Radar Clutter Simulation for Range-Doppler Map Generation

Radar clutter simulation is a technique used to model clutter signals received by radar systems in complex environments, ultimately generating range-Doppler maps for target detection performance analysis. Below are the core implementation concepts for this process: First, appropriate statistical clutter models must be established, commonly using Rayleigh distribution, Weibull distribution, etc., to describe the random characteristics of ground or sea surface reflections. Based on radar operating frequency and observation scenarios, parametric modeling is employed to simulate clutter echoes of varying intensities. In code implementation, this typically involves generating random sequences with specified statistical properties using functions like raylrnd() or wblrnd() in MATLAB. During the time-domain simulation phase, random sequences with specific power spectrum characteristics need to be generated. This is commonly achieved using linear filtering methods or frequency-domain shaping techniques, where filters are designed to match the Doppler broadening characteristics of clutter. For non-uniform scenarios, block-based modeling approaches may be necessary. Implementation-wise, this involves designing FIR/IIR filters or using frequency-domain multiplication with shaped spectra. The generation of range-Doppler maps involves two key processing steps: range dimension resolution is achieved through pulse compression processing, while Doppler dimension resolution is implemented via FFT processing. Careful attention must be paid to setting appropriate integration times and sampling rates based on radar parameters. In practical code, this typically involves matched filtering for pulse compression and fft() functions for Doppler processing, with proper windowing and zero-padding considerations. Modern simulation systems also consider space-time coupling effects, incorporating array antenna models to simulate spatial filtering characteristics. The final two-dimensional image clearly displays clutter distribution in the range-velocity domain, providing a test benchmark for subsequent moving target detection algorithms. This can be implemented using phased array toolbox functions for antenna pattern modeling and space-time adaptive processing (STAP) techniques. This technology is widely applied in airborne early-warning radar systems and autonomous driving perception systems for anti-interference algorithm validation. By adjusting clutter parameters, radar detection performance under different environmental conditions can be evaluated through parameter sweeps in simulation scripts.