Polar Format Algorithm (PFA) is effective for single-channel high-resolution synthetic aperture radar (SAR) imaging. However, to image for high-resolution and wide swath (HRWS) SAR, the traditional methods for multichannel (MC) SAR require an extra signal reconstruction process. When the signal reconstruction is combined with the PFA, some advantages of PFA, such as simple implementation and high efficiency, cannot be retained. In this paper, a PFA for MC SAR (MC-PFA) is proposed which avoids the extra signal reconstruction by a frequency-band reweighting interpolation (FBRI) proposed in this paper, thus retaining the simplicity and high efficiency of the traditional PFA. In the MC-PFA, the FBRI is combined with the azimuth interpolation in the traditional PFA. Compared to the azimuth interpolation of the traditional PFA, the combined processing can fulfill the range cell migration correction and the signal reconstruction simultaneously without additional interpolation. Furthermore, when the MC-PFA is combined with the Generalized PFA (GPFA), it can be further extended to MC sliding spotlight SAR and MC Terrain Observation by Progressive Scans (TOPS) SAR. Simulation experiments verify the effectiveness of the algorithm proposed in this paper.

This study presents an InSAR flight experiment of the latest mission using helicopter dual-band Synthetic Aperture Radar system (HD-SAR), conducted in southern China by the Xi'an Institute of Space Radio Technology. The HD-SAR system is a dual-band polarization radar based on a helicopter platform, designed for rapid installation and high integration. In every frequency band, the dual receiving channel architecture activates the InSAR mode. High-frequency and low-frequency digital elevation models (DEMs) provide differing benefits depending on the scenario because of the various impacts of ground object scattering qualities. Both high-coherence and low-coherence sectors can achieve optimal performance through the use of dual-band fusion technology. This paper presents the system design and key parameters first. The flying experiments and antenna installation plans for InSAR mode on the Sikorsky S-76 helicopter are described in the section that follows. The results showed that in hilly areas, the relative elevation accuracies of the dual-band fusion DEMs improved by 32% and 25% respectively, whereas the relative elevation accuracies of the C-band and Ku-band DEMs were less than 3 meters. SAR and InSAR mode flight experiments have demonstrated that the HD-SAR system is suitable for most high-resolution detection and interferometry mapping scenarios.

It is important to explore the application of electromagnetic vortex (EMV) wave radar carrying orbital angular momentum in the field of SAR imaging as a new type of radar. Due to the unique Bessel antenna pattern modulation and the vortex azimuth angle phase influence in EMV wave radar, the traditional SAR imaging methods result in a decrease in sidelobe quality, which affects the image quality. To address the aforementioned issues, this paper propose an EMV SAR sidelobe quality improvement imaging method. Accurate geometric and signal model for EMV SAR are established. The Bessel antenna pattern and vortex azimuth angle phase compensation functions are designed. And range block division and pattern modification methods are proposed to address the spatial variation and near zero value issues of Bessel antenna pattern issues respectively. Simulation and image evaluation results verified the effectiveness of the proposed method.

Millimeter-wave radars are widely used in advanced driver assistance systems (ADAS) and autonomous driving. The suppression of mutual interference is challenging for automotive radars to address. The traditional sparse-based methods are effective in interference suppression but have a high computational overhead. However, automotive radars are sensitive to computational overhead. To tackle the problem, this paper proposes a fast convergence method based on the fused Lasso. Taking advantage of the pulse-like shape of the mutual interference in the time domain, a fused Lasso based sparse model is proposed to extract and eliminate the mutual interference. Experiments on simulated and real radar data are conducted to verify the effectiveness of the proposed method, and experiments in dynamic scenarios are conducted. In the two-dimensional range-Doppler (RD) map, the increased signal to interference plus noise ratio (SINR) of the proposed method is about 11.95 dB. In addition, the time cost of the proposed method is much lower than the traditional methods. The robustness of the proposed method is also verified via experiments with different chirp rates and pulse durations.

This paper unrolls some preliminary results of a spaceborne-airborne bistatic SAR experiment, conducted in October, 2020 in Zhejiang, China, using GF-3 SAR satellite as the transmitter. Some important aspects of the experiment are firstly introduced, including bistatic acquisition geometry, receiving system, signal synchronization and theoretical spatial resolution. Then, the imaging processing flow is given, with emphasis on the data synchronization. A modified BP imaging method is proposed, which is suitable for direct signal synchronization scheme commonly used in spaceborne-airborne experiments. Finally, the imaging result is given with evaluation of the spatial resolution.

With the geosynchronous synthetic aperture radar (SAR) satellite as the transmitter, the unmanned aerial vehicle (UAV) can passively receive the echo within the illuminated ground area and achieve 2-D imaging of the interested target. This SAR system, known as GEO-UAV bistatic SAR, is capable of autonomously accomplishing the bistatic SAR mission in rough terrain environments by prespecifying a path for the UAV receiver. In this paper, the GEO-UAV bistatic SAR system is first investigated. The practical advantages and spatial resolution are then analyzed in detail. The spatial resolution of GEO-UAV bistatic SAR is dependent on the observation geometry, which is determined by the UAV path. Therefore, the path planning for GEO-UAV bistatic SAR aims at identifying a set of optimal paths for the UAV receiver to travel through a 3-D terrain environment that simultaneously guarantees the safety of the UAV and achieves SAR imaging with optimized performance during the flight. The path planning is modeled as a constrained multiobjective optimization problem (MOP), which accurately represents the two main aspects for the path planning problem, i.e., UAV navigation and bistatic SAR imaging. Then, a path planning method based on a constrained-adaptive-multiobjective-differential-evolution algorithm is proposed to solve the MOP and generate multiple feasible paths for the UAV receiver with different tradeoffs between navigation for UAV and bistatic SAR imaging performance. The GEO-UAV bistatic SAR mission designer can choose a path from the solution set according to the application requirements, which makes the method more pragmatic.