Ambiguity Function Analysis of Radar Signals with MATLAB Implementation

This text presents MATLAB code examples for analyzing ambiguity functions of radar signals. The implementation includes Linear Frequency Modulated (LFM) signals using chirp generation functions, LFM pulse train signals with appropriate pulse repetition intervals, and single-frequency signals as baseline references. Through comparative analysis of these different signal types' ambiguity functions, we can observe their distinctive characteristics in terms of range resolution, Doppler tolerance, and sidelobe patterns. The MATLAB code structure typically involves three main components: signal waveform generation using functions like 'chirp' for LFM signals, ambiguity function calculation through 2D correlation processing with Doppler-shifted versions, and visualization using contour or 3D surface plots. For pulse train signals, the implementation includes coherent pulse integration and range-Doppler coupling analysis. Further investigation into the practical implications of different ambiguity functions reveals their significance in applications like target resolution, clutter rejection, and anti-jamming capabilities. In radar signal processing, studying ambiguity functions for various signal types is crucial as it helps better understand and interpret radar signal characteristics and behaviors. The research methodology demonstrated in the code includes parameter optimization for desired ambiguity function shapes and performance comparisons under different signal-to-noise ratios. Therefore, in-depth study of ambiguity functions for different radar signals represents a valuable research direction that can provide important references and guidance for advancing radar signal processing techniques, particularly in modern systems requiring adaptive waveform design and cognitive radar capabilities.