Management method for multiple sensors' recognizing and tracking multiple targets cooperatively
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摘要:
针对被跟踪的目标中存在虚假目标的问题，首先建立基于风险理论、贝叶斯理论和证据理论的目标识别模型，在此基础上考虑边跟踪边识别的情况，建立同时考虑目标跟踪和识别性能的风险函数模型。在模型求解过程中，提出一种基于多Agent分布计算理论的分布式算法。仿真实验结果表明：目标识别框架下能够对目标有效识别并及时停止对虚假目标跟踪；提出的传感器方案求解算法具有较好的求解质量和较快的求解速度；本文传感器管理方法能够避免传感器资源浪费，提高对真目标的跟踪效果。
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关键词:
- 传感器管理 /
- 目标识别 /
- 目标跟踪 /
- 风险理论 /
- 多Agent分布计算理论
Abstract:Aimed at the problem that there are false targets among targets being tracked, a target recognition model based on risk theory, Bayesian theory and evidence theory is established firstly. Secondly, the situation of target recognition when the target is being tracked is analyzed, and a risk function model in which both target tracking and recognition are considered at the same time is established. When calculating the sensor management, a distributed algorithm based on distributed computing of multi-Agent is proposed. The simulation experiment results show that:First, targets can be recognized effectively and the tracking progress ends in time once a target is recognized as a false target under the framework of target recognition in this paper; Second, the solution of the algorithm proposed in this paper is better and the calculation speed is faster than other algorithms; Third, the sensor management method in this paper can avoid the waste of sensor resources and improve the tracking effect of real targets.
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图 5 传感器s1对目标t1的目标识别过程
Figure 5. Process of target identification of sensor s1 to target t1
图 6 传感器s2对目标t3的目标识别过程
Figure 6. Process of target identification of sensor s2 to target t3
表 1 传感器信息
Table 1. Information of sensors
传感器 pd pf σd2 σα2 Ω/m2 s1 0.8 0.1 10 0.010 30×30 s2 0.9 0.2 20 0.020 30×30 s3 0.8 0.2 15 0.015 30×30 s4 0.7 0.1 30 0.030 20×20 
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表 2 目标信息
Table 2. Information of targets
目标 C 
t1 C(1) (500, 0) 0.5 -300 0 t2 C(1) (0, 500) 0.5 0 -600 t3 C(0) (-500, 0) 0.4 450 0 t4 C(0) (0, -500) 0.5 0 -400
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