Affiliation:
1. School of Computer Science & Technology, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
2. Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks, Jiangsu Province, Nanjing 210003, China
Abstract
This paper proposes a method based on AP clustering and an improved particle swarm algorithm for radio frequency identification (RFID) indoor positioning, called the AP-PSO method. Firstly, an AP clustering algorithm is used to cluster the RSSI values of the experimental region tags with similarity, in order to achieve the division of tagged regions, reduce the search area of the later improved particle swarm algorithm, and reduce the search time. Secondly, the learning factor of the particle swarm algorithm is dynamically adjusted, in order to improve the search ability and convergence speed of the global optimal solution of particles. The experimental results show that the algorithm can effectively achieve RFID indoor positioning of the tags to be measured, with high positioning accuracy and with the algorithm spending less time.
Funder
Postgraduate Research and Practice Innovation Program of Jiangsu Province
Subject
Electrical and Electronic Engineering,Instrumentation,Control and Systems Engineering
Cited by
2 articles.
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