一种局部定位测量系统的鲁棒位置估计算法

R. Pfeil, Stefan Dipl.-Ing. Schuster, P. Scherz, A. Stelzer, G. Stelzhammer
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引用次数: 11

摘要

在许多技术问题中,精确的位置估计一直是一个具有挑战性但又要求很高的任务。基于到达时间差(TDOA)的局部位置测量系统LPM采用著名的Bancroft算法,该算法对非线性距离测量方程进行封闭解的计算。这种计算方法的一个关键问题是测量中的异常值会显著降低位置估计的质量。本文提出了一种用于位置估计的最小平方中位数(LMS)算法,即使原始数据包含损坏的测量值,该算法也能提供合适的位置估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A robust position estimation algorithm for a local positioning measurement system
Precise position estimation has always been a challenging but highly requested task in many technical problems. The time-difference of arrival (TDOA) based local position measurement system LPM uses the well-known Bancroft algorithm, which computes a closed-form solution to the non-linear range measurement equations. A critical issue of this computation method is that outliers in the measurements will decrease the quality of the position estimate significantly. In this contribution a least median of squares (LMS) algorithm for position estimation is developed which delivers an appropriate position estimate even if the raw data contain corrupted measurements.
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