Abstract: This paper proposes a new effective TDOA location algorithm to overcome the disadvantage of the traditional closed-form localization algorithms. The algorithm proposed in this paper firstly obtains the location of the source using unconstrained weighted linear least-squares, and then calibrates the estimator according to the maximum likelihood equation to acquire the final solution for the position coordinates. Computer simulation results show that the mean square position error of new algorithm is smaller than the classic Chan algorithm as the noise variance is high.

Key words: TDOA location, maximum likelihood, calibration

摘要： 针对传统时差定位闭式解法在量测噪声较大情况下定位性能不佳的缺点，提出了一种新的时差定位算法。该算法首先在无约束条件下利用加权最小二乘得到目标的初始位置估计值，然后利用最大似然方程对初始位置估计值进行校正，校正后的位置估计值将更加接近最大似然估计。通过对算法的仿真分析，结果表明在量测噪声较大的情况下，算法的定位均方误差要小于经典的Chan算法。

关键词: 时差定位l, 最大似然, 校正