Robust Imaging of Aerial Targets With Maneuvering Trajectory Based on Multioptimization Strategies Under a Spaceborne SAR/ISAR Hybrid Mode

The aerial targets with maneuvering trajectories can result in severe defocusing in inverse synthetic aperture radar (ISAR) images, while the low signal-to-noise ratio (SNR) from remote observations can also pose challenges to imaging. However, due to the stable motion state of satellites and their higher speeds compared to aerial targets, the accumulation time required for imaging is relatively short. This makes the impact of aerial target trajectory maneuvers on imaging effects relatively minor, providing a significant advantage for robust imaging of aerial targets with maneuvering trajectory under a spaceborne SAR/ISAR hybrid mode. This letter proposes an algorithm for robust imaging of aerial targets with maneuvering trajectory based on multioptimization strategies (OSs) under a spaceborne SAR/ISAR hybrid mode. In this algorithm, robust imaging is divided into two parts: 1) multistep optimal imaging time interval selection method based on OSs (MS-OITI-OSs). Through multiple optimization steps based on the target's aerial trajectory and image information, the method achieves robust selection of the OITI by utilizing an "attitude first, quality later" optimization strategy, reducing computational complexity and increasing imaging success rates; and 2) joint translational motion compensation method based on OSs (JTMC-OSs). Characterizing motion parameters using a polynomial model, the method optimizes the motion parameters using image entropy as the objective function through the Grasshopper optimization algorithm (GOA). During the optimization process, a "high-order first, low-order later" optimization strategy is employed based on the impact of motion parameters on imaging quality to achieve robust translational motion compensation. The proposed algorithm enables robust imaging of aerial targets with maneuvering trajectory based on multi-OSs under a spaceborne SAR/ISAR hybrid mode. Extensive experimental validation confirms the effectiveness and robustness of the proposed method.