An Optimal Enhanced Kalman Filter for a ZUPT-Aided Pedestrian Positioning Coupling Model
| Autor: | Pengsong Zhang, Jie Jia, Zhu Yixin, Hai Zhang, Fan Qigao, Zhuang Xiangpeng, Sun Yan |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
pedestrian positioning
attitude fusion filter zero velocity update algorithm OEKF Positioning system Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 02 engineering and technology Pedestrian Environment lcsh:Chemical technology 01 natural sciences Biochemistry Article Analytical Chemistry Indoor positioning system Inertial measurement unit Control theory 0202 electrical engineering electronic engineering information engineering lcsh:TP1-1185 Electrical and Electronic Engineering Instrumentation Inertial navigation system Pedestrians Coupling Electronic Data Processing 010401 analytical chemistry 020206 networking & telecommunications Kalman filter Atomic and Molecular Physics and Optics 0104 chemical sciences Algorithms |
| Zdroj: | Sensors, Vol 18, Iss 5, p 1404 (2018) Sensors (Basel, Switzerland) Sensors; Volume 18; Issue 5; Pages: 1404 |
| ISSN: | 1424-8220 |
| Popis: | Aimed at overcoming the problems of cumulative errors and low positioning accuracy in single Inertial Navigation Systems (INS), an Optimal Enhanced Kalman Filter (OEKF) is proposed in this paper to achieve accurate positioning of pedestrians within an enclosed environment. Firstly, the errors of the inertial sensors are analyzed, modeled, and reconstructed. Secondly, the cumulative errors in attitude and velocity are corrected using the attitude fusion filtering algorithm and Zero Velocity Update algorithm (ZUPT), respectively. Then, the OEKF algorithm is described in detail. Finally, a pedestrian indoor positioning experimental platform is established to verify the performance of the proposed positioning system. Experimental results show that the accuracy of the pedestrian indoor positioning system can reach 0.243 m, giving it a high practical value. |
| Databáze: | OpenAIRE |
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