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噪声相关下含无序量测的多传感器信息融合估计

Multi-Sensor Information Fusion with OOSM in Case of Correlated Noise
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摘要 多传感器跟踪系统中因通信延迟常会出现无序量测现象,为了提高系统估计精度,采用直接更新法对状态进行更新估计,并针对噪声相关下含无序量测的多传感器系统,提出了矩阵加权最优信息融合状态估计算法,考虑了过程噪声和量测噪声的相关性以及局部估计的误差相关性.仿真计算验证了算法的有效性. In multi-sensor tracking system,Out-Of-Sequence Measurement（OOSM）always occur due to communication delays.The system needs to update the OOSM in order to improve the precision.An optimal information fusion estimation weighted by matrix was presented for multi-sensor information fusion with OOSM,in which correlation between the process noise and measurement noise,local errors were considered.The simulation shows its effectiveness.
作者 张希彬
机构地区 天津科技大学理学院 天津大学电气与自动化工程学院
出处 《天津科技大学学报》 CAS 2010年第6期71-74,共4页 Journal of Tianjin University of Science & Technology
关键词 无序量测 信息融合 线性最小方差 矩阵加权 OOSM information fusion least square weighted by matrix
分类号 O231 [理学—运筹学与控制论]
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参考文献6

  • 1Bar-Shalom Y. Update with out of sequence measurements in tracking:exact solution [J]. The International Society for Optical Engineering,2000,4048:541-556.
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  • 6张希彬,秦超英.相关噪声下多步无序量测状态估计更新算法[J].纯粹数学与应用数学,2008,24(1):174-178. 被引量：3

二级参考文献5

  • 1郭尚来.随机控制[M].北京:清华大学出版社,1997.140-147.
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共引文献2

天津科技大学学报
2010年 第6期

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