中文摘要：

提出了改进型约束总体最小二乘多目标定位算法.首先引入辅助变量将非线性定位方程转化为伪线性方程;然后利用两步最小二乘法估计目标的初始位置,依据目标初始位置重新选择参考传感器;最后考虑伪线性方程中所有系数矩阵的噪声,采用拉格朗日乘子技术求解约束条件,利用拟牛顿算法迭代公式得到精确解.仿真结果证明了理论分析的正确性和可行性,所提算法能够达到克拉美罗下界,具有较强的鲁棒性和精确的定位性能.

英文摘要：

An improved constrained total least squares approach was proposed for location of multiple targets. Firstly, the auxiliary variable is introduced to transform the nonlinear positioning equation into pseudo linear equation. Then the initial position of the target was estimated by two-stage weighted least squares, and the reference sensor was re-selected according to the initial estimation position. Finally, considering the noise of all the coefficients in the pseudo-linear equation and applying the Lagrangian multiplier to solve the constraint condition, an exact solution was obtained by using the quasi-Newton iterative formula. Simulations show that the proposed approach can reach the Cramer-Rao lower bound with strong robustness and precise positioning performance.