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• W2599682296 abstract "For existing indoor localization algorithm has low accuracy, high cost in deployment and maintenance, lack of robustness, and low sensor utilization, this paper proposes a particle filter algorithm based on multi-sensor fusion. The pedestrian’s localization in indoor environment is described as dynamic system state estimation problem. The algorithm combines the smart mobile terminal with indoor localization, and filters the result of localization with the particle filter. In this paper, a dynamic interval particle filter algorithm based on pedestrian dead reckoning (PDR) information and RSSI localization information have been used to improve the filtering precision and the stability. Moreover, the localization results will be uploaded to the server in time, and the location fingerprint database will be built incrementally, which can adapt the dynamic changes of the indoor environment. Experimental results show that the algorithm based on multi-sensor improves the localization accuracy and robustness compared with the location algorithm based on Wi-Fi." @default.
• W2599682296 created "2017-04-07" @default.
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• W2599682296 date "2017-01-01" @default.
• W2599682296 modified "2023-10-18" @default.
• W2599682296 title "An Indoor Pedestrian Localization Algorithm Based on Multi-Sensor Information Fusion" @default.
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• W2599682296 doi "https://doi.org/10.4236/jcc.2017.53012" @default.
• W2599682296 hasPublicationYear "2017" @default.
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