Edge computing-enabled green multisource fusion indoor positioning algorithm based on adaptive particle filter

Li, Mengyao; Zhu, R. Y.; Ding, Qianao; Wang, Jun; Wan, Shaohua

doi:10.1007/s10586-022-03682-4

Cited by 2 publications

(1 citation statement)

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“…In [57], a positioning method combining Pedestrian Dead Reckoning (PDR) and RSSI is designed to address the issues of insufficient positioning accuracy and strong interference in single-source positioning. This method takes advantage of the relatively accurate nature of PDR in short-range positioning and uses the fluctuation of Bluetooth RSSI as a judgment criterion to determine whether to perform adaptive particle filtering.…”

Section: Combined With Inertial Sensormentioning

confidence: 99%

Research Progress of Wireless Positioning Methods Based on RSSI

Chen,

Ma,

Zhang

et al. 2024

Electronics

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Location-based services are now playing an integral role in the development of emerging industries, such as the Internet of Things, artificial intelligence and smart cities. Although GPS, Beidou and other satellite positioning technologies are becoming more and more mature, they still have certain limitations. In order to meet the needs of high-precision positioning, wireless positioning is proposed as a supplementary technology to satellite positioning, in which the Received Signal Strength Indication (RSSI) is one of the most popular positioning methods. In this paper, the application scenarios, evaluation methods and related localization methods of wireless positioning based on RSSI are studied. Secondly, the relevant optimization methods are analyzed and compared from different angles, and the methods of RSSI data acquisition are described. Finally, the existing problems and future development trends in RSSI positioning methods are expounded, which has certain reference significance for further research on RSSI localization.

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Section: Combined With Inertial Sensormentioning

confidence: 99%