证据源权重的计算及其在证据融合中的应用

孟光磊; 龚光红

证据源权重的计算及其在证据融合中的应用

孟光磊^,,
龚光红

北京航空航天大学自动化科学与电气工程学院, 北京 100191

基金项目: 总装备部装备预研重点基金资助项目(9140A04040106HT0801)

详细信息

作者简介:
孟光磊(1982-),男,黑龙江齐齐哈尔人,博士生,mengguanglei@gmail.com.

通讯作者:
孟光磊

中图分类号: TP391.9
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出版历程
- 收稿日期: 2009-09-30
- 网络出版日期: 2010-11-30

Weight coefficients calculation for evidence sources and it-s application in evidences fusion

Meng Guanglei^,,
Gong Guanghong

School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China

More Information

Corresponding author: Meng Guanglei

摘要

摘要: 证据融合是提高目标识别准确性的有效方法.为了解决高度冲突证据融合时产生不合理结果的问题,提出了证据源权重的评定原则.引入了证据距离的概念,根据证据源权重的评定原则,提出了证据源权重的计算方法,实现了对各传感器证据的按权相加修正,从而在信息融合之前消除了冲突证据,避免了不合理结果的产生.为了有效利用先验知识,提高目标识别的效率,分两种情况设计了证据融合的方案,并进行了融合复杂性分析.分别对两种证据融合方案进行了仿真试验并进行了比较分析,仿真结果验证了使用证据融合进行目标识别的有效性.
- 传感器网络 /
- 信息融合 /
- 复杂性
Abstract: Evidences fusion is an effective approach for improving target identification. In order to solve the unreasonable results generated by conflictive evidences, the assessment principle for weight coefficients of evidence sources was proposed. The evidence distance concept was introduced and a calculation method for weight coefficients of evidence sources was proposed according to the assessment principle for weight coefficients of evidence sources. Evidences from multiple sensors were modified and added with these weight coefficients. As a result, evidences conflict is dissolved and unreasonable results are avoided. For the purpose of efficiently utilizing the transcendent knowledge and accelerating target identification, two evidence-fusion schemes were designed and the fusion complexation was analyzed. Simulations were carried out to test the two evidence-fusion schemes, and the results verify the validity of the schemes in target identification.
- sensor networks /
- information fusion /
- complexation

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参考文献(1)

[1] Murphy R R.Dempster-Shafer theory for sensor fusion in autonomous mobile robots[J].IEEE Trans on Robotics and Automation,1998,14(2):197-206 [2] 邓勇,朱振福,钟山.基于证据理论的模糊信息融合及其在目标识别中的应用[J].航空学报,2005,26(6),754-758 Deng Yong,Zhu Zhenfu,Zhong Shan.Fuzzy information fusion based on evidence theory and its application in target recognition[J].Acta Aeronautica et Astronautica Sinica,2005,26(6):754-758(in Chinese) [3] 李楠,曲长文,苏峰,等.基于证据组合理论的多传感器目标识别算法[J].弹箭与制导学报,2009,29(2),217-220 Li Nan,Qu Changwen,Su Feng,et al.The algorithm of multi-sensor target identification based on evidence combination theory[J].Journal of Projectiles,Rockets,Missiles and Guidance,2009,29(2):217-220(in Chinese) [4] 柳毅,高晓光,卢广山,等.基于加权证据组合的多传感器目标识别[J].系统工程与电子技术,2003,25(2),1475-1478 Liu Yi,Gao Xiaoguang,Lu Guangshan,et al.Multi-sensor target recognition based on the weighted evidencecombination[J].Systems Engineering and Electronics,2003,25(2):1475-1478 (in Chinese) [5] Haenni R.Comments on about the belief function combination and the conflict management problem[J].Information Fusion,2002(3):149-162 [6] Anne-L J,Dominic G,Eloi B.A new distance between two bodies of evidence[J].Information Fusion,2001(2):91-101 [7] Jian Yonglin,Wen Dongxiao,Lewis F L,et al.Energy-efficient distributed adaptive multi-sensor scheduling for target tracking in wireless sensor networks[J].IEEE Trans on Instrumentation and Measurement,2009,58(6):1886-1896 [8] Waske B,Benediktsson J A.Fusion of support vector machines for classification of multisensor data[J].IEEE Trans on Geoscience and Remote Sensing,2007,45(12):3858-3866 [9] Chanussot J,Mauris G,Lambert P.Fuzzy fusion techniques for linear features detection in multi-temporal SAR images[J].IEEE Trans on Geosci Remote Sensing,1999,37(3):1292-1305 [10] Beynon M,Curry B,Morgan P.The Dempster-Shafer theory of evidence: an alternative approach to multicriteria decision modeling[J].Omega,2000(28):37-50 [11] Chiang H,Moses R L,Potter L C.Model-based classification of radar images[J].Information Theory,2000,46(5):1842-1854 [12] Ma B,Lakshmanan S,Hero A O.Simultaneous detection of lane and pavement boundaries using model-based multisensor fusion[J].IEEE Trans on Intelligent Transportation Systems,2000,1(3):135-147 [13] Zhang Lan,Henry Leung,Chan K.Information fusion based smart home control system and its application[J].IEEE Trans on Consumer Electronics,2008,54(3):1157-1165

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