System Error Real-Time Estimation of Radar Network based on Iterative Generalized Least Squares

Jianjuan Xiu, Kai Dong, Meng Wang
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Abstract

Because system error may cause the same target measured by different radar to be misjudged as two targets, the system error estimation is an important process for data fusion and target tracking in radar networking system. In order to eliminate system error in real time, a new algorithm based on iterative generalized least squares (GLS) algorithm in earth-centered earth-fixed (ECEF) coordinate systems(CS) is studied in this paper. In this method the system error is modeled by state vector, and the corresponding state equation is obtained. The measurement equation is modeled based on GLS algorithm, and the iterative estimation filtering model is used to improve the real-time and convergent performance of the system error estimation in ECEF. Simulation results reveal the feasibility and validity of the algorithm presented in this paper.
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基于迭代广义最小二乘的雷达网络系统误差实时估计
由于系统误差可能导致不同雷达测量的同一目标被误判为两个目标,因此系统误差估计是雷达组网系统中数据融合和目标跟踪的重要过程。为了实时消除系统误差,本文研究了一种基于迭代广义最小二乘(GLS)算法的地心定地坐标系(ECEF)定位算法。该方法利用状态向量对系统误差进行建模,得到相应的状态方程。基于GLS算法对测量方程进行建模,采用迭代估计滤波模型提高ECEF系统误差估计的实时性和收敛性。仿真结果表明了该算法的可行性和有效性。
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