MATLAB Implementation of Ambiguity Function for Radar Linear Frequency Modulated Signals

This MATLAB code provides comprehensive analysis of the ambiguity function for radar Linear Frequency Modulated (LFM) signals. The implementation covers both single pulse and pulse train processing scenarios. Radar Linear Frequency Modulated signals are fundamental signal processing techniques used for measuring target distance, velocity, and direction. In this MATLAB implementation, we demonstrate the generation and processing of radar LFM signals to extract target information. The code utilizes ambiguity function analysis to effectively handle signal noise and interference, thereby enhancing measurement accuracy and reliability. The implementation includes MATLAB functions for generating chirp signals using the chirp() function and computing ambiguity functions through cross-correlation techniques. Single pulse and pulse train represent two common radar signal formats. Single pulses are primarily employed for target range detection, while pulse trains facilitate velocity and direction measurement through Doppler processing. This code demonstrates the processing of both signal types, featuring algorithms for pulse compression using matched filtering and Doppler processing for velocity estimation. The implementation includes techniques for signal generation, windowing functions to reduce sidelobes, and efficient computation of ambiguity surfaces using vectorized operations. The code structure includes modular functions for signal generation, ambiguity function calculation, and visualization of results through contour plots and 3D surfaces. Key MATLAB functions utilized include fft() for Fourier transforms, xcorr() for correlation analysis, and meshgrid() for ambiguity surface computation. This comprehensive implementation provides practical insights into radar signal processing techniques suitable for both educational and research applications. We hope this code proves valuable for your radar signal processing projects!