基于修正模糊理论和D-S证据决策的航迹关联算法

doi:10.16182/j.issn1004731x.joss.17-0425

系统仿真学报 ›› 2019, Vol. 31 ›› Issue (10): 2019-2029.doi: 10.16182/j.issn1004731x.joss.17-0425

基于修正模糊理论和D-S证据决策的航迹关联算法

王志伟^1,3, 胡玉兰¹, 胡树杰¹, 刘炜²

1. 沈阳理工大学信息科学与工程学院,辽宁沈阳 110159;
2. 沈阳理工大学机械工程学院,辽宁沈阳 110159;
3. 国防科技大学电子科学学院,湖南长沙 410073

收稿日期:2017-09-11 修回日期:2018-03-01 出版日期:2019-10-10 发布日期:2019-12-12
作者简介:王志伟(1988-),男,山西吕梁,博士生,研究方向为多源信息融合,计算机视觉等。
基金资助:
国家自然科学基金(61373089,61672360)

Track Synthetic Algorithm based on Modified Fuzzy Theory and D-S Evidence Decision

Wang Zhiwei^1,3, Hu Yulan¹, Hu Shujie¹, Liu Wei²

1. School of Information Science and Engineering, Shenyang Ligong University, Shenyang 110159, China;
2. School of Mechanical Engineering, Shenyang Ligong University, Shenyang 110159, China;
3. School of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, China

Received:2017-09-11 Revised:2018-03-01 Online:2019-10-10 Published:2019-12-12

摘要/Abstract

摘要： 针对模糊推理航迹关联时滤波发散、隶属度函数性能下降、关联门限值确定难、复杂情况下关联效果变差等问题。提出基于修正模糊理论和D-S证据决策的航迹关联算法。算法在衰减记忆扩展卡尔曼滤波的基础上,提出对数似然函数自适应修正隶属度函数不定向畸变的方法,提出带冲突分解和一致聚焦的D-S证据决策的航迹关联方法,仿真结果表明,在高密度航迹条件下,新算法与原算法相比,提高了隶属度函数性能,解决了相关门限值确定难的问题,新的航迹关联算法可使航迹平均关联决策正确率提高5.3%。

关键词: 模糊综合决策, 对数似然函数, 隶属度函数, 关联门限, 冲突分解, D-S证据决策

Abstract: Aiming at the problems existing in fuzzy reasoning track association, such as the filter divergence, the membership performance degradation, the difficulty in determining association threshold value, and the association effect deterioration under complex circumstances, a track association algorithm based on modified fuzzy theory and D-S Evidence Decision is proposed. Based on the attenuated memory extended Kalman filter (AMEKF), a logarithmic likelihood function adaptive correction method is proposed to correct the disorientation of membership function,and a D-S evidence decision-making tracking association algorithm with conflict resolution and consistent focusing is proposed. The simulation results show that comparing with the original algorithm, the new algorithm improves the membership performance and lowers the difficulty in determining the correlation threshold value. This new association algorithm improves the accuracy of track average Association decision by 5.3%.

Key words: fuzzy synthetic decision, logarithm likelihood, membership function, correlation threshold, collision resolution, D-S evidence decision

中图分类号:

TP202

王志伟, 胡玉兰, 胡树杰, 刘炜. 基于修正模糊理论和D-S证据决策的航迹关联算法[J]. 系统仿真学报, 2019, 31(10): 2019-2029.

Wang Zhiwei, Hu Yulan, Hu Shujie, Liu Wei. Track Synthetic Algorithm based on Modified Fuzzy Theory and D-S Evidence Decision[J]. Journal of System Simulation, 2019, 31(10): 2019-2029.

参考文献

[1] 李莉. 衰减记忆扩展卡尔曼滤波在目标跟踪中的应用[J]. 电子测量技术, 2011, 34(2): 36-37.
Li Li.Fading memory extended kalman filtering algorithm for maneuvering target tracking application[J] Electronic Mesurement Tecnology, 2011, 34(2): 36-37.
[2] Barnett J A.Computational methods for a mathematical theory of evidence[C]. Proceedings of 7^th International Joint Conference on Artificial Intelligence (IJCAI-81). Vancouver, B. C. , Canada: Springer, 1981, 2: 868-875.
[3] Smets P.The combination of evidence in the transferable model[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence (S0162-8828), 1990, 12(5): 447-458.
[4] Smets P, Kennes R.The transferable belief model[J]. Artificial Intelligence (S0004-3702), 1994, 66(2): 191-234.
[5] Yen J.Generalizing the Dempster-Shafer theory to fuzzy sets. IEEE Transactions on Systems.Man and Cybernetics (S2168-2216), 1990, 20(3): 559-570.
[6] 孙锐. 基于D-S证据理论的信息融合及在可靠性数据处理中的应用研究[D]. 成都: 电子科技大学, 2011: 17-36.
Sun Rui.Research on D-S Evidence Theory Based Information Fusion And its Application in Reliablility Data Processing[D]. Chengdu: University of Electronic Science and Technology of China, 2011, 17-36.
[7] 何友, 王国宏, 关欣. 信息融合理论及应用[M]. 北京: 电子工业出版社, 2010: 241-242.
He You, Wang Guohong, Guan Xin.Information Fusion Theory With Applications[M]. Beijing: Publishing House of Electronics Industry, 2010: 241-242.
[8] 王峰, 王荫槐, 潘泉, 等. 一种基于航迹类型的传感器关联算法[J]. 火力与控制指挥, 2008, 33(5): 103-109.
Wang Feng, Wang Yinhuai, Pan Quan, et al.An Algorithm of Sensor Management based on Type of Track[J]. Fire Control and Command Control, 2008, 33(5): 103-109.
[9] 范恩, 谢维信, 刘宗香, 等. 传感器组网中基于模糊信息处理的多目标跟踪[J]. 指挥信息系统与技术, 2014, 5(6): 15-21.
Fan En, Xie Weixin, Liu Zongxiang, et al.Multiple Target Tracking in Sensor NetWork Based on fuzzy Information Processing[J]. Command information System and Technology, 2014, 5(6): 15-21.
[10] 何友, 黄晓东. 基于模糊综合决策的航迹关联算法[J]. 海军工程学院学报, 1999, 4: 6.
He You, Huang Xiaodong.Algorithm of the Track Correlation Based on fuzzy Integration Judgement[J]. Journal of Naval Academy of Engineering, 1999, 4: 6.
[11] 刘颢, 陈世友, 汪学东, 等. 一种自适应航迹关联算法[J]. 电子学报, 2013, 41(12): 2417-2418.
Liu Hao, Chen Shiyou, Wang Xuedong, et al.An Adaptive Track Correlation Algorithm[J]. Acta Electronica Sinica, 2013, 41(12): 2417-2418.
[12] Fan X F, Zuo M J.Fault diagnosis of machines based on D-S evidence theory: Part 1. D-S evidence theory and its improvement[J]. Pattern Recognition Letters (S0167-8655), 2006, 27(5): 366-376.
[13] Fan X F, Zuo M J.Fault diagnosis of machines based on D-S evidence theory: Part 2. Application of the improved D-S evidence theory in gearbox fault diagnosis[J]. Pattern Recognition Letters (S0167-8655), 2006, 27(5): 377-385.
[14] 何友, 修建娟, 关欣, 等. 雷达数据处理及应用[M]. 北京: 电子工业出版社, 2013: 44-46.
He You, Xiu Jianjuan, Guan Xin, et al.Radar Data Processing With Applications[M]. Beijing: Publishing House of Electronics Industry, 2013: 44-46.

基于修正模糊理论和D-S证据决策的航迹关联算法

Track Synthetic Algorithm based on Modified Fuzzy Theory and D-S Evidence Decision

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