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基于模糊逻辑的交互式多模型网络化弹药多节点目标跟踪算法
Fuzzy Logic-based Interacting Multiple Model Algorithm of Networked Munitions for Target Tracking
查看参考文献12篇
文摘
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针对地面网络化弹药系统多节点目标跟踪问题,提出了基于模糊逻辑的交互式多模型(FL-IMM)多节点目标跟踪算法。在多模型交互输出阶段,利用测量误差协方差矩阵的理论值与估计值之间的差值自适应调整测量误差方差;在多节点融合阶段,建立模糊融合系统(FFS)将来自不同节点的目标状态估计数据融合,进而得到网络目标状态估计。通过一个具有3个主探测节点的网络验证了该算法的可行性。实验结果表明,该算法在传感器失效、系统测量误差未知等情况下仍能很好地跟踪机动目标;该算法在地面网络化弹药多节点目标跟踪方面具有较大的实用性。 |
其他语种文摘
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Fuzzy logic-based interacting multiple model (FL-IMM) algorithm in target tracking is proposed for networked munitions. During the interacting stage, the difference value between the theoretical value of covariance matrix and its estimated value is used to adaptively adjust the measured error of the system. In order to fuse multi-nodes data, a FFS (fuzzy-fusion system) is proposed to obtain the target state estimation.The feasibility of the proposed algorithm is verified through a network with 3 detecting nodes. The results show that the algorithm can effectively trace the maneuvering target under the condition of sensor failure and unknown system measurement error, which means that FL-IMM algorithm has great practicability in tracking the targets by the ground networked munition multi-nodes. |
来源
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兵工学报
,2015,36(4):595-601 【核心库】
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DOI
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10.3969/j.issn.1000-1093.2015.04.004
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关键词
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兵器科学与技术
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网络化弹药
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多传感数据融合
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交互式多模型
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模糊逻辑
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目标跟踪
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地址
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北京理工大学机电学院, 北京, 100081
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语种
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中文 |
文献类型
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研究性论文 |
ISSN
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1000-1093 |
学科
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自动化技术、计算机技术 |
基金
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北京理工大学爆炸科学与技术国家重点实验室基金
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文献收藏号
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CSCD:5428586
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参考文献 共
12
共1页
|
1.
任强. 网络中心战初探.
计算机工程与设计,2006,27(3):433-436
|
CSCD被引
3
次
|
|
|
|
2.
Textron Systems.
Next generation ground combat systems,2009
|
CSCD被引
3
次
|
|
|
|
3.
赵玉民.
战场监视地面传感器系统技术与应用,2011
|
CSCD被引
2
次
|
|
|
|
4.
杨万海.
多传感器数据融合及其应用,2006
|
CSCD被引
2
次
|
|
|
|
5.
范洪达.
飞机低空突防航路规划技术研究,2007
|
CSCD被引
2
次
|
|
|
|
6.
Mazor E. Interacting multiple model methods in target tracking:a survey.
IEEE Transactions on Aerospace and Electronic Systems,1998,34(1):103-203
|
CSCD被引
159
次
|
|
|
|
7.
Escamilla-Ambrosio P J. Multi-sensor data fusion architecture based on adaptive Kalman filters and fuzzy logic performance assessment.
Proceedings of the Fifth International Conference on Information Fusion,2002:1542-1549
|
CSCD被引
6
次
|
|
|
|
8.
Lee B J. Fuzzy-logic-based IMM algorithm for tracking a maneuvering target.
IEE Proceedings-Radar Sonar and Navigation,2005,152(1):16-22
|
CSCD被引
6
次
|
|
|
|
9.
Ding Z. Model-set adaptation using a fuzzy Kalman filter.
Mathematical and Computer Modelling,2001,34(7/8):779-812
|
CSCD被引
9
次
|
|
|
|
10.
Ilke T. IMM fuzzy probabilistic data association algorithm for tracking maneuvering target.
Expert System with Applications,2008,34:1243-1249
|
CSCD被引
5
次
|
|
|
|
11.
Mehra R K. On the identification of variances and adoptive kalman filtering.
IEEE Transaction on Automatic Control,1970,15(2):75-184
|
CSCD被引
48
次
|
|
|
|
12.
Mohamed A H. Adaptive Kalman filtering for INS/GPS.
Journal of Geodesy,1999,73(4):193-203
|
CSCD被引
116
次
|
|
|
|
|
|