Wireless sensor indoor positioning based on an improved particle filter algorithm
Autor: | Pan Feng, Danyang Qin, Guangchao Xu, Ruolin Guo, Min Zhao |
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Jazyk: | angličtina |
Rok vydání: | 2020 |
Předmět: | |
Zdroj: | International Journal of Distributed Sensor Networks, Vol 16 (2020) |
Druh dokumentu: | article |
ISSN: | 1550-1477 15501477 |
DOI: | 10.1177/1550147720903633 |
Popis: | Positioning by wireless sensor network is one of its main functions and has been widely used in many fields. However, when signal propagation is hindered, serious errors, non-line-of-sight errors, occur. In order to solve this problem, this article proposes an improved particle filter algorithm, which introduces the idea of residual analysis to improve reliability. The algorithm assigns weights to the particles based on the residuals and selects the appropriate particles. In addition, the non-line-of-sight error parameter α is introduced, and the second selection is made according to α , which considers the influence of non-line-of-sight error. The non-line-of-sight error is greatly reduced after two selections. The simulation is performed under several different non-line-of-sight errors, and results show that the algorithm is superior to Kalman filter and particle filter. |
Databáze: | Directory of Open Access Journals |
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