Wireless sensor indoor positioning based on an improved particle filter algorithm. (February 2020)

• Record Type: Journal Article
• Authors: Feng, Pan; Qin, Danyang; Xu, Guangchao; Guo, Ruolin; Zhao, Min
• Is Part Of: International journal of distributed sensor networks. Volume 16:Number 2(2020)
• Publication Date: 2020-02
• Subjects: Indoor positioning -- particle filter -- wireless sensor -- residual analysis -- non-line-of-sight error; Sensor networks -- Periodicals; Intelligent agents (Computer software) -- Periodicals; Multisensor data fusion -- Periodicals; 681.2
• DOI: 10.1177/1550147720903633
• Languages: English
• ISSNs: 1550-1329

Abstract

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 parameterα is introduced, and the second selection is made according toα, 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.