低信噪比条件下一种迭代加权拟合的ISAR包络对齐方法

A Range Alignment Method with Iterative Weighted Least Squares Fitting for ISAR Under Low SNR

针对低信噪比条件下传统包络对齐算法性能下降问题,提出基于迭代加权最小二乘拟合的逆合成孔径雷达(ISAR)包络对齐方法(ICWLS:Iterative Cleaning and Weighted Least Squares).该方法利用目标的平稳运动特性,对目标走动量和加权矩阵采用迭代交替更新方式,在估计出目标运动参数的基础上实现包络对齐.仿真结果表明所提方法能有效抑制突跳误差的传播和缓解积累误差所导致的参数估计精度下降问题,具有良好的包络对齐性能.

To deal with the degradation of the conventional range alignment algorithm under low SNR,an ISAR（Inverse Synthetic Aperture Radar） range alignment method is proposed based on iterative weighted least squares fitting.Utilizing the stationary moving characteristic of the target,the proposed method make alternatively iterative update of both the range migration and the weighted matrix,thus realizing the range alignment based on the estimation of the parameters of the target motion.The simulation demonstrates that the proposed method can effectively restrain the transmission of the jump error and relieve the decline of the parameter estimation precision caused by the drift error,which shows a good performance in range alignment.