Barrage jamming technique with controllable jamming coverage against synthetic aperture radar (SAR) systems is of great importance in electronic countermeasures. However, it is still a difficulty for the jammer to accurately impose controllable two-dimensional (2-D) local jamming on the regions of interest (ROIs). In this respect, a new parameterized and large-dynamic-range precise controllable (PLDR-PC) jamming method has been proposed in this paper to assist in solving such problems. Based on the SAR imaging properties of linear frequency modulation (LFM) case, the range and azimuth modulation factors have been well designed to generate large dynamic controllable coverage of jamming signals with high 2-D processing gain. In such a context, the PLDR-PC technique can provide the optimal power allocation and considerably reduce the jamming power while still ensuring the satisfactory performance. The proposed PLDR-PC technique can improve the jamming efficiency and considerably reduce the exposure probability of the jammer. Moreover, to improve the barrage jamming performance, the parameter estimation error model is also established to determine the simple yet valid jamming strategy in practical implementations. Finally, extensive numerical simulations in comparison with the current jamming methods have been carried out to demonstrate the effectiveness and prospect of the PLDR-PC technique against airborne/spaceborne SAR systems.

The Doppler shift effect results in some targets shadows in theirs actual position, and a strong correlation exists between adjacent frames of Video Synthetic Aperture Radar (VideoSAR) imagery. Based on the above rationale, a novel approach to moving targets shadow detection for high-frame-rate VideoSAR imagery sequence is presented. First, a fast preprocessing stage is essential in real applications, where the SIFT with RANSAC registration algorithm is employed to compensate for the changing background, and the CattePM model is used to suppress the speckle noise. Then, in order to separate the targets and the background automatically, a threshold segmentation algorithm, called maximizing the Tsallis entropy, is applied. Finally, background difference with three frame difference method implements the precise moving targets extraction. Experimental results utilizing VideoSAR imaging fragment show that multiple moving vehicles are detected effectively and, hence, the validity has been demonstrated.

The processing of synthetic aperture radar (SAR) echoes collected during radar antenna beam steering, such as in the staring spotlight, sliding spotlight, and TOPS operating modes, requires additional efforts due to the limited pulse repetition frequency (PRF). Subaperture processing is mostly used in these cases, but the complexity arising from subaperture dividing and recombination is preferably avoided. The two-step approach (TSA) is an elegant solution to full-aperture processing. Nevertheless, for high-resolution airborne and spaceborne SAR processing, the TSA is still faced with a number of difficulties, which does not occur, however, in subaperture processing. For instance, the high range bandwidth induces Doppler spectrum aliasing during the spectral analysis (SPECAN) stage of the original TSA. Moreover, the Doppler spectrum obtained in TSA, when inverse Fourier transformed back to the slow time domain, might also suffer from aliasing, which precludes the estimation and correction of the unknown residual motion error or tropospheric disturbance. In this article, we extend the TSA to address these problems and present a full-aperture processing framework to precisely focus the high-resolution airborne and spaceborne SAR data. Simulation of X-band spaceborne SAR echoes with transmission signal bandwidth of 3.6 GHz and coherent integration angle of 12.5° has validated the extended TSA (ETSA). Meanwhile, experimental X-band airborne SAR data with the same range and azimuth resolution are also processed using the ETSA, where the conventional autofocusing techniques have been smoothly incorporated.

Video synthetic aperture radar (VideoSAR) imaging mode presents the capability of generating dynamic scenes. In this paper, a postprocessing-based VideoSAR imaging scheme suitable for frequency-domain SAR algorithms is proposed to achieve more flexible application. First, the full-aperture image can be partitioned into the stationary region and a dynamic region of interest (DROI). Then the selected DROI data is segmented at a certain overlapping rate in the azimuth Doppler spectrum. Thus, the unified VideoSAR image coordinate system is achieved, and hence extra image registration technique is avoided. Moreover, VideoSAR can distinguish the relationship between the stationary target and shadow for a more accurate retrieval of height information. Subsequently, a complete procedure of information extraction without geometric prior knowledge, including denoising algorithm, threshold segmentation, matching strategy, and height retrieval is proposed in detail. Based on varying shadows and scattering characteristics in the DROI, multiple experiments using real airborne X-band VideoSAR data validate the feasibility of the proposed imaging scheme and the height retrieval method can achieve a higher accuracy.

Automatic vehicle detection from a video synthetic aperture radar (VideoSAR) system presents significant potential to enhance the surveillance performance in dynamic region of interest (DROI). In this paper, a novel VideoSAR low-rank plus sparse decomposition (LRSD) perspective for single-channel single-pass configuration is proposed to track the ground defocusing vehicles. Vehicle imaging features with 2-D motion parameters are derived theoretically by exploiting a priori knowledge of polar format algorithm (PFA). In accordance with the revealed characteristics, a vision-based VideoSAR-LRSD algorithm, called three-term decomposition (TTD) with proximal exchange-based alternating directions method of multipliers (PEADMM), is then proposed to improve the performance of vehicle detection. It can be used to break the limitation for the application of emergency response not permitting the acquisition of multi-channel or multi-pass data. We comprehensively demonstrate using extensive VideoSAR DROI experiments that in comparison with the state-of-the-art algorithms, TTD-PEADMM algorithm presents the improved accuracy and is able to offer competitive results.

Real-time and high-resolution imaging is demonstrated based on field trial detection of a non-cooperative target using a photonics-based inverse synthetic aperture radar (ISAR). By photonic generation and de-chirping of broadband linear frequency modulation signals, the radar can achieve a high range resolution thanks to the large instantaneous bandwidth (8 GHz at the K band), as well as real-time ISAR imaging using low-speed analog-to-digital conversion (25 MSa/s). A small-size unmanned aerial vehicle is employed as the non-cooperative target, and ISAR imaging is realized with a resolution far better than those achieved by the previously reported photonics-based ISARs. The capability for real-time ISAR imaging is also verified with an imaging frame rate of 25 fps. These results validate that the photonics-based radar is feasible in practical real-time and high-resolution ISAR imaging applications.