| 一个用于目标跟踪的改进粒子滤波算法 |
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| 引用本文： | 邓小龙,谢剑英,倪宏伟.一个用于目标跟踪的改进粒子滤波算法[J].中国航空学报,2005,18(2):166-170. |
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| 作者姓名： | 邓小龙 谢剑英 倪宏伟 |
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| 作者单位： | [1]Department of Automation , Shanghai Jiaotong University, Shanghai 200030, China [2]First Research Institute of Corps of Engineers, General Armaments Department, PLA, Wuxi 214035, China |
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| 基金项目： | National Natural Science Foundation of China （50405017） |
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| 摘 要： | 简化UT（unscented transformation）转化参数，修改UKF（unscented Kalmanfilter）提议分布，提出了改进的粒子滤波算法。调节因子的增加使得能在线自适应估计，滤波性能提高，并形成一个自适应的算法。仅有角测量的目标跟踪仿真试验证实了改进的粒子滤波算法要优于其它滤波方式。
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| 关 键 词： | 粒子滤波 仅有角测量跟踪 UKF 提议分布 |
| 文章编号： | 1000-9361（2005）02-0166-05 |
| 收稿时间： | 2004-08-30 |
| 修稿时间： | 2005-01-15 |
Improved Particle Filter for Target Tracking |
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| Deng XiaoLong;Xie JianYing;Ni HongWei.Improved Particle Filter for Target Tracking[J].Chinese Journal of Aeronautics,2005,18(2):166-170. |
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| Authors: | Deng XiaoLong;Xie JianYing;Ni HongWei |
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| Abstract: | A new improved particle filter algorithm with the simplified UT (unscented transformation) and the modified unscented Kalman filter (UKF) proposal distribution is presented. The scaling factor is added to adaptively estimate on line and to improve the filtering performance. An adaptive algorithm is developed. In the bearings-only tracking experiments, the results confirm the improved particle filter algorithm outperforms others. |
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| Keywords: | particle filter bearings-only tracking UKF proposal distribution |
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