多传感器多目标系统误差融合估计算法

宋强; 熊伟; 何友

多传感器多目标系统误差融合估计算法

宋强¹,
熊伟²,
何友²

1.
海军装备研究院, 北京 100036
2. 海军航空工程学院, 信息融合技术研究所, 烟台 264001

基金项目: 国家自然科学基金资助项目(60801049); 全国优秀博士学位论文作者专项资金资助项目(200443)

详细信息

中图分类号: TP953;TN957
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出版历程
- 收稿日期: 2011-05-06
- 网络出版日期: 2012-06-30

Multi-sensor multi-target systematic bias fusion estimation algorithm

1.
Naval Academy of Armament, Beijing 100036, China
2. Research Institute of Information Fusion, Naval Aeronautical and Astronautical University, Yantai 264001, China

摘要

摘要: 为解决多传感器组网系统的系统误差估计问题,基于多传感器多目标上报信息,研究并提出了一种多传感器多目标系统误差融合估计算法.算法构建了两级融合结构,即第一级对多传感器组合状态估计信息进行反馈融合以改善局部组合状态估计精度,从而间接改善系统误差的估计精度,而第二级对多目标系统误差估计信息进行融合以进一步提高系统误差的估计精度.蒙特卡洛仿真显示算法能有效融合利用多传感器多目标信息,实现多传感器系统误差的实时精确估计.
- 系统误差 /
- 传感器网络 /
- 误差配准 /
- 信息融合
Abstract: To solve the problem of sensor systematic bias estimation in sensor network, a systematic bias fusion estimation algorithm was presented based on multi-sensor multi-target information. To solve the forenamed problem, the algorithm was constituted a two layer fusion structure. In order to improve the precision of corresponding combination estimation, the first layer fuses the multi-sensor combination state estimation information with feedback, so the estimation precision of systematic bias can also be improved. While, the second layer fuses the multi-target systematic bias estimation information in order to further improve the estimation precision. The monte-carlo simulation result shows that the algorithm can make sufficient use of the multi-sensor multi-target information with fusion structure, and achieve an exact and real-time estimation of the multi-sensor systematic bias.
- systematic bias /
- sensor network /
- bias registration /
- information fusion

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参考文献(13)

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