TDOA Positioning Method Based on Taylor Series Expansion Based on Cuckoo Search Algorithm

Yu Chen, Chong Shen, Kun Zhang, Liwen Xu, Xing Huang
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引用次数: 4

Abstract

In order to solve the problems of low accuracy and large computation in traditional locating methods, an uWB locating method based on Taylor series expansion TDOA of cuckoo search algorithm is proposed. It is to substitute the nonlinear equation established by TDOA positioning measurement value into the initial value obtained by cuckoo search algorithm. This method utilizes the powerful maximum value search ability of Cuckoo algorithm to provide initial value for Taylor series expansion algorithm, which solves the problem that Taylor series expansion algorithm is sensitive to initial value and has good convergence characteristics. According to the simulation results, the TDOA positioning algorithm based on The Taylor series expansion of cuckoo search algorithm has a significant improvement in positioning accuracy compared with the common Chan-Taylor algorithm, and can obtain more accurate positioning results without increasing the system hardware cost.
基于杜鹃搜索算法的泰勒级数展开TDOA定位方法
针对传统定位方法精度低、运算量大的问题,提出了一种基于布谷鸟搜索算法泰勒级数展开TDOA的超宽带定位方法。将TDOA定位测量值建立的非线性方程代入布谷鸟搜索算法得到的初始值。该方法利用布谷鸟算法强大的最大值搜索能力为泰勒级数展开算法提供初值,解决了泰勒级数展开算法对初值敏感且收敛性好的问题。仿真结果表明,基于布谷鸟搜索算法的泰勒级数展开的TDOA定位算法与普通的Chan-Taylor算法相比,定位精度有明显提高,并且在不增加系统硬件成本的情况下,可以获得更精确的定位结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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