求用iwr6843采集的原始数据进行cfar检测的MATLAB程序,进行人体存在感知
时间: 2024-03-05 20:50:36 浏览: 31
以下是一个基于MATLAB的iwr6843 CFAR检测程序示例,用于人体存在感知:
```matlab
% Load raw data from IWR6843
load('iwr6843_data.mat');
% Define parameters
numADCBits = 16; % Number of ADC bits per sample
numRxChannels = 4; % Number of receiver channels
numChirps = 128; % Number of chirps per frame
numFrames = 100; % Number of frames to process
rangeResolution = 0.0433; % Range resolution in meters
rangeWindow = 15; % Range window size for CFAR detection
dopplerWindow = 5; % Doppler window size for CFAR detection
dopplerResolution = 3e-3; % Doppler resolution in meters/second
% Pre-processing of raw data
rawData = double(rawData) - 2^(numADCBits-1);
rawData = reshape(rawData, numRxChannels, numChirps, numFrames);
rawData = permute(rawData, [2 1 3]);
% Perform range FFT
rangeFFT = fft(rawData, [], 1);
% Extract range profile
rangeProfile = abs(rangeFFT).^2;
rangeProfile = sum(rangeProfile, 2);
rangeProfile = squeeze(rangeProfile);
% Perform CFAR detection
rangeProfile = [rangeProfile(end-rangeWindow+1:end); rangeProfile; rangeProfile(1:rangeWindow)];
rangeProfile = conv(rangeProfile, ones(rangeWindow*2+1,1), 'same')/(rangeWindow*2+1);
rangeProfile = rangeProfile(rangeWindow+1:end-rangeWindow);
detectionMap = zeros(size(rangeProfile));
for i = dopplerWindow+1:length(rangeProfile)-dopplerWindow
detectionMap(i) = max(rangeProfile(i-dopplerWindow:i+dopplerWindow));
end
detectionMap = detectionMap(dopplerWindow+1:end-dopplerWindow);
% Plot detection results
figure;
rangeAxis = (0:length(rangeProfile)-1)*rangeResolution;
dopplerAxis = ((1:length(detectionMap))-dopplerWindow-1)*dopplerResolution;
imagesc(dopplerAxis, rangeAxis, detectionMap);
xlabel('Doppler (m/s)');
ylabel('Range (m)');
title('CFAR Detection Map');
```
请注意,这只是一个简单的示例程序,您需要根据您的具体应用场景进行调整和优化。