Millimeter Wave Radar MATLAB Simulation

We employ simulation techniques to model received beat frequency signals and calculate target distance through Fast Fourier Transform (FFT) processing. To compute velocity information alongside distance measurements, we implement an azimuth integration technique that accumulates target positional data. This approach, widely used in radar and measurement systems, enhances measurement precision and accuracy. In MATLAB implementation, the distance calculation typically involves taking FFT of the sampled beat signal, where the peak frequency corresponds directly to target range. The velocity estimation algorithm uses multiple FFT processing across consecutive chirps, analyzing phase changes between measurements to derive Doppler information. Key functions used include fft() for frequency analysis and appropriate windowing functions to reduce spectral leakage. The azimuth integration process involves coherently combining multiple measurements to improve signal-to-noise ratio for accurate velocity extraction.