基于牛顿迭代的非线性定位算法

Jian-Yin Lu, Guirong Fei
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引用次数: 1

摘要

为了提高到达时间差(TDOA)定位的性能,提出了一种非线性最小二乘算法。首先,基于到达时差误差平方和最小的准则,将位置估计表示为非线性规划的最优问题;然后,利用半定规划得到一个初始点。最后,从牛顿迭代得到的局部最优解中提取位置。仿真结果表明,当锚节点数量较大时,随着测量噪声的增加,所提算法的性能将明显优于半确定规划方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Non-Linear Localization Algorithm Based on Newton Iterations
In order to improve the performance of time difference of arrival (TDOA) localization, a nonlinear least squares algorithm is proposed in this paper. Firstly, based on the criterion of the minimized sum of square error of time difference of arrival, the location estimation is expressed as an optimal problem of a non-linear programming. Then, an initial point is obtained using the semi-definite programming. And finally, the location is extracted from the local optimal solution acquired by Newton iterations. Simulation results show that when the number of anchor nodes is large, the performance of the proposed algorithm will be significantly better than that of semi-definite programming approach with the increase of measurement noise.
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