基于MATLAB实现的fmcw 雷达仿真，功能现多目标的检测，基于fmcw体制进行调制，可以测距测速仿真+使用说明文档.rar

%% parameters. fc = 77e9; c = 3e8; lambda = c/fc; %% % The sweep time can be computed based on the time needed for the signal to % travel the unambiguous maximum range. In general, for an FMCW radar % system, the sweep time should be at least 5 to 6 times the round trip % time. This example uses a factor of 5.5. range_max = 200; tm = 5.5*range2time(range_max,c); %% % The sweep bandwidth can be determined according to the range resolution % and the sweep slope is calculated using both sweep bandwidth and sweep % time. range_res = 1; bw = range2bw(range_res,c); sweep_slope = bw/tm; %% % Because an FMCW signal often occupies a huge bandwidth, setting the % sample rate blindly to twice the bandwidth often stresses the capability % of A/D converter hardware. To address this issue, one can often choose a % lower sample rate. Two things can be considered here: % % # For a complex sampled signal, the sample rate can be set to the same as % the bandwidth. % # FMCW radars estimate the target range using the beat frequency embedded % in the dechirped signal. The maximum beat frequency the radar needs to % detect is the sum of the beat frequency corresponding to the maximum % range and the maximum Doppler frequency. Hence, the sample rate only % needs to be twice the maximum beat frequency. % % In this example, the beat frequency corresponding to the maximum range is % given by fr_max = range2beat(range_max,sweep_slope,c); %% % In addition, the maximum speed of a traveling car is about 230 km/h. % Hence the maximum Doppler shift and the maximum beat frequency can be % computed as v_max = 230*1000/3600; fd_max = speed2dop(2*v_max,lambda); fb_max = fr_max+fd_max; %% % This example adopts a sample rate of the larger of twice the maximum beat % frequency and the bandwidth. fs = max(2*fb_max,bw); %% % The following table summarizes the radar parameters. % % System parameters Value % ---------------------------------- % Operating frequency (GHz) 77 % Maximum target range (m) 200 % Range resolution (m) 1 % Maximum target speed (km/h) 230 % Sweep time (microseconds) 7.33 % Sweep bandwidth (MHz) 150 % Maximum beat frequency (MHz) 27.30 % Sample rate (MHz) 150 %% % With all the information above, one can set up the FMCW waveform used % in the radar system. waveform = phased.FMCWWaveform('SweepTime',tm,'SweepBandwidth',bw,... 'SampleRate',fs); %% % This is a up-sweep linear FMCW signal, often referred to as sawtooth % shape. One can examine the time-frequency plot of the generated signal. sig = waveform(); figure(1) plot(0:1/fs:tm-1/fs,real(sig)); xlabel('Time (s)'); ylabel('Amplitude (v)'); title('FMCW signal'); axis tight; %% Target Model car_dist = 10; car_speed = 40*1000/3600; car_rcs = db2pow(min(10*log10(car_dist)+5,20)); cartarget = phased.RadarTarget('MeanRCS',car_rcs,'PropagationSpeed',c,... 'OperatingFrequency',fc); carmotion = phased.Platform('InitialPosition',[car_dist;0;0.5],... 'Velocity',[car_speed;0;0]); cartarget2 = phased.RadarTarget('MeanRCS',car_rcs,'PropagationSpeed',c,... 'OperatingFrequency',fc); carmotion2 = phased.Platform('InitialPosition',[20;0;0.5],... 'Velocity',[car_speed;0;0]); %% % The propagation model is assumed to be free space. channel = phased.FreeSpace('PropagationSpeed',c,... 'OperatingFrequency',fc,'SampleRate',fs,'TwoWayPropagation',true); %% Radar System Setup ant_aperture = 6.06e-4; % in square meter ant_gain = aperture2gain(ant_aperture,lambda); % in dB tx_ppower = db2pow(5)*1e-3; % in watts tx_gain = 9+ant_gain; % in dB rx_gain = 15+ant_gain; % in dB rx_nf = 4.5; % in dB transmitter = phased.Transmitter('PeakPower',tx_ppower,'Gain',tx_gain); receiver = phased.ReceiverPreamp('Gain',rx_gain,'NoiseFigure',rx_nf,... 'SampleRate',fs); %% % Automotive radars are generally mounted on vehicles, so they are often in % motion. This example assumes the radar is traveling at a speed of 100 % km/h along x-axis. So the target car is approaching the radar at a % relative speed of 4 km/h. radar_speed = 100*1000/3600; radarmotion = phased.Platform('InitialPosition',[0;0;0.5],... 'Velocity',[radar_speed;0;0]); %% Radar Signal Simulation % As briefly mentioned in earlier sections, an FMCW radar measures the % range by examining the beat frequency in the dechirped signal. To extract % this frequency, a dechirp operation is performed by mixing the received % signal with the transmitted signal. After the mixing, the dechirped % signal contains only individual frequency components that correspond to % the target range. % % In addition, even though it is possible to extract the Doppler % information from a single sweep, the Doppler shift is often extracted % among several sweeps because within one pulse, the Doppler frequency is % indistinguishable from the beat frequency. To measure the range and % Doppler, an FMCW radar typically performs the following operations: % % # The waveform generator generates the FMCW signal. % # The transmitter and the antenna amplify the signal and radiate the % signal into space. % # The signal propagates to the target, gets reflected by the target, and % travels back to the radar. % # The receiving antenna collects the signal. % # The received signal is dechirped and saved in a buffer. % # Once a certain number of sweeps fill the buffer, the Fourier transform % is performed in both range and Doppler to extract the beat frequency as % well as the Doppler shift. One can then estimate the range and speed of % the target using these results. Range and Doppler can also be shown as an % image and give an intuitive indication of where the target is in the % range and speed domain. % % The next section simulates the process outlined above. A total of 64 % sweeps are simulated and a range Doppler response is generated at the % end. % % During the simulation, a spectrum analyzer is used to show the spectrum % of each received sweep as well as its dechirped counterpart. specanalyzer = dsp.SpectrumAnalyzer('SampleRate',fs,... 'PlotAsTwoSidedSpectrum',true,... 'Title','Spectrum for received and dechirped signal',... 'ShowLegend',true); %% % Next, run the simulation loop. rng(2012); Nsweep = 64; xr = complex(zeros(waveform.SampleRate*waveform.SweepTime,Nsweep)); %for m = 1:Nsweep while 1 % Update radar and target positions [radar_pos,radar_vel] = radarmotion(waveform.SweepTime); [tgt_pos,tgt_vel] = carmotion(waveform.SweepTime); [tgt_pos2,tgt_vel2] = carmotion2(waveform.SweepTime); % Transmit FMCW waveform sig = waveform(); txsig = transmitter(sig); % Propagate the signal and reflect off the target txsig2 = channel(txsig,radar_pos,tgt_pos2,radar_vel,tgt_vel2); txsig = channel(txsig,radar_pos,tgt_pos,radar_vel,tgt_vel); txsig2 = cartarget2(txsig2); txsig = cartarget(txsig); % Dechirp the received radar return txsig2 = receiver(txsig2); txsig = receiver(txsig); dechirpsig = dechirp(txsig,sig); dechirpsig2 = dechirp(txsig2,sig); figure(2) subplot(211) plot(real(dechirpsig)) subplot(212) plot(real(dechirpsig)) % Visualize the spectrum specanalyzer([dechirpsig dechirpsig2 ]); pause(1) end