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# 多传感器多目标航迹关联与融合算法研究.doc

UDC注1

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he simulation examples, and proves that the algorithm is effective. Data support for researching subsequent track correlation and track fusion algorithm is provided.
Secondly, based on the practical engineering research background, the distributed correlation algorithms which are currently widespread adoption are summarized and discussed in the dissertation. Include weighting, fixed, independent sequential correlation algorithm, and analyzes when track is crossing, bifurcating and combining, and the feasibility of the algorithm thought the several of simulation examples is proved.
Finally, the dissertation describes several common track fusion algorithms of the target tracking field, including centralized and distributedstructure. Since centralizedstructure has large amount of calculation and the high requirements of system processor, the dissertation adopts the distributed fusion algorithm, and associated successful route, withno feedback optimal distributed fusion algorithm 50 times Monte Carlo simulation to verify the algorithm reliability.
From the Angle of engineering area, the key of target tracking data fusion area is discussed in this dissertation, and useful referencefor the practical engineering application
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is provided.
Keywords：Multi-sensor, target tracking, IMM filtering, trackcorrelation, track fusion
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ABSTRACTII
1绪论1
1.1论文研究背景与意义1
1.2国外发展与研究现状2
1.3 航迹关联与融合算法发展现状3

1.4 本文的主要研究工作与容安排5
2多传感器多目标信息融合理论基础7
2.1信息融合的定义7
2.2信息融合的基本原理7
2.3信息融合的系统结构8

2.4信息融合的技术与应用10

2.5本论文研究的主要问题与解决思路11
2.6本章小结12
3多目标跟踪中的数据处理13
3.1量测数据预处理技术13

3.1.2 时间配准算法16
3.1.3 空间配准算法17
3.2卡尔曼滤波19
3.3交互式多模型跟踪算法20
3.4仿真分析23
3.4.1 仿真指标23
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3.4.2 滤波仿真结果24
3.5本章小结29
4基于统计理论的航迹关联算法31
4.1 算法描述31

4.1.2 修正航迹关联算法32
4.1.3