Intelligent Interference Waveform Design for Radar Detection Based on the Cross-Correlation Value Function

The subject of this article is a waveform design method of intelligent interference for radar detection. It proposes a cross-correlation value function interrupted sampling repeater jamming (CCVISRJ) algorithm. The mathematical expression of this function and the pulse compression theoretical expression of interference waveforms for frequency-modulated and phase-modulated radar signals are explicitly derived. The effects of nonuniform sampling time, repeated forwarding times, and Doppler modulation frequency on interference waveforms are analyzed, which are optimized by the proposed pulsewidth constrained genetic algorithm. The study then analyzed the influence of CCVISRJ waveform parameters on the interference characteristics through simulations and compared experiments with other interference waveform design methods. The cross-correlation coefficient (CCC) obtained by the algorithm is small, and the reduction correlation characteristics of the target echo signal are effective. When the interference-to-signal ratio is 10 dB, the CCC value can be compressed to less than 10%, so radar detection is invalid. The correctness of the derivation of this cross-correlation theory and the effectiveness of the CCVISRJ algorithm are proved theoretically. Finally, this article presents our analysis of the interference performance of the algorithm by a radar constant false alarm rate (CFAR) detection experiment, which caused the cell-averaging CFAR detection failure and order-statistics CFAR detection probability reduction by 5.36%. The intelligent interference waveform design method presented in this article constructs an interference effectiveness evaluation function, designs the parameter optimization search algorithm, and verifies the method's effectiveness through comparative experiments.