Radar Signal Simulation with Code Implementation Examples

The radar signal simulation codebase implements multiple signal processing techniques through modular MATLAB/Python functions. Core algorithms include digital filtering implementations (FIR/IIR filters using conv() or filtfilt() functions), amplitude/frequency modulation schemes with carrier wave synthesis, and coherent demodulation processes with phase recovery logic. The architecture allows customization through parameterized system objects that simulate various radar types: pulsed radar with pulse-width and PRF controls, continuous-wave radar with Doppler processing chains, and FMCW radar with linear frequency sweep generation and dechirping algorithms. Target modeling incorporates Swerling fluctuation models and RCS calculations through scattering point simulations using phased.BackscatterRadarTarget objects (MATLAB) or equivalent custom classes. The simulation generates realistic echo signals by convolving transmit waveforms with target impulse responses, incorporating path loss and atmospheric attenuation models. Key functions include waveform_generator() for creating customizable pulse structures, signal_processor() implementing matched filtering and CFAR detection algorithms, and environment_model() simulating multipath and clutter effects using statistical distributions. This modular approach enables researchers to validate radar performance metrics like detection probability and range resolution under various scenarios through configurable test benches.