UKF sensor fusion method based on principal component analysis
Pages 247 - 251
Abstract
In the process of mobile robot simultaneous localization and map building, to solve the problems, such as the information source of the laser radar navigation system being single and the assigned weight of multi-sensor fusion algorithm being unreasonable, a new UKF multi-sensor data fusion algorithm combined with principal component analysis (PCA) is proposed. In this PCA-UKF algorithm, the PCA based on multivariate statistical theory is used to distribute the weight deduced from the various sensors during navigation and calculate the state estimation after each measurement. Then, the estimated values which close to the real state are integrated into the observations. The experimental results show that the proposed algorithm can effectively improve the navigation accuracy and reliability. Furthermore, it performs better at fault tolerance and environment adaptability.
References
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Hao Gang, Ye Xiu Fen. 2013. Multi-sensor weighted observation fusion adaptive UKF filter. Journal of Astronautics. Vol.32, No.6.
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Hu Gao-ge, Gao She Sheng, Zhao Yan.2014. A new adaptive UKF algorithm and its application in combination navigation. 1005-6734(2014)03-0357-05.
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Liang Li, Ming Yang, Chunxiang Wang, Bing Wang. 2016. Cubature Kalman Filter based point set registration for SLAM. IEEE 19th International Conference on Intelligent Transportation Systems (ITSC).847--852.
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Meng Wu; Jian Yao. 2015. Adaptive UKF-SLAM based on magnetic gradient inversion method for underwater navigation. IEEE Conference Publication. International Conference on Unmanned AircraftSystems, 839--843.
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Index Terms
- UKF sensor fusion method based on principal component analysis
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Published In
November 2017
545 pages
ISBN:9781450353656
DOI:10.1145/3162957
- Conference Chairs:
- Jalel Ben-Othman,
- Feng Gang,
- Program Chairs:
- Jain-Shing Liu,
- Masayuki Arai
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Association for Computing Machinery
New York, NY, United States
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Published: 24 November 2017
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ICCIP 2017
ICCIP 2017: 2017 the 3rd International Conference on Communication and Information Processing
November 24 - 26, 2017
Tokyo, Japan
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Overall Acceptance Rate 61 of 301 submissions, 20%
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