Translational Motion Compensation Method for ISAR Imaging of Air Maneuvering Weak Targets Based on CV-GRUNet

For air maneuvering targets, the higher order components in the translational motion can induce severe range shifts and phase errors. They can deteriorate the performance of translational motion compensation (TMC) in the inverse synthetic aperture radar (ISAR) imaging process. In addition, for weak targets, low signal-to-noise ratio (SNR) can also severely affect the accuracy of TMC. In this letter, a novel TMC method for ISAR imaging of air maneuvering weak targets based on CV-GRUNet is proposed. First, leveraging the noise robustness and capability to handle time series of the gated recurrent unit (GRU), it is extended to the complex domain to construct CV-GRU. CV-GRU can effectively extract the features of range shifts and higher order phase errors. Subsequently, CV-GRUNet is constructed to obtain the compensation function. Finally, TMC can be achieved using the compensation function, resulting in well-focused ISAR images. Compared with existing methods, the proposed method can achieve accurate TMC for ISAR imaging of maneuvering weak targets. The compensation accuracy of the simulated target has reached 1/20 of the wavelength. Simulated and real data results verify the effectiveness and superiority of the proposed method.