基于ECEF的广义最小二乘误差配准技术

Generalized Least Squares Registration Algorithm with Earth-Centered Earth-Fixed(ECEF) Coordinate System

雷达组网数据处理首先要进行误差配准,来准确地估计和消除系统误差。传统的误差配准技术多基于球极投影,当雷达之间距离较远时,给配准结果引入一定的误差。基于地球中心坐标系(ECEF),提出了一种广义最小二乘的ECEF-GLS误差配准技术,较好地解决了远距离误差配准问题,误差分析表明,如果忽略模型线性化引入的误差,配准结果达到了CRLB下限。最后,使用仿真数据验证了算法的性能,并和Zhou提出的基于ECEF坐标系的最小二乘ECEF-LS误差配准算法进行了比较。

Registration is a prerequisite process for the data fusion in radar networking system to estimate and correct systematic errors accurately. Some classical registration algorithms are all based on the stereographie projection, which introduce errors to the registration of the long distance sensors. In this work, a generalized least squares registration algorithm （ECEF- GLS） is proposed based on the Earth centered Earth-fixed （ECEF） coordinates. This new approach solves the problem of registration between the long distance sensors, and the covariance of its estimation achieves the Cramer-Rao bound （CRLB） ignoring the errors of the linear model. Simulated data are used to evaluate the performance of the proposed method, and comparisons are made to the geeneralized least squares （ECEF GLS） registration algorithm presented by Zhou.