Space–Ground Bistatic SA-ISAR Imaging via AIWF-Based Cross-Term-Free Time–Frequency Reconstruction

Space-ground bistatic configurations offer significant potential for anti-stealth and global coverage, overcoming the detection limitations of ground-based bistatic inverse synthetic aperture radar (Bi-ISAR) systems. However, achieving high-resolution Bi-ISAR imaging in this configuration remains challenging due to the complex observation model, particularly involving long dwell times and sparse aperture (SA) scenarios. This article proposes a high-precision imaging and cross-range scaling (CRS) scheme for space-ground Bi-ISAR under short-aperture observations, which employs second-order phase error approximation and formulates Bi-ISAR autofocusing and CRS as sparse time-frequency reconstruction problems within the Centroid Frequency-Chirp Rate (CFCR) domain. Furthermore, an adaptive iterative Wiener filter (AIWF)-based reconstruction algorithm is developed, which employs complex Gaussian and Generalized Double Pareto distributions for prior modeling of the original noise and the noise auto-term, respectively, facilitating Bayesian inference. By exploiting the correlation between cross-terms and signal components, the proposed method adaptively suppresses cross-terms, ensuring high-precision, cross-term-free sparse time-frequency reconstruction. Experimental results demonstrate that the proposed algorithm exhibits strong robustness in low signal-to-noise ratio (SNR) and high missing rate (MR) scenarios, achieving well-focused and high-resolution Bi-ISAR imaging even at an SNR of 0 dB or an MR of 70%.