Radar Signal Modulation and Pulse Compression Techniques with Matched Filter Implementation

This document presents a comprehensive MATLAB implementation of radar signal modulation and pulse compression techniques utilizing matched filters. The matched filter represents a fundamental signal processing technique that significantly enhances radar signal resolution and anti-interference capabilities. Through MATLAB implementation, we demonstrate how applying matched filters to radar signals enables extraction of target details from received signals while effectively distinguishing them from interference components. The implementation includes key algorithms for optimal filter design based on signal autocorrelation properties. Pulse compression technology further improves radar system performance by reducing pulse width to enhance measurement resolution. Our MATLAB code showcases practical implementation of pulse compression algorithms, including linear frequency modulation (LFM) signals and phase-coded waveforms. The program demonstrates critical signal processing functions such as cross-correlation computation, windowing techniques, and signal-to-noise ratio (SNR) optimization. We provide detailed MATLAB examples illustrating signal generation, matched filter design using the freqz and filter functions, and pulse compression implementation through convolution operations. The code includes performance analysis sections that calculate key metrics like range resolution improvement and peak sidelobe levels. These practical examples help users understand fundamental concepts while providing reusable code templates for real-world radar system development.