约束总体最小二乘空间配准算法

摘要

Compared to a single radar, radar network can significantly improve the performance of the fusion system. The precision of space registration is generally low with the situation of big random error in radar network. This will lead to a significant decline in the fusion performance. In the case of neglecting model linearization errors, this shortcoming is due to the fact that the coefficient matrix of measurement equation exists errors- This paper presents the constrictive total least squares algorithm based on the Earth-Centered Earth-fixed (ECEF) coordinates, which exploits the correlation among coefficient matrix errors. Simulation results show that the method has higher registration accuracy and faster convergence speed, compared with least squares, generalized least squares algorithm.%相对于单个雷达而言,组网雷达能显著提高其融合系统的性能,但是在随机误差较大情况下,由于空间配准精度往往较低,其融合性能会显著下降.在忽略模型线性化误差的情况下,分析出这一缺点出现的原因是量测方程的系数矩阵中存在误差,进而利用系数矩阵误差存在统计相关性的特点,提出一种基于地心地固坐标系(ECEF)的约束总体最小二乘算法进行空间配准.仿真结果表明该方法比最小二乘、广义最小二乘算法具有更高的配准精度和更快的收敛速度.