An Efficient ISAR Imaging Method for Non-Uniformly Rotating Targets Based on Multiple Geometry-Aided Parameters Estimation

The inverse synthetic aperture radar (ISAR) imaging for non-uniformly rotating target plays an important role in many applications. However, it always faces a serious challenge, i.e., the time-varying Doppler frequency induced by the target complex motions will degrade the quality of ISAR image seriously. Several algorithms based on motion parameter estimation have been proposed in recent years. However, most of them always suffer from the heavy computational burden and considerable propagation errors, which deteriorate the performances of algorithms and limit their practical applications. To tackle this problem, an efficient ISAR imaging algorithm is proposed for non-uniformly rotating targets based on geometry-aided parameters estimation in this paper. After the motion compensation, the ISAR echoes are modeled as the quadratic frequency modulated signal first, then is transformed into time-chirp distribution (TCD) plane and the least square Radon transform (RT) based on TCD (LSRT) to estimate the derivative of chirp rate efficiently is proposed. To improve the estimation performance and robustness, the pre-processing and the weighted least square RT TCD methods are both developed. Similarly, the weighted LSRT based on time-frequency distribution is also proposed to estimate the chirp rate. The proposed multiple geometry-aided method can eliminate the effect of propagation error and reduce the computational complexity simultaneously. The simulated data and real-measured data results are both presented to validate the proposed method.