A low-cost indoor localization system based on received signal strength indicator by modifying trilateration for harsh environments

Haibin Tong, Qingxu Deng, Tianyu Zhang and Yuanguo Bi

International Journal of Distributed Sensor Networks, 2018, vol. 14, issue 6, 1550147718779680

Abstract: Indoor localization systems using received signal strength indicator are very popular for their low power and low complexity, but some drawbacks limit their accuracy, especially in harsh environments, such as multipath and fluctuation. Most existing approaches solve the problem by “fingerprinting.†However, “fingerprinting†based algorithms are unsuitable for changeable environments like construction, since they all demand prior knowledge of the environment. This article studies a novel localization system to achieve an acceptable accuracy position using received signal strength indicator for harsh environments like construction. Based on analysis of the targets’ behavior pattern, we first use curve fitting to filter the distance derived from received signal strength indicator. And then, we propose a distance ratio location algorithm to estimate the targets’ positions. Furthermore, Kalman filter is considered to smooth the position results. This method has been applied in the “Monitoring and Control System for Underground Tunneling Based on Cyber Physical System†Project in Wuhan for tracking workers and vehicles. Practice results show that our system has an acceptable accuracy.

Keywords: Indoor localization; Internet of things; curve fitting; Kalman filter; trilateration (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:14:y:2018:i:6:p:1550147718779680

DOI: 10.1177/1550147718779680

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