综合位置和属性信息的阵群成员观测匹配算法

张昌芳; 杨宏文; 胡卫东; 郁文贤

doi:10.3724/SP.J.1146.2008.01217

综合位置和属性信息的阵群成员观测匹配算法

doi: 10.3724/SP.J.1146.2008.01217

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国家部级基金资助课题

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出版历程
- 收稿日期: 2008-09-25
- 修回日期: 2009-03-23
- 刊出日期: 2009-08-19

A Group Member Matching Algorithm Synthesized Position and Attribute Information

摘要

摘要: 在位置观测噪声幅度较大、传感器识别性能较差或者目标属性不唯一等情况下，单独依靠位置或属性观测难以实现有效的阵群成员匹配。为此，该文提出了一种综合位置和属性信息的阵群成员观测匹配算法。构造了基于位置观测和属性观测的匹配信度函数，定义了一种新的信度组合规则来对上述两类匹配信度进行组合，并提出了一种新的匹配判决思想基于观测序列截断的匹配判决。仿真实验证实了文中算法的有效性。
- 目标识别;匹配信度函数;信度综合;匹配度量;匹配判决
Abstract: It is difficult to get effective group member matching by their position or attribute measurement separately when the sensors position measurement noise level is high and their identification performance is relatively poor or the members types are not exclusive. So a matching algorithm for group members measurement is given which synthesizes their position and attribute information. The matching belief functions related to the position and attribute measurement respectively are constructed which are further combined with a newly defined combination rule. Besides, a new matching decision idea is proposed which is based on the truncation of the measurement sequence. Simulation experiments validate the effectiveness of the proposed algorithm.

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郭磊, 唐斌, 刘刚. 基于辐射源信号特征信息的JPDA 无源跟踪算法[J]. 电子科技大学学报, 2007, 36(1): 27-29.Guo Lei, Tang Bin, and Liu Gang. Passive tracking based onjoin probabilistic data association with signal feature ofemitted source [J]. Journal of University of Electronic Scienceand Technology of China, 2007, 36(1): 27-29.[2]程洪玮, 周一宇, 孙仲康. 多目标跟踪关联中的多特征数据融合方法[J]. 电子学报, 1999, 27(3): 136-139.Cheng Hong-wei, Zhou Yi-yu, and Sun Zhong-kang. Multiplefeature data fusion method in multitarget association andtracking [J]. Acta Electronica Sinica, 1999, 27(3): 136-139.[3]汤亚波, 徐守时. 基于D-S 证据理论的多源遥感图像目标数据联合关联算法[J]. 中国科学技术大学学报, 2006, 36(5):466-471.Tang Ya-bo and Xu Shou-shi. A united data associationalgorithm based on D-S theory and multiple remote sensingimages [J]. Journal of University of Science and Technology ofChina, 2006, 36(5): 466-471.[4]王杰贵, 罗景青. 基于多目标多特征信息融合数据关联的无源跟踪方法[J]. 电子学报, 2004, 32(6): 1013-1016.Wang Jie-gui and Luo Jing-qing. Passive tracking based ondata association with information fusion of multi-feature andmulti-target [J]. Acta Electronica Sinica, 2004, 32(6):1013-1016.[5]王杰贵, 罗景青. 多目标无源跟踪中的多特征模糊综合数据关联算法[J]. 航空学报, 2004, 25(2): 172-175.Wang Jie-gui and Luo Jing-qing. Data association algorithmbased on fuzzy synthetic evaluation of multiple features inmulti-target passive tracking [J]. Acta Aerouautica etAsstonautica Sinica, 2004, 25(2): 172-175.[6]Smets P and Kennes R. The transferable belief model [J].Artificial Intelligence.1994, 66(2):191-234[7]Ristic B and Smets P. Global cost of assignment in the TBMframework for association of uncertain ID reports [J].Aerospace Science and Technology.2007, 11(4):303-309[8]Serban N. Clustering confidence sets [J]. Journal of StatisticalPlanning and Inference (2008), doi: 10.1016/j. jspi. 2007.12.016.

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