关键词：Matlab，频谱分析仪AbstractThis spectrum analyzer is a Matlab-based waveform analysis, spectrum analysis of the virtual instrument that can function digital signal generator, sound recordings, open wav sound files , to achieve time-domain digital signal analysis and frequency domain analysis, and draw the waveform, frequency spectrum, the signal windowing function, and other additional features.Keywords: Matlab, spectrum analyzer目录摘要 (1)Abstract (1)第一章概述 (3)第二章设计原理 (3)2.1 波形分析原理 (3)2.1.1 信号频率、幅值和相位估计 (3)2.1.2 数字信号统计量估计 (5)（1）峰值P的估计 (5)（2）均值估计 (5)（3）均方值估计 (5)（4）方差估计 (5)2．2 频谱分析原理 (5)2.2.1 DFT与FFT (5)2.2.2 频率、周期的估计 (6)2.2.3 频谱图 (6)2.2系统的功能分析 (7)第三章系统的界面设计 (8)3.1图形界面和主要新功能介绍 (8)3.2新功能实现的程序 (9)3．2.1 浏览功能程序 (9)3.2.2 input按钮功能程序 (10)3.2.3 gridon/off功能程序 (11)双位按钮gridon/off (11)3.2.4 boxon/off功能程序 (11)3.2.5 退出功能程序 (11)3.2.5 保存信号功能程序 (12)第四章遇到的问题和缺陷 (15)4.1 遇到的问题 (15)4.2 缺陷 (16)第五章结束语 (16)第六章致谢 (16)参考文献 (17)第一章概述本频谱分析仪是在网上下的资料的基础上添加自己的内容，完善频谱分析仪，使其功能更强大。
10频谱分析仪设计外文资料翻译
MATLAB的关键特性介绍MATLAB 是一种应用于算法开发、数据显示、数据分析、数值计算方面的高级计算机语言和交互式开发环境。
使用MATLAB软件，你能比例如C、C++, 或者Fortran更快的解决技术上的问题。
你能在很多领域使用MATLAB，例如信号或者图像处理、通讯、控制、测量、金融建模和生物学计算等。
可以通过添加某些收集了特殊用途函数的工具箱来将MATLAB专门用于解决某一应用领域的问题。
MATLAB 为编排和分享你的功能提供了一系列的功能。
你可以将MALAB 代码与其他语言整合，并且区别开算法与应用程序。
关键特性(1)高级的计算语言。
(2)开发环境支持代码、文件、数据的管理。
(3)采用了为重复研究、设计和解决问题的交互式的工具。
(4)为线性代数、统计学、傅立叶分析、滤波器设计、最优化设计、数值综合等设计了相关的数学函数。
(5)为显示数据而准备了2-D 和3-D 图形功能。
(6)有个性化的用户接口工具。
(7)有外部语言（例如C, C++,Fortran, Java, COM,和Microsoft Excel）集成在Matlab中的函数。
开发算法和应用MATLAB 提供了一个高级语言和开发工具，这些允许让你能迅速的开发和分析你的算法和应用。
MATLAB 语言MATLAB 语言支持向量和矩阵，而这些是工程和特殊问题的基本。
它允许快速的开发和执行。
有了MATLAB 语言，你可以比其他传统的语言在编写和开发算法方面更加快速。
因为你不再需要去执行一些低级的操作，例如定义变量、s制定数据类型和分配内存。
在许多例子中，MATLAB 可以不用‘for’语句. 结果是一行MATLAB语句可以替代许多行的 C or C++ 代码.同时，MATLAB 提供传统编程语言的所有特性，包括算法操作、流控制、数据结构、数据类型、面向对象(OOP)和调试特性。
MATLAB 允许你在执行一个命令或者一组命令时不去编译和链接，确保你能够迅速的重试而得到最优的解决方案。
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MATLAB的关键特性介绍
MATLAB 是一种应用于算法开发、数据显示、数据分析、数值计算方面的高级计算机语言和交互式开发环境。
使用MATLAB软件，你能比例如C、C++, 或者Fortran更快的解决技术上的问题。
你能在很多领域使用MATLAB，例如信号或者图像处理、通讯、控制、测量、金融建模和生物学计算等。
可以通过添加某些收集了特殊用途函数的工具箱来将MATLAB专门用于解决某一应用领域的问题。
MATLAB 为编排和分享你的功能提供了一系列的功能。
你可以将MALAB 代码与其他语言整合，并且区别开算法与应用程序。
关键特性
(1)高级的计算语言。
(2)开发环境支持代码、文件、数据的管理。
(3)采用了为重复研究、设计和解决问题的交互式的工具。
(4)为线性代数、统计学、傅立叶分析、滤波器设计、最优化设计、数值综合等设计了相关的数学函数。
(5)为显示数据而准备了2-D 和3-D 图形功能。
(6)有个性化的用户接口工具。
(7)有外部语言（例如C, C++,Fortran, Java, COM,和Microsoft Excel）集成在Matlab中的函数。
开发算法和应用
MATLAB 提供了一个高级语言和开发工具，这些允许让你能迅速的开发和分析你的算法和应用。
MATLAB 语言
MATLAB 语言支持向量和矩阵，而这些是工程和特殊问题的基本。
它允许快速的开发和执行。
有了MATLAB 语言，你可以比其他传统的语言在编写和开发算法方面更
加快速。
因为你不再需要去执行一些低级的操作，例如定义变量、s制定数据类型和分配内存。
在许多例子中，MATLAB 可以不用‘for’语句. 结果是一行MATLAB语句可以替代许多行的 C or C++ 代码.
同时，MATLAB 提供传统编程语言的所有特性，包括算法操作、流控制、数据结构、数据类型、面向对象(OOP)和调试特性。
MATLAB 允许你在执行一个命令或者一组命令时不去编译和链接，确保你能够迅速的重试而得到最优的解决方案。
为了能快速计算大型的矩阵和向量，MATLAB 使用了增强型处理器库。
为了普通的标量计算，MATLAB 使用了即时编辑技术的机器码指令集。
这种在大多数平台上使用的技术提供了可以与传统的编程语言可以媲美的执行速度。
开发工具
MATLAB 包含的开发工具可以帮助你高效的实现你的算法。
这些工具包括：:
MATLAB Editor——提供标准的编辑和调试特点，例如设置断点和单步执行。
M-Lint Code Checker——分析你的代码和推荐的改变方法去改善它的性能和稳定性。
MATLAB Profiler——记录程序在每一行所花的时间。
Directory Reports——在一个文件夹中扫描所有的文件并且报告代码的效率、文件的差异、文件的依赖性和代码的覆盖等。
设计图形化的用户接口
你的可以使用交互式的工具GUIDE (图形化的用户接口开发环境) 去布置、设计和编辑用户接口。
GUIDE 能为你提供列表框、下拉式菜单、按键、收音机式按钮、滚动条和MATLAB plots and ActiveX 控件. 或者，你也可以通过MATLAB 函数用程序的形式创建GUIs。
分析和访问数据
MATLAB 提供整套的数据分析处理，上到从外部设备和数据库通过预处理、形象化或者数值分析所获取数据，下至创造质量的描述。
数据分析
MATLAB提供了交互式的工具和命令行功能用于数据分析操作，其中包括：
(1)内插和抽取。
(2)提取数据段、计算比例、计算平均值。
(3)设定阈值和平滑化。
(4)相关、傅立叶分析、滤波。
(5)找峰值、谷值、过零点。
(6)数据统计和曲线估计。
(7)矩阵分析。
数据访问
作为一个平台，MATLAB 能有效的访问来自文件、其他应用程序、数据库、外部设备的数据。
你能够从一些像Microsoft Excel、ASCII 文本、二进制文件、图像、音频、视频等通常的文件中读取数据，或者也可以从一些科学文件像HDF 和HDF5中读取。
低级的二进制文件IO函数允许你操作任何格式的数据文件。
另一些函数也允许你从Web网页和XML中读取数据。
你可以调用一些像C、C++,、COM objects、DLLs、Java、Fortran、Microsoft Excel、访问FTP 网站和Web 服务的其他程序语言和应用程序。
使用数据库Toolbox™,，你也可以访问来自ODBC/JDBC-compliant 数据库的数据。
你能够从一些像你电脑的串口、声卡这样的硬件中获取数据。
使用数据获取工具箱，你可以将测量的数据流直接送MATLAB ，这样跟便于分析和显示。
仪器控制工具箱能够与GPIB 和VXI 硬件通信。
显示数据
在MATLAB中，提供的所有图表特性都满足工程和科学上的数据对显示的要求。
其中包括2-D和3-D绘图功能、3-D立体绘图函数、交互式绘图函数和导出通用格式的的图形文件的能力。
你可以个性化的设计图形，包括添加多个
坐标轴，改变线的颜色和标记方式，添加注释、LaTEX 等式、长度和绘制形状。
2-D 图形的绘制
你可以使用2-D函数来绘制数据向量。
该2-D函数可以创建：
(1)线、面、柱和饼状图形。
(2)方向和速度图形。
(3)直方图。
(4)多边形和曲面
(5)分散/气泡图
(6)动画。
3-D图形的绘制
MATLAB 为绘制2-D矩阵、3-D标量和3-D向量提供了一些函数。
你可以使用这些函数去显示和理解那些庞大、复杂和多维的数据。
你可以指定一些绘制的特性，例如摄像头的观察角度、远景、照明效果、光源位置和透明度。
3-D 绘制函数包括：
(1)Surface, contour, and mesh
(2)Image plots
(3)Cone, slice, stream, and isosurface
个性化的创建和编辑绘制
MATLAB 为设计和修饰图表提供了交互式的编辑工具。
从一个MATLAB 图形窗口，你可以执行以下的任务：
(1)给图表拖放一个新的数据集合。
(2)改变图中任意对象的性能
(3)缩放、旋转、平移、和改变相机的角度和亮度
(4)添加注释和数字提示
(5)绘制形状
(6)产生一个能给其他数字再次使用的函数
导入和导出图形文件
MATLAB允许你读取和写入一些普通格式的文件，例如GIF、JPEG、BMP、EPS、TIFF、PNG、HDF、A VI,和PCX。
因此，你可以将MATLAB 的绘制图形导出到其他的像Microsoft Word 和Microsoft PowerPoint,或者桌面上其他注册过的应用程序中。
导出以前，你可以创建和应用模版的特性像布局、字体和线的宽度并将这些应用到要公布的应用程序中。
公布结果和应用程序
MATLAB提供一系列的功能用于整理和分享你的工作。
你可以将MATLAB 代码和其他语言的应用程序整合并且把你的MATLAB 算法和应用程序分配为单机程序或者软件模型。
公布结果
MATLAB允许你把结果作为一个图表导出或者将结果完整的导出。
你可以把图表导出成任何通用的格式而其他软件（像Microsoft Word or Microsoft PowerPoint）可以把这个图表导入。
使用MATLAB 编辑器，你的可以把MATLAB 代码在HTML、Word、LaTEX或者其他格式的软件中自动的发布。
在做更多的像仿真运行或者多参数测试的复杂导出功能中，你可以使用MATLAB 导出生成器。
MATLAB 代码与其他语言或者应用程序的混合编程
MATLAB 提供了能把C and C++ 代码、Fortran 代码、COM objects和Java 代码与你的应用集合在一起的功能。
你可以调用DLLs、Java 类和ActiveX 控件等。
使用MATLAB 引擎库，你也可以在C、C++、或者Fortran 代码中调用MATLAB。
配置应用程序
You能在MATLAB中编写算法并把它分配给其他MATLAB 用户直接的使用。
使用MATLAB 编译器，你可以把你的项目中编写的作为一个单机版的
应用程序或者一个软件模型的算法分配给那些没有MATLAB的用户。
另外MATLAB允许你把你的算法转变为一像COM or Microsoft Excel这样的软件可以调用的程序。