Sub-Nyquist Sampling Jamming Against Chirp-ISAR With CS-D Range Compression

Compressed sensing (CS) for sparse backscattering field recovery from very limited measurements has received increasing attention among the radar imaging community. The chirp (i.e., linear frequency modulated) waveform, benefiting from a large time-bandwidth product, is widely utilized in imaging radars, such as synthetic aperture radars (SARs) and inverse SARs (ISARs). In this paper, the influence of sub-Nyquist sampling jamming on ISAR with chirp waveform is investigated, where the CS-based dechirping (CS-D) algorithm is applied to achieve range compression of the under-sampled jamming signals. The jamming signals, formed by the intercepted radar signals under the sub-Nyquist sampling theorem and scattered by the moving targets, are collected by ISAR to form a (2-D) array and the azimuth compression is done via conventional Fourier transform. The main novelty of this framework is twofold: 1) the CS-D range compression of the under-sampled jamming signals is characterized and 2) the potential of sub-Nyquist sampling jamming is demonstrated against ISAR with the CS-D range compression. Simulated trials and real data of a Yak-42 plane are used to validate the correctness of the analyses and finally, the well-focused false-target images greatly support the effectiveness of the sub-Nyquist sampling jamming idea in the countermeasures of chirp-ISAR with the CS-D range compression.