Globally solving the fractional squared least squares model for GPS localization

IF 1.7 3区数学 Q2 MATHEMATICS, APPLIED

Numerical Algorithms Pub Date : 2024-09-14 DOI:10.1007/s11075-024-01935-4

Xiaoli Cen, Yong Xia

引用次数: 0

Abstract

This study presents a new branch and bound algorithm designed for the global optimization of the fractional squared least squares model for GPS localization. The algorithm incorporates a novel underestimation approach that provides theoretically superior lower bounds while requiring a comparable computational effort to the current approach. Numerical results demonstrate the substantial efficiency enhancements of the proposed algorithm over the existing algorithm.

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全局求解用于 GPS 定位的分数平方最小二乘模型

本研究提出了一种新的分支和约束算法，旨在对用于 GPS 定位的分数平方最小二乘法模型进行全局优化。该算法采用了一种新颖的低估方法，可提供理论上更优越的下限，同时所需的计算量与当前方法相当。数值结果表明，与现有算法相比，拟议算法大大提高了效率。

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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来源期刊

Numerical Algorithms 数学-应用数学

CiteScore

4.00

自引率

9.50%

发文量

201

审稿时长

9 months

期刊介绍： The journal Numerical Algorithms is devoted to numerical algorithms. It publishes original and review papers on all the aspects of numerical algorithms: new algorithms, theoretical results, implementation, numerical stability, complexity, parallel computing, subroutines, and applications. Papers on computer algebra related to obtaining numerical results will also be considered. It is intended to publish only high quality papers containing material not published elsewhere.