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http://dx.doi.org/10.6109/jkiice.2012.16.12.2792

Improvement of Multilateration using Vector Prediction Algorithm and Kalman Filter  

Kim, Jung-Ha (한국해양대학교 전기전자공학과 대학원)
Joo, Yang-Ick (한국해양대학교 전기전자공학부)
Lee, Sung-Geun (한국해양대학교 전기전자공학부)
Park, Sang-Gug (위덕대학교 컴퓨터공학과)
Seo, Dong-Hoan (한국해양대학교 전기전자공학부)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.16, no.12, 2012 , pp. 2792-2799 More about this Journal
Abstract
Multilateration that consists of three or more fixed nodes has been widely used in the field of indoor real time location system(RTLS). However, when one or two among fixed nodes are partially out of communication reachability due to obstruction and unstable node, it is difficult to obtain an efficient location information. In order to improve the challenges of poor ranging measurements and fluctuations in these environment, this paper presents, based on TOF(Time of Flight), a new algorithm which can reduce the inherent ranging measurements errors in the conventional multilateration using a vector prediction algorithm for the displacement estimation of mobile node and Kalman filter for an efficient distance average. Even if a person moves with mobile node and then it fails ranging measurement from some of fixed nodes, the proposed algorithm using a present and previous measurement value can predict the distance between mobile node and fixed node which fails ranging measurement. The experimental results are shown that the proposed system improves the localization accuracy and efficiency compared with conventional method, respectively.
Keywords
Multilateration; Kalman filter; Real Time Location System; CSS; SDS-TWR;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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