| An unscented particle filter for ground maneuvering target tracking |
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| 作者姓名： | GUO Rong-hua QIN Zheng |
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| 作者单位： | Department of Computer Science and Technology，Tsinghua University，Beijing 100084，China |
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| 基金项目： | Project supported by the National Natural Science Foundation of China （No. 60673024） and the National Basic Research Program （973） of China （No. 2004CB719400） |
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| 摘 要： | In this study, an unscented particle filtering method based on an interacting multiple model (IMM) frame for a Markovian switching system is presented. The method integrates the multiple model (MM) filter with an unscented particle filter (UPF) by an interaction step at the beginning. The framework (interaction/mixing, filtering, and combination) is similar to that in a standard IMM filter, but an UPF is adopted in each model. Therefore, the filtering performance and degeneracy phenomenon of particles are improved. The filtering method addresses nonlinear and/or non-Gaussian tracking problems. Simulation results show that the method has better tracking performance compared with the standard IMM-type filter and IMM particle filter.
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| 关 键 词： | 地面跟踪 计算机技术 PF 人工智能 |
| 收稿时间： | 2007-03-26 |
| 修稿时间： | 2007-04-28 |
An unscented particle filter for ground maneuvering target tracking |
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| GUO Rong-hua QIN Zheng.An unscented particle filter for ground maneuvering target tracking[J].Journal of Zhejiang University Science,2007,8(10):1588-1595. |
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| Authors: | Guo Rong-hua Qin Zheng |
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| Institution: | (1) Department of Computer Science and Technology, Tsinghua University, Beijing, 100084, China |
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| Abstract: | In this study, an unscented particle filtering method based on an interacting multiple model (IMM) frame for a Markovian switching system is presented. The method integrates the multiple model (MM) filter with an unscented particle filter (UPF) by an interaction step at the beginning. The framework (interaction/mixing, filtering, and combination) is similar to that in a standard IMM filter, but an UPF is adopted in each model. Therefore, the filtering performance and degeneracy phenomenon of particles are improved. The filtering method addresses nonlinear and/or non-Gaussian tracking problems. Simulation results show that the method has better tracking performance compared with the standard IMM-type filter and IMM particle filter. |
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| Keywords: | Interacting multiple model (IMM) Unscented particle filter (UPF) Ground target tracking Particle filter (PF) |
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