Joint Motion Compensation and Distortion Correction for Maneuvering Target Bistatic ISAR Imaging Based on Parametric Minimum Entropy Optimization

Bistatic inverse synthetic aperture radar (Bi-ISAR) can obtain complementary information about moving targets and overcome the inherent imaging limitations of monostatic ISAR. However, the complex motion of maneuvering targets invalidates the assumption that the imaging projection plane (IPP) is constant in conventional Bi-ISAR imaging. The 2-D spatial variant phase errors would be induced. Moreover, the phase errors have a high-order form due to the time-varying bistatic angle and the high maneuvering characteristics of the target. Meanwhile, the linear geometric distortion induced by the bistatic configuration seriously challenges target identification and classification. In this article, we propose a novel method to compensate for the 2-D spatial variant phase errors and correct the geometric distortion simultaneously for Bi-ISAR imaging based on parametric minimum entropy optimization. First, the signal mode for a maneuvering target in the bistatic configuration is developed. Second, based on the developed signal model, we analyze the coupling relationship between the 2-D high-order spatial variant phase errors and the bistatic angle and establish a parametric minimum entropy optimization model for high-order spatial variant phase error compensation. Then, an efficient Broyden-Fletcher-Goldfarb-Shanno (BFGS) method is adopted to obtain the optimal solution of spatial variant coefficients. Finally, with the estimated optimal parameters, the integrated processing of 2-D spatial variant phase error compensation and distortion correction can be realized. This method can simultaneously obtain well-focused and restored Bi-ISAR images of maneuvering targets without selecting prominent scatterers. Experiments based on scattering point simulation data and electromagnetic data verify the effectiveness of the proposed method.