CFAR detection of DRFM deception jamming based on singular spectrum analysis
Yunlong Lu, Siyu Li · 2017
For detecting the deception jamming that produced based on a digital radio frequency memory (DRFM) device, a novel jamming detection approach is proposed based on singular spectrum analysis (SSA). Firstly, the phase quantization model of the jamming is built and the spectrum of the quantized jamming is analyzed subsequently. The spectrum analysis result of the quantized jamming shows that the jamming contains a series false terms which differ from the target echo. Then, the singular values energy distribution diversity which caused by the appearance of the false terms between the jamming and the target echo is extracted for jamming detection based on the SSA algorithm. The proposed jamming detection approach has the precious property of a constant false alarm rate (CFAR), and does not need to estimate the noise parameter. The effectiveness of the proposed approach is confirmed through simulations.