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题名:
Multi-sensor data fusion based on electro-optical tracking system
作者: Zhang Jin; Lu Yu; Wang Wanping; Zhang Yong; Wu Qinzhang
出版日期: 2009
会议名称: Proceedings of SPIE
会议日期: 2009
通讯作者: Zhang Jin
中文摘要: The modern electro-optical (EO) measurement and tracing system usually has different kind of EO sensors that can get measurement of the target at the same time. The traditional tracking system of electro-optical measurement device mainly relies on single sensor that has better precision, and switches to other sensors while tracking is unstable. However, it brings on unstable tracking performance and dramatic decrease of tracking precision while switching among different sensors that have different measurement accuracy. To overcome the disadvantage of the conventional tracking method, a federated Kalman filter algorithm based on multi-sensor fusion of several sensors in EO tracking system is proposed. The local filters deal with the target track from each sensor, then the synthetic target estimation is made according to the sensor fusion of local estimation. Then the wEight factor is assigned to each local filter using the fuzzy logic technique by analyzing the covariance of target estimation. The wEight factor represents the degree of performance of the local estimation and shows the relationship between each sensor. The simulations with Monte Carlo methods show that the proposed algorithm is effective in optoelectronic tracking system especially in the situation of switching among different sensors, and the precision is also superior to the traditional single sensor tracking algorithm.
英文摘要: The modern electro-optical (EO) measurement and tracing system usually has different kind of EO sensors that can get measurement of the target at the same time. The traditional tracking system of electro-optical measurement device mainly relies on single sensor that has better precision, and switches to other sensors while tracking is unstable. However, it brings on unstable tracking performance and dramatic decrease of tracking precision while switching among different sensors that have different measurement accuracy. To overcome the disadvantage of the conventional tracking method, a federated Kalman filter algorithm based on multi-sensor fusion of several sensors in EO tracking system is proposed. The local filters deal with the target track from each sensor, then the synthetic target estimation is made according to the sensor fusion of local estimation. Then the wEight factor is assigned to each local filter using the fuzzy logic technique by analyzing the covariance of target estimation. The wEight factor represents the degree of performance of the local estimation and shows the relationship between each sensor. The simulations with Monte Carlo methods show that the proposed algorithm is effective in optoelectronic tracking system especially in the situation of switching among different sensors, and the precision is also superior to the traditional single sensor tracking algorithm.
收录类别: Ei
语种: 英语
卷号: 7383
文章类型: 会议论文
内容类型: 会议论文
URI标识: http://ir.ioe.ac.cn/handle/181551/7514
Appears in Collections:光电探测技术研究室(三室)_会议论文

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作者单位: 中国科学院光电技术研究所

Recommended Citation:
Zhang Jin,Lu Yu,Wang Wanping,et al. Multi-sensor data fusion based on electro-optical tracking system[C]. 见:Proceedings of SPIE. 2009.
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