Evaluating Effect of Blanket Jamming on Radar Via Robust Time-Frequency Analysis and Peak to Average Power Ratio

Evaluating the effect of blanket jamming is at the core of performance analysis and jamming/anti-jamming design for radar. Restricted to diverse jamming types and radar’s applications, it is challenging to put forward a unified framework for quantitative evaluation. To address this issue, we come up with a composite evaluation by combining the robust time-frequency analysis (RTFA) and peak to average power ratio (PAPR). In term of signal-level evaluation, RTFA is exploited to analyze the echoes directly, providing the time-frequency (TF) spectrum for calculating two-dimensional image entropy. For system/application-level evaluation, we derive the variation of signal to jamming ratio (SJR) in radar processing chain, and thus define the PAPR to associate SJR with target detection, a type of common and fundamental application that usually affects the other subsequent ones. To refine composite evaluation, we modify the traditional RTFA by leveraging joint sparse model with convolution framelets to improve TF concentration and to avoid the crossing terms; meanwhile, we derive the quantitative relationship between SJR and detection probability, leading to theoretical guarantee of PAPR for evaluation. Finally, the feasibility and the superiority of the proposed evaluation approach are validated in numerical experiments.