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A Practical, Robust and Fast Method for Location Localization in Range-Based Systems

为在基于范围的系统的地点本地化的一个实际、柔韧、快的方法

作     者:Huang, Shiping Wu, Zhifeng Misra, Anil 

作者机构:South China Univ Technol State Key Lab Subtrop Bldg Sci Guangzhou 510640 Guangdong Peoples R China China Univ Min & Technol State Key Lab Coal Resources & Safe Min Xuzhou 221116 Peoples R China Guangdong Commun Polytech Sch Informat Guangzhou 510650 Guangdong Peoples R China Univ Kansas Civil Environm & Architectural Engn Lawrence KS 66045 USA 

出 版 物:《SENSORS》 (传感器)

年 卷 期:2017年第17卷第12期

页      面:2869-2869页

核心收录:

学科分类:0710[理学-生物学] 071010[理学-生物化学与分子生物学] 0808[工学-电气工程] 07[理学] 0804[工学-仪器科学与技术] 0703[理学-化学] 

基  金:State Key Lab of Subtropical Building Science South China University of Technology Fundamental Research Funds for the Central Universities Research Fund of The State Key Laboratory of Coal Resources and safe Mining, CUMT [12KF07] 

主  题:location localization indoor localization positioning algorithm Newton's Method 

摘      要:Location localization technology is used in a number of industrial and civil applications. Real time location localization accuracy is highly dependent on the quality of the distance measurements and efficiency of solving the localization equations. In this paper, we provide a novel approach to solve the nonlinear localization equations efficiently and simultaneously eliminate the bad measurement data in range-based systems. A geometric intersection model was developed to narrow the target search area, where Newton s Method and the Direct Search Method are used to search for the unknown position. Not only does the geometric intersection model offer a small bounded search domain for Newton s Method and the Direct Search Method, but also it can self-correct bad measurement data. The Direct Search Method is useful for the coarse localization or small target search domain, while the Newton s Method can be used for accurate localization. For accurate localization, by utilizing the proposed Modified Newton s Method (MNM), challenges of avoiding the local extrema, singularities, and initial value choice are addressed. The applicability and robustness of the developed method has been demonstrated by experiments with an indoor system.

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