The interrupted sampling repeater jamming (ISRJ) is considered an efficient deception method of jamming for coherent radar detection. However, current countermeasure methods against ISRJ interference may fail in detecting weak echoes, particularly when the transmitting power of the jammer is relatively high. In this paper, we propose a novel countermeasure scheme against ISRJ based on Bayesian compress sensing (BCS), where stable target signal can be reconstructed over a relatively large range of signal-to-noise ratio (SNR) for both single target and multi-target scenarios. By deriving the ISRJ jamming strategy, only the unjammed discontinuous time segments are extracted to build a sparse target model for the reconstruction algorithm. An efficient alternate iteration is applied to optimize and solve the maximum a posteriori estimate (MAP) of the sparse targets model. Simulation results demonstrate the robustness of the proposed scheme with low SNR or large jammer ratio. Moreover, when compared with traditional FFT or greedy sparsity adaptive matching pursuit algorithm (SAMP), the proposed algorithm significantly improves on the aspects of both the grating lobe level and target detection/false detection probability.

Range ambiguity resolving and deceptive jamming suppression are both challenges for high-resolution wide-swath (HRWS) SAR imagery. With the accommodation of the digital beamforming (DBF) techniques, agile waveforms are of potential to tackle the ambiguity-resolving and anti-jamming tasks simultaneously. In this paper, an algorithm blending agile waveforms and elevation DBF is proposed for wide-swath SAR imagery and adaptive jamming suppression. A shift-stepped Costas DFC (SSC-DFC) waveform is developed with optimal shifted orthogonality. Compared with the orthogonal waveform with smeared ambiguous energy, SSC-DFC can provide precise ambiguity energy position for the spatial filter construction. Meanwhile, cyclic shifts coherence of the agile waveforms minimizes the azimuth ambiguity residual after the Doppler filtering. A serial DBF is designed for adaptive false target extraction and jammer location estimation. The jammer direction notch is only added in the false target area while executing the wide image deblurring. The sub-region DBF avoids the dark strip in the final wide-swath image effectively. Extensive simulation has been presented to verify the practicability of the proposed scheme.

Height detection of a low elevation angle target is crucial in radar applications. Due to the presence of the multiple path reflections, elevation angle estimation is difficult with conventional narrowband radar waveforms. The reflection ground area parameters are especially hard to obtain for modeling. In this paper, we proposed a wideband, low elevation angle estimator based on range super-resolution, achieving a high robustness to variations in reflection coefficients. A relaxation (RELAX) algorithm was applied as the range super-resolution algorithm to separate the direct target echo and the reflected signal thanks to the relatively abundant frequency diversity. The grazing angle was obtained by synthesizing the steering vector of the direct signal and the range structure relationship between the two signal components. Theoretical analysis and simulation results confirmed the improved behavior of the proposed robust estimator in contrast to other conventional algorithms.

Random stepped-frequency chirp waveform (RSFCW) is capable of achieving high-resolution synthetic aperture radar (SAR) imagery as well as certain electronic countermeasure capabilities. The Doppler-dependent phase incoherence due to the platform motion leads to degradation of the frequency synthesis of RSFCW. In this letter, a coherence processing algorithm for RSFCWSAR is developed with full cell Doppler correction (FCDC). The waveform structure of RSFCW is exploited to decompose the signal into different Doppler cells, which paves a way to the FCDC in phase alignment for frequency synthesis. Extensive simulation has confirmed the superiority of our method’s performance in comparison to those of traditional techniques.

Interrupted sampling repeater jamming (ISRJ) is characterized by its coherent processing gains and flexible modulation techniques. ISRJ generates spurious targets along the range, which presents significant challenges to the radar systems. However, existing ISRJ countermeasure methods struggle to eliminate ISRJ signals without compromising the integrity of the real target signal, especially under low-signal-to-noise-ratio (SNR) conditions, resulting in a deteriorated sidelobe and diminished detection performance. We propose a complex-valued encoder–decoder network (CVEDNet) to address these challenges based on signal decomposition. This network offers an end-to-end ISRJ suppression approach, working on complex-valued time-domain signals without the need for additional preprocessing. The encoding and decoding structure suppresses noise components and obtains more compact echo feature representations through layer-by-layer compression and reconstruction. A stacked dual-branch structure and multi-scale dilated convolutions are adopted to further separate the echo signal and ISRJ based on high-dimensional features. A multi-domain combined loss function integrates the waveform and range-pulse-compression information to ensure the amplitude and phase integrity of the reconstructed echo waveform during the training process. The effectiveness of the proposed method was validated in terms of its jamming suppression capability, echo fidelity, and detection performance indicators under low-SNR conditions compared to conventional methods.