UWB/Binocular VO Fusion Algorithm Based on Adaptive Kalman Filter

• Published in: Sensors (Basel, Switzerland) Vol. 19; no. 18; p. 4044
• Main Authors: Zeng, Qingxi, Liu, Dehui, Lv, Chade
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 19.09.2019; MDPI
• Subjects: Accuracy; adaptive kalman filter; Algorithms; Automation; binocular VO; Experiments; Global positioning systems; GPS; Information technology; International conferences; Kalman filters; Laboratories; Localization; Navigation systems; Radio frequency identification; Robots; sensor fusion; Sensors; ultra-wideband (UWB); Unmanned aerial vehicles; Vehicles; Workshops; United States > US; Portugal; China; Japan
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s19184044

Among the existing wireless indoor positioning systems, UWB (ultra-wideband) is one of the most promising solutions. However, the single UWB positioning system is affected by factors such as non-line of sight and multipath, and the navigation accuracy will decrease. In order to make up for the shortcomings of a single UWB positioning system, this paper proposes a scheme based on binocular VO (visual odometer) and UWB sensor fusion. In this paper, the original distance measurement data of UWB and the position information of binocular VO are merged by adaptive Kalman filter, and the structural design of the fusion system and the realization of the fusion algorithm are elaborated. The experimental results show that compared with a single positioning system, the proposed data fusion method can significantly improve the positioning accuracy.