A Novel Bistatic ISAR Space-Variant Phase Error Compensation and Geometric Correction Method Based on Entropy Minimization

Owing to its superior capabilities in counter-stealth and anti-jamming, bistatic inverse synthetic aperture radar (Bi-ISAR) has garnered significant attention in both military and civilian applications. However, the variability in the bistatic angle of Bi-ISAR will lead to position-dependent defocusing and geometric distortions in the imaging result. To address these problems, a novel Bi-ISAR space-variant phase error compensation and geometric correction method based on entropy minimization is proposed. Firstly, a space-variant signal model for Bi-ISAR is derived in a short coherent processing interval (CPI). Subsequently, an optimization function is established, utilizing image entropy as the cost function. By applying the Broyden–Fletcher–Goldfarb–Shanno algorithm to solve this optimization problem, the focused imaging result and the space-variant factors can be obtained simultaneously. Utilizing the distortion relationship derived from the focused image, a range-dependent correction function is constructed and applied to perform geometric corrections. Additionally, image scaling can also be performed by using the space-variant factors. Simulated data processing results validate the effectiveness of the proposed method.