Abstract
Interrupted sampling repeater jamming (ISRJ) is an attracted coherent jamming method to inverse synthetic aperture radar (ISAR) in the past decades. By means of different jamming parameters settings, realistic dense false targets can be formed around the true target. This paper proposed an adaptive anti-jamming method against ISRJ by adjusting the number of measurements based on compressed sensing (CS). The jamming signal is energy concentrated and segmented sparse in the frequency domain. The measurements number of the reconstructed target signal and the jamming signal is different. According to the restricted isometry property (RIP) condition of CS theory, signal reconstructing performance depends on the number of measurements that varies with the sparsity of the vector. Thus, the jamming signal is suppressed, and the true target signal is retained by altering the measurements number of echo signals. Besides, the two-dimensional (2D) anti-jamming method is derived in detail. The anti-jamming effect is analyzed with different signal-to-noise ratios (SNR), sampling rates, and jam-to-signal ratios (JSR). Simulations prove the effectiveness of the proposed anti-jamming method.
Highlights
With the increasing types and quantities of targets near space, including aircraft, ballistic missiles, decoys, satellites, near space target, and space debris, inverse synthetic aperture radar (ISAR) plays an increasingly important role in target imaging and identification [1,2]
The interrupted sampling repeater jamming (ISRJ) method based on digital radio frequency memory (DRFM) can realize deceiving the victim radar by generating amounts of realistic false targets [3,4]
The ISRJ signal in the azimuth dimension is similar with that in the range dimension that the jamming signal can be generated by interrupted transmitting the radar signal in the slow time domain
Summary
With the increasing types and quantities of targets near space, including aircraft, ballistic missiles, decoys, satellites, near space target, and space debris, inverse synthetic aperture radar (ISAR) plays an increasingly important role in target imaging and identification [1,2]. ISRJ is a novel jamming method against ISAR by interrupting sampling the target echo signal and retransmitting the intercepted segments. According to the variable sparsity influence, the reconstruction effect, a Bayesian compress sensing-based method is proposed to reconstruct the multiple targets signal by optimizing the sparse model in [26]. This model is based on the unjammed discontinuous segments extracted by the ISRJ strategy already. CS theory, this paper proposed an adaptive anti-jamming ming method to suppress the ISRJ signal by adjusting vector sparsity.
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