Detection of Noise Product Amplitude Modulated Slice Repeat Jamming Based on Dual-Dimension Mutations of Statistical Properties and Amplitude

Abstract

Slice repeat jamming is a coherent jamming mode that exhibits deceptive and suppressive characteristics. Accurate detection of such jamming can provide key prior information for subsequent antijamming measures, thus holding notable research value. However, when this jamming adopts noise-product amplitude modulation, the performance of existing jamming detection methods often degrades significantly. To address this issue, this article proposes a noise-product amplitude modulated slice repeat jamming detection method based on dual-dimension mutations of statistical properties and amplitude. First, this method compares and analyzes the power distribution of noise, signal, and jamming segments in radar echo signals. On this basis, by leveraging the mutations in statistical properties at the boundaries between different segments, we design a bidirectional pruned exact linear time changepoint detection algorithm for radar echo power signals, which achieves initial localization of boundary points between segments. Next, combined with the amplitude mutations of jamming in the time-domain, we perform precise corrections on the initially localized boundary points. Finally, jamming segments are identified via adaptive dual-index clustering. Experimental results show that by jointly leveraging statistical properties and amplitude mutations, the proposed method effectively mitigates the degradation of slice repeat jamming detection performance induced by noise-product amplitude modulation, and markedly improves the detection accuracy and reliability of slice repeat jamming.