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Robust Adaptive Unscented Particle Filter

Robust Adaptive Unscented Particle Filter

Li Xue, Shesheng Gao, Yongmin Zhong
Copyright: © 2013 |Volume: 3 |Issue: 2 |Pages: 12
ISSN: 2156-1664|EISSN: 2156-1656|EISBN13: 9781466632684|DOI: 10.4018/ijimr.2013040104
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MLA

Xue, Li, et al. "Robust Adaptive Unscented Particle Filter." IJIMR vol.3, no.2 2013: pp.55-66. http://doi.org/10.4018/ijimr.2013040104

APA

Xue, L., Gao, S., & Zhong, Y. (2013). Robust Adaptive Unscented Particle Filter. International Journal of Intelligent Mechatronics and Robotics (IJIMR), 3(2), 55-66. http://doi.org/10.4018/ijimr.2013040104

Chicago

Xue, Li, Shesheng Gao, and Yongmin Zhong. "Robust Adaptive Unscented Particle Filter," International Journal of Intelligent Mechatronics and Robotics (IJIMR) 3, no.2: 55-66. http://doi.org/10.4018/ijimr.2013040104

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Abstract

This paper presents a new robust adaptive unscented particle filtering algorithm by adopting the concept of robust adaptive filtering to the unscented particle filter. In order to prevent particles from degeneracy, this algorithm adaptively determines the equivalent weight function according to robust estimation and adaptively adjusts the adaptive factor constructed from predicted residuals to resist the disturbances of singular observations and the kinematic model noise. It also uses the unscented transformation to improve the accuracy of particle filtering, thus providing the reliable state estimation for improving the performance of robust adaptive filtering. Experiments and comparison analysis demonstrate that the proposed filtering algorithm can effectively resist disturbances due to system state noise and observation noise, leading to the improved filtering accuracy.

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