RSS Positioning Algorithm Based on Maximum Likelihood Recursive Estimation and CKF. (August 2020)

• Record Type: Journal Article
• Authors: Ning, Xiao; Shuai, Shi
• Is Part Of: Journal of physics. Volume 1617(2020)
• Publication Date: 2020-08
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1617/1/012018
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: In order to improve the positioning accuracy of indoor and dense obstacles, a positioning algorithm based on maximum likelihood recursive estimation and cubature Kalman filter is proposed for the positioning technology based on the received signal strength. The algorithm consists of two steps: initial position estimation and mobile location. Firstly, according to the principle of triangulation, the possible target region of mobile terminal is determined and the region is divided into smaller possible target region step by step. Then, based on the hybrid cooperation of the received signal strength and time of arrival, the nonlinear CKF filter is used to realize the mobile location. Finally, MATLAB is used to simulate the algorithm, and the simulation results show that the proposed method has better positioning performance even in the shadow area.