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A new unscented particle filter
Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, 2008We present a new unscented particle filter for dynamic systems that outperforms the general particle filter and the unscented particle filter when the variance of the observation noise is small. Our algorithm uses a bank of unscented Kalman filters to refine the prediction in particle filter.
Pascal Bondon
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An unscented particle filter for ground maneuvering target tracking
Journal of Zhejiang University: Science A, 2007In this note, an unscented filtering method based on an interacting multiple model (IMM) frame for a Markovian switching system is presented. The central idea is to integrate an unscented particle filter (UPF) with IMM estimator. The framework (interaction/mixing, filtering, and combination) is similar to that in a standard IMM filter, but an UPF is ...
Guo, Rong-Hua, Qin, Zheng
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Research on Particle Filter Based on Spherical Unscented Transformation
2008 7th World Congress on Intelligent Control and Automation, 2008In order to improve the particle degeneracy phenomenon of particle filter, a method for particle filtering based on unscented transformation was proposed. The spherical unscented Kalman filter was used to generate the important distribution for particle filter.
Han Chongzhao
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An Improved Unscented Particle Filter Approach for Multi-Sensor Fusion Target Tracking [PDF]
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Unscented Particle Filter Approach for Underwater Target Tracking
International Journal of e-Collaboration, 2021This research aims to find an appropriate approach to improve system accuracy in the Doppler-bearing tracking (DBT) problem for target estimation. The topic of DBT problem is to achieve a target trajectory using bearing and frequency measurements. The difficulty of DBT problem comes from the nonlinearity terms exposed in the measurement equations.
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