UWB positioning algorithm and accuracy evaluation for different indoor scenes. (3rd July 2021)

• Record Type: Journal Article
• Authors: Wang, Jian; Wang, Minmin; Yang, Deng; Liu, Fei; Wen, Zheng
• Is Part Of: International journal of image and data fusion. Volume 12:Number 3(2021)
• Page Start: 203
• Page End: 225
• Publication Date: 2021-07-03
• Subjects: UWB -- indoor positioning -- multiple scenes -- map information -- robust Kalman filter; Image processing -- Periodicals; Multisensor data fusion -- Periodicals; Multisensor data fusion; Periodicals; 621.36705
• DOI: 10.1080/19479832.2020.1864788
• Languages: English
• ISSNs: 1947-9832

Abstract

ABSTRACT: UWB indoor positioning is a research hotspot, but there are few literatures systematically describing different positioning algorithms for different scenes. Therefore, several positioning algorithms are proposed for different indoor scenes. Firstly, for the sensing positioning scenes, a sensing positioning algorithm is proposed. Secondly, for the straight and narrow scenes, a two anchors robust positioning algorithm based on high pass filter is proposed. Experimental results show that this algorithm has better positioning accuracy and robustness than the traditional algorithm. Then, for ordinary indoor scenes, a robust indoor positioning model is proposed based on robust Kalman filter and total LS, which considers the coordinate error of UWB anchors. The positioning accuracy is 0.093m, which is about 29.54% higher than that of the traditional LS algorithm. Finally, for indoor scenes with map information, a map aided indoor positioning algorithm is proposed based on two UWB anchors. This algorithm can effectively improve the reliability and reduce the cost of UWB indoor positioning system, which average positioning accuracy is 0.238m. The biggest innovation of this paper lies in the systematic description of multi-scene positioning algorithm and the realisation of indoor positioning based on double anchors.