Multichannel ROI Joint Azimuth Compression Algorithm for InISAR Imaging Under Space-Time Varying Doppler

Three-dimensional (3D) InISAR imaging plays an essential role in ensuring spacecraft reliability. However, spacecraft 3D rotation introduces space-time varying Doppler during imaging, complicating simultaneous image focusing and interferometric phase error mitigation. This paper proposes a multi-channel joint azimuth compression InISAR imaging algorithm based on local region-of-interest (ROI) processing. To tackle decorrelation phase errors, an overall InISAR imaging framework based on multi-channel joint compensation is designed. In this framework, each motion compensation step is performed using consistent parameters across all channels, ensuring strict coherence. Furthermore, to prevent accumulated phase errors, an ROI-based multi-channel joint processing method is proposed. Otsu's thresholding and rectangular coverage optimization are employed for ROI extraction and segmentation, with the resulting sub-images serving as independent signal processing units. For focusing the ROI sub-images, a local fractional Fourier transform (FrFT)-based azimuth compression method is introduced. The technique leverages the Local FrFT to differentially compensate quadratic phase terms and limits computational complexity by exponential decay search. Simulation and electromagnetic computational data demonstrate that the proposed algorithm effectively focuses ISAR images and reduces interferometric phase errors, yielding superior 3D imaging accuracy compared to conventional InISAR imaging methods.