The interrupted-sampling repeater jamming (ISRJ) is coherent and has the characteristic of suppression and deception to degrade the synthetic aperture radar (SAR) image quality. The anti-ISRJ methods are studied in this work in order to suppress the ISRJ based on the waveform and filter design for SAR. First, the relationship between the ISRJ and waveform is obtained by analyzing the principle of the ISRJ using the ambiguity function. The ISRJ produces multiple false targets based on the high Doppler tolerance of waveform and the characteristic of the matched filter. Next, a method is proposed to counter the ISRJ by transmitting a phase-coded (PC) waveform with low Doppler tolerance and designing the corresponding mismatched filter. The joint design method is then developed to improve the anti-ISRJ and imaging performance. In the proposed methods, the majorization minimization framework is introduced to solve the nonconvex waveform and filter design problem. Finally, several simulations are conducted to demonstrate the effectiveness of the proposed methods. Simulation results show that the joint design method shows better anti-ISRJ and imaging performance in comparison with the separate design method, but it is more sensitive to the ISRJ sampling duty ratio and period.

A joint waveform and filter design method is developed for suppressing radar pulse compression sidelobe level in this paper. The problem is formulated as the minimization of the integrated sidelobe level (ISL) under the constraint of waveform constant modular and filter energy. To control the loss-in-processing gain (LPG), an additional function is introduced to constrain the peak level based on penalty function method. The joint design algorithm is then derived based on the alternating minimization and majorization minimization (MM) schemes. The computation complexity is analyzed and the convergence analysis verifies that the algorithm can converge to a critical point. Specifically, the proposed method is extended to the waveform and filter design for suppressing the peak sidelobe level (PSL). Numerical simulations are carried out to analyze the key parameters, which demonstrate the feasibility of the proposed method. Simulation results show that the ISL and PSL can be significantly reduced with small LPG. Moreover, the proposed method exhibits faster running speed than the existing one and it thus can be applied to longer sequence designs.

Frequency agility increases the difficulty of jammers to predict and estimate the carrier frequency and, thus, improves the radar electronic counter-countermeasures (ECCM) performance. In this article, frequency agility is introduced into synthetic aperture radar (SAR). The characteristic of the Doppler history of frequency-agile SAR (FASAR) is analyzed, which shows that the azimuth compression could not be achieved by the classic imaging algorithms. In order to reconstruct the images of interested targets, a three-channel sparse imaging method is proposed based on approximated observation model by using the echo data of different carrier frequencies. By deriving the equivalent observation model, it is concluded that the reconstruction performance can be enhanced by improving the coherence of match filter imaging results in different channels. The image characteristic of different channels in FASAR is analyzed based on the chirp scaling imaging operator. A phase compensation method is then proposed to improve the coherence of images of interested targets in different channels. Specifically, the SAR mode of random frequency agility is proposed to improve the reconstruction performance. Finally, simulations are carried out to demonstrate the effectiveness of imaging methods and ECCM performance. Theoretical analysis and simulation results demonstrate that images generated in random FASAR have better performance than those in stepped FASAR. By performing the phase compensation, the reconstruction performance of small targets can be significantly improved.

Severe sidelobe interference is one of the major problems with traditional Synthetic Aperture Radar (SAR) imaging. In the observation scene of sea areas, the number of targets in the observation scene is so small that targets can be regarded as sparse. Taking this into account, a method of sidelobe suppression, on the basis of sparsity constraint regularization, is proposed to reduce sidelobes of Gaofen-3 (GF-3) images in sea areas of the image domain. This proposed method has a prominent sidelobe suppression effect with resolution maintenance and without destruction of amplitude and phase information. This method can also be applied to SAR images of other satellites. In addition to the employment of peak sidelobe ratio (PSLR) and integrated sidelobe ratio (ISLR) in evaluating sidelobe suppression level, AE (amplitude error) and PE (phase error) are firstly defined for the evaluation of amplitude and phase-preserving quality, respectively. Through the proposed method, AE and PE values are nearly unchanged and the PSLR and ISLR are significantly reduced. The method, as an important part of the quality-improvement project of GF-3, has been successfully applied to the sidelobe suppression of GF-3 data.

This paper intends to address the long-time coherent integration (LTCI) of high maneuvering targets in low signal-to-noise (SNR) environments with high computational efficiency and accuracy. The high-order motion parameters estimation, considering the acceleration and jerk, is modeled as the under-estimated linear regression and the complex-field Bayesian compressive sensing (BCS) algorithm is introduced to resolve the sparse recovery. To correct the high-order range migration (RM) and reduce the order of Doppler frequency migration (DFM), the adjacent cross correlation (ACCF) is applied. An effective method based on non-coherent integration is proposed to extract the self-term from ACCF result. Further, with the proper design of sensing matrix, the acceleration and jerk motion parameters are estimated by sparse reconstruction based on the complex-field BCS. Compared with the traditional methods based on time-frequency transform, like Lv's distribution (LVD), the proposed BCS algorithm is free from the interference of cross-terms and maintains the super-resolution ability, which provides better performance in parameters estimation and multi-targets discrimination. Finally, the numerical experiments validate the advantages of the proposed method in motion parameters estimation, super-resolution ability and computational efficiency.

The video synthetic aperture radar (ViSAR) is a new application in radar techniques. ViSAR provides high- or moderate-resolution SAR images with a faster frame rate, which permits the detection of the dynamic changes in the interested area. A moving target with moderate velocity can be detected by shadow detection in ViSAR. This paper analyses the frame rate and the shadow feature, discusses the velocity limitation of ViSAR moving target shadow detection and quantitatively gives the expression of velocity limitation. Furthermore, a fast factorized back projection (FFBP) based SAR video formation method and a shadow-based ground moving target detection method are proposed to generate SAR videos and detect the moving target shadow. The experimental results with simulated data prove the validity and feasibility of the proposed quantitative analysis and the proposed methods.