Here is my main code, I look the spectograms but I only see a red strip just near to the middle bins, which I assume that it is an object with zero speed.
rFFT = fft(mDopplerAvg.*win, [],1);
rFFT = rFFT – mean(rFFT, 2);
% Obtain range bins that include a target
rangePower = mean(abs(rFFT).^2,2);
% Do not use first few bins as they would probably include DC peaks due
% to antenna leakage (can be adjusted empirically)
rangeVar = var(abs(rFFT), 0, 2);
rangeVar(1:6) = 0;
[~, targetIdx] = max(rangeVar);
slowTime = rFFT(targetIdx,:);
Here, the mDopplerAvg is the raw I/Q matrix that I process for micro-Doppler. I have applied some tricks in order that the static zero speed object (the red strip) go away. However, it didn’t work. At the last of the code, the classic short time Fourier transform is applied along the second axis, and I think the size of the spectogram is well-configurated. I almost always obtain a map just like below.Here is my main code, I look the spectograms but I only see a red strip just near to the middle bins, which I assume that it is an object with zero speed.
rFFT = fft(mDopplerAvg.*win, [],1);
rFFT = rFFT – mean(rFFT, 2);
% Obtain range bins that include a target
rangePower = mean(abs(rFFT).^2,2);
% Do not use first few bins as they would probably include DC peaks due
% to antenna leakage (can be adjusted empirically)
rangeVar = var(abs(rFFT), 0, 2);
rangeVar(1:6) = 0;
[~, targetIdx] = max(rangeVar);
slowTime = rFFT(targetIdx,:);
Here, the mDopplerAvg is the raw I/Q matrix that I process for micro-Doppler. I have applied some tricks in order that the static zero speed object (the red strip) go away. However, it didn’t work. At the last of the code, the classic short time Fourier transform is applied along the second axis, and I think the size of the spectogram is well-configurated. I almost always obtain a map just like below. Here is my main code, I look the spectograms but I only see a red strip just near to the middle bins, which I assume that it is an object with zero speed.
rFFT = fft(mDopplerAvg.*win, [],1);
rFFT = rFFT – mean(rFFT, 2);
% Obtain range bins that include a target
rangePower = mean(abs(rFFT).^2,2);
% Do not use first few bins as they would probably include DC peaks due
% to antenna leakage (can be adjusted empirically)
rangeVar = var(abs(rFFT), 0, 2);
rangeVar(1:6) = 0;
[~, targetIdx] = max(rangeVar);
slowTime = rFFT(targetIdx,:);
Here, the mDopplerAvg is the raw I/Q matrix that I process for micro-Doppler. I have applied some tricks in order that the static zero speed object (the red strip) go away. However, it didn’t work. At the last of the code, the classic short time Fourier transform is applied along the second axis, and I think the size of the spectogram is well-configurated. I almost always obtain a map just like below. i/q, radar, signal processing, filtering MATLAB Answers — New Questions

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