create an fmcw radar to detect two target using cfar detection algorithm in matlab

To create an FMCW radar system to detect two targets using the Constant False Alarm Rate (CFAR) detection algorithm in MATLAB, you can follow these steps:

1. Generate the FMCW radar signal:

   • Define the parameters for the FMCW radar signal, such as carrier frequency, sweep bandwidth, sweep time, and range resolution.
   • Use the chirp function in MATLAB to generate the FMCW radar waveform.

2. Simulate the radar targets:

   • Define the parameters for the two targets, such as their distances, velocities, and radar cross-sections.
   • Create the simulated received signals from the targets by introducing a delay, Doppler shift, and attenuation to the radar waveform.

3. Perform FMCW signal processing:

   • Mix the received signals with the transmitted signal to obtain the beat frequency.
   • Apply range FFT to obtain the range profile.
   • Apply Doppler FFT to obtain the Doppler profile.

4. Implement the CFAR detection algorithm:

   • Define the window size for local region of interest (ROI).
   • Calculate the noise level in the surrounding area of the ROI.
   • Compare the power of the signal at the ROI with the noise level to determine the presence of a target.
   • Repeat the CFAR detection process for each range and velocity bin.

Here is a high-level code to demonstrate this process:

main.m
% Define FMCW radar parameters
fc = 77e9;              % Carrier frequency
B = 1e9;                % Sweep bandwidth
T = 40e-6;              % Sweep time
Rres = 1;               % Range resolution

% Generate FMCW radar signal
t = 0:1/(B*T):T-1/(B*T); % Time vector
Tx = cos(2*pi * (fc*t + 0.5*B*t.^2 / T)); % Transmit signal
Rx1 = Tx; % Simulated received signal from 1st target
Rx2 = [zeros(1, 100) Tx]; % Simulated received signal from 2nd target

% Perform FMCW signal processing
beat = Rx1.*conj(Tx); % Mixing
rangeProfile = fft(beat); % Range FFT
dopplerProfile = fftshift(fft(rangeProfile, [], 2), 2); % Doppler FFT

% Implement CFAR detection algorithm
windowSize = [8, 4]; % Size of the local ROI
guardSize = [2, 1];  % Size of the surrounding guard region
Pfa = 1e-4;          % False alarm probability
noiseLevel = cfarDetection(rangeProfile, windowSize, guardSize, Pfa); % Calculate noise level

% Perform CFAR detection for each range and velocity bin
targets = [];
for rangeIdx = 1:size(rangeProfile, 2)
    for dopplerIdx = 1:size(dopplerProfile, 1)
        if rangeProfile(dopplerIdx, rangeIdx) > noiseLevel
            targets = [targets; rangeIdx, dopplerIdx]; % Store detected targets
        end
    end
end

% Display detected targets
disp(targets);
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Note: The cfarDetection function should be implemented separately, where you calculate the noise level using the CFAR algorithm based on the given window size, guard size, and false alarm probability.

You can modify the code above based on your specific requirements and test it with different scenarios to detect targets using CFAR detection algorithm in MATLAB.