| 基于粒子滤波的仅有角测量的被动跟踪 |
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| 引用本文： | 邓小龙,谢剑英,王林. 基于粒子滤波的仅有角测量的被动跟踪[J]. 上海交通大学学报, 2005, 39(6): 993-996 |
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| 作者姓名： | 邓小龙 谢剑英 王林 |
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| 作者单位： | 上海交通大学,自动化系,上海,200030;上海交通大学,自动化系,上海,200030;上海交通大学,自动化系,上海,200030 |
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| 摘 要： | 基于粒子滤波，提出了仅有角测量无源被动跟踪的新解决方法．该方法采用“当前”统计模型，使用粒子滤波算法，融合了双站测量数据．在双站测量的被动跟踪试验中，仿真结果证实了该方法能有效跟踪高度机动的目标．
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| 关 键 词： | 粒子滤波 当前统计模型 被动跟踪 数据融合 |
| 文章编号： | 1006-2467(2005)06-0993-04 |
| 修稿时间： | 2004-06-28 |
Bearings-only Passive Tracking Based on Particle Filter |
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| DENG Xiao-long,XIE Jian-ying,WANG Lin. Bearings-only Passive Tracking Based on Particle Filter[J]. Journal of Shanghai Jiaotong University, 2005, 39(6): 993-996 |
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| Authors: | DENG Xiao-long XIE Jian-ying WANG Lin |
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| Abstract: | Based on a particle filter, a new solution to bearings-only passive tracking was presented. The new method adopts the current statistical model and uses the particle filter algorithm to fuse the data from two observers measurements. In the passive tracking experiments with two observers, the simulation results confirm that the algorithm can (effectively) track the highly maneuvering targets. |
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| Keywords: | particle filter current statistical model passive tracking data fusion |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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