At present, the majority of deep learning-based ship object detection algorithms concentrate predominantly on enhancing recognition accuracy, often overlooking the complexity of the algorithm. These complex algorithms demand significant computational resources, making them unsuitable for deployment on resource-constrained edge devices, such as airborne and spaceborne platforms, thereby limiting their practicality. With the purpose of alleviating this problem, a lightweight and high-accuracy synthetic aperture radar (SAR) ship image detection network (LHSDNet) is proposed. Initially, GhostHGNetV2 was utilized as the feature extraction network, and the calculation amount of the network was reduced by GhostConv. Next, a lightweight feature fusion network was designed to combine shallow and deep features through lightweight convolutions, effectively preserving more information while minimizing computational requirements. Lastly, the feature extraction module was integrated through parameter sharing, and the detection head was lightweight to save computing resources further. The results from our experiments demonstrate that the proposed LHSDNet model increases mAP50 by 0.7% in comparison to the baseline model. Additionally, it illustrates a pronounced decrease in parameter count, computational demand, and model file size by 48.33%, 51.85%, and 41.26%, respectively, when contrasted with the baseline model. LHSDNet achieves a balance between precision and computing resources, rendering it more appropriate for edge device implementation.

Existing false moving target generation methods face challenges such as uncontrollable position and velocity when against multichannel synthetic aperture radar ground moving target indication (SAR-GMTI) system, as well as significant computational burden in generating dense false targets. Meanwhile, current false blocking image generation methods struggle to create blocking images with controllable position and coverage shape, and the generated images will be partially cancelled against multichannel SAR-GMTI. To tackle these issues, we propose a smart multi-transmitter cooperative false images generation method against multichannel SAR-GMTI and present an accurate and a fast implementation scheme of the method in this paper. The accurate implementation scheme is referred to as the multi-transmitter cooperative frequency-shifting modulation jamming (MTC-FSMJ) method, which can generate false moving targets with controllable radial velocities and initial positions by utilizing multiple transmitters. However, due to the need for iteration calculations in generating a single false target, the computation load of the MTC-FSMJ method becomes substantial when generating dense false moving targets. When we want to generate dense false moving targets, a fast implementation scheme known as the multi-transmitter cooperative template-modulated jamming (MTC-TMJ) method provides an excellent alternative. This approach can quickly generate dense false moving targets within the template without iteration calculations. Moreover, by reasonably designing the template, the MTC-TMJ method can also generate false blocking images with controllable positions, while avoiding partial cancellation. Theoretical analysis and simulation experiments have verified the effectiveness of both implementation structures.

For the special azimuth multi-channel reconstruction processing of high-resolution wide-swath single-input multiple-output synthetic aperture radar (HRWS-SIMO-SAR) to resolve the Doppler ambiguities, this letter studies the imaging characteristics of conventional SAR Doppler-modulation jamming (DMJAM) in HRWS-SIMO-SAR, to provide the theoretical basis for the development of HRWS-SIMO-SAR anti-jamming technology. The theoretical analysis points out that the DMJAM signal will generate equally spaced false targets along the azimuth direction after imaging, and the amplitude of the false targets are decided by the combined sinusoidal function and matched filter loss associated with the Doppler-modulation frequency. The simulation experiments verify the accuracy of the theoretical analysis.

In this article, a fast method for generating false large scenes against SAR based on the cooperative multi-transmitter is proposed. First, we give an improved range frequency-shifting modulation (IRFSM) method utilizing the template Chirp-Z Transform (CZT) in range, which can help the transmitter accomplish the jamming modulation quickly. Then, with the derivation of formulas in azimuthal Doppler domain, an azimuthal convolution and IRFSM jamming (ACIRFSMJ) method built on the two-dimensional CZT (2D-CZT) of the template is proposed. This ACIRFSMJ method can decouple the azimuthal and range directions to reduce the difficulties in the false large-scene signal generation process. The IRFSM ensures that the transmitter can quickly modulate the intercepted signal, while the azimuthal convolution modulation (ACM) expands the coverage width of the false scene generated by a single transmitter in azimuth and avoids the distortion caused by ghosting and high sidelobes. However, when only using a single transmitter to generate false scenes, the azimuthal coverage width is still limited, and the jamming signal of most false scattering points are incomplete. Therefore, this article further proposes using multiple transmitters distributed along the azimuthal direction to address the shortcomings of a single transmitter. Theoretical analysis and experimental simulations verify the effectiveness of the proposed method.

Traditional synthetic aperture radar (SAR) deceptive jamming can effectively generate deceptive scenes or false targets in SAR images. However, these false targets or scenes can be easily distinguished or eliminated by the multichannel SAR system. To interfere with the multichannel SAR, we first analyzed the results of SAR deceptive jamming generated by one transponder and two transponders against three-channel SAR- ground moving target indication (GMTI). Then, we propose a new deceptive jamming method against three-channel SAR-GMTI by using three synergetic transponders. By modulating each transponder with a complex coefficient, three synergetic transponders can generate false moving targets with the controllable radial velocity and located azimuth position in three-channel SAR-GMTI. Besides, in this paper, we also introduce an algorithm to deploy three transponders reasonably by utilizing the minimum condition number. In the end, a general architecture of multiple transponders deceiving multichannel SAR is given. The proposed method can not only generate deceptive false targets against multichannel SAR-GMTI, but also guide the production of a deceptive digital elevation model (DEM) against multichannel interferometric SAR (InSAR). Simulations verify the effectiveness of the proposed method.

The interferometry synthetic aperture radar (InSAR) deceptive jamming method utilizing two synergetic transponders can generate a false three-dimension (3D) scene in a single baseline InSAR image. However, such deceptive capability could be reduced by the multibaseline InSAR system. To obtain effective deception on multibaseline InSAR, a novel deceptive scene generation method jointly employing multiple transponders is proposed. It only demands that each transponder is modulated with a complex coefficient when generating a false point. The complex modulation coefficient can be offline calculated according to the deceptive point coordinate by solving a matrix. Besides, the complex modulation coefficient can be combined with the deceptive scene template, and thus a large 3D deceptive scene is able to be created quickly in the multibaseline InSAR image by using the fast two-dimension (2D) SAR deceptive scene generation algorithm. As long as the number of transponders is not less than the number of antennas of the multibaseline InSAR system, this proposed method is effective. The effectiveness of the proposed method is validated by computer simulations.