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Novel passive localization algorithm based on weighted restricted total least square

机译:基于加权约束最小二乘的无源定位新算法

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摘要

A novel multi-observer passive localization algorithm based on the weighted restricted total least square (WRTLS) is proposed to solve the bearings-only localization problem in the presence of observer position errors. Firstly, the unknown matrix perturbation information is utilized to form the WRTLS problem. Then, the corresponding constrained optimization problem is transformed into an unconstrained one, which is a generalized Rayleigh quotient minimization problem. Thus, the solution can be got through the generalized eigenvalue decomposition and requires no initial state guess process. Simulation results indicate that the proposed algorithm can approach the Cramer-Rao lower bound (CRLB), and the localization solution is asymptotically unbiased.
机译:提出了一种基于加权受限最小二乘(WRTLS)的新型多观察者被动定位算法,以解决存在观察者位置误差的纯方位定位问题。首先,利用未知矩阵扰动信息形成WRTLS问题。然后,将相应的约束优化问题转换为无约束问题,这是广义瑞利商最小化问题。因此,该解决方案可以通过广义特征值分解获得,并且不需要初始状态猜测过程。仿真结果表明,该算法可以逼近Cramer-Rao下界(CRLB),并且定位解是渐近无偏的。

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