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提出了一种基于正则约束总体最小二乘(RCTLS)无源测角定位算法.首先将非线性测角定位方程转化为线性方程,根据线性方程系数的一阶泰勒近似得到测角噪声与方程系数噪声之间的线性映射,再基于RCTLS算法得到定位目标函数,对其求偏导并忽略噪声高阶项得到定位结果的近似闭式解,通过对RCTLS算法的偏差和均方差进行分析确定正则化参数.理论分析和仿真实验表明,该算法在观测站数目较少和角度测量噪声较高时与之前的算法相比定位精度有所提高.
A new algorithm based on regular constrained total least square (RCTLS) passive angular location algorithm is proposed.Firstly, the nonlinear angular measurement locating equation is transformed into a linear equation, and according to the first-order Taylor approximation of linear equation coefficient, Noise, and then locate the target function based on the RCTLS algorithm. The partial closed-form solution is obtained by deriving the partial derivative of the noise and neglecting the noise higher-order terms. The regularization is determined by analyzing the deviation and the mean square error of the RCTLS algorithm The theoretical analysis and simulation results show that the proposed algorithm has higher positioning accuracy compared with the previous algorithm when the number of observing stations is small and the angle measuring noise is high.