Explore MATLAB source code curated for "雷达信号检测" with clean implementations, documentation, and examples.
This archive contains statistical signal processing implementations for Constant False Alarm Rate (CFAR) methods in radar signal detection, featuring original programs with results for both slow-threshold and fast-threshold approaches using cell-averaging and ordered-statistics algorithms
Simulate detection performance across varying SNR levels by generating different target model data under false alarm probability constraints. The radar system employs square law detection followed by non-coherent integration of 10 pulses. Implementation includes generating Swerling 0-IV type target signals with additive white Gaussian noise. Monte Carlo simulations (≥10^5 iterations) are performed for SNR ranging from -10dB to 10dB in 1dB steps, with false alarm probability fixed at 10^-6. Detection probability (Pd) vs SNR curves are plotted to analyze system performance.