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Precession parameter estimation method of the cone-shaped target based on inverse synthetic aperture radar image sequence analysis

机译:基于逆合成孔径雷达图像序列分析的锥形目标进动参数估计方法

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摘要

The micro-motion features induced by space targets provide effective information for target classification and recognition. This study introduces the equivalent rotational velocity (ERV) estimation for precession parameter estimation of the cone-shaped target with inverse synthetic aperture radar image sequence. On the basis of the rotation matching relationship of precession cone-shaped target, the estimated ERV is used to build an eigenfunction, and the parameter searching set is obtained. Through theoretical analysis, the coupled parameters of the eigenfunction will concentrate on a curve on the searching plane. Thus, the parameter searching set is reduced to the neighbouring area of this curve, which reduces the computational burden greatly. Finally, the parameters are decoupled by the reconstructed radar observation angle, and the precession parameters such as precession period, precession angle, average observation angle, radial length and bottom radius of the target are precisely estimated. The proposed algorithm requires no prior information and it has high computational efficiency. Simulation results with electromagnetic data illustrate the validity of the proposed method.
机译:由空间目标引起的微动特征为目标的分类和识别提供了有效的信息。这项研究介绍了等效旋转速度(ERV)估计,用于具有合成孔径雷达图像序列反演的锥形目标的进动参数估计。根据进动圆锥形目标的旋转匹配关系,利用估计的ERV建立本征函数,得到参数搜索集。通过理论分析,本征函数的耦合参数将集中在搜索平面上的一条曲线上。因此,参数搜索集减少到该曲线的相邻区域,这大大减少了计算负担。最后,通过重建的雷达观测角对参数进行解耦,精确估算目标的进动参数,如进动周期,进动角,平均观测角,径向长度和底半径。该算法不需要先验信息,具有较高的计算效率。电磁数据的仿真结果证明了该方法的有效性。

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