多传感器分布式推广卡尔曼滤波算法及其在雷达红外目标跟踪中的应用

崔宁周; 谢维信; 余雄南

多传感器分布式推广卡尔曼滤波算法及其在雷达红外目标跟踪中的应用

崔宁周^{①;谢维信},
谢维信,
余雄南

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- 被引次数: 0
出版历程
- 收稿日期: 1995-01-11
- 修回日期: 1996-04-16
- 刊出日期: 1997-05-19

MULTISENSOR DISTRIBUTED EXTENDED KALMAN FILTERING ALGORITHM AND ITS APPLICATION TO RADAR/IR TARGET TRACKING

Cui Ningzhou^{①;谢维信},
Xie Weixin,
Yu Xiongnan

摘要

摘要: 本文提出了一种用于非线性系统的多传感器分布式推广卡尔曼滤波算法,该算法中系统的动态方程和传感器的观测方程分别围绕全局估计和全局预测线性化,融合中心基于所有传感器观测的全局估计由各传感器基于自身观测的局部估计来重构。算法分析说明,全局估计的精度高、误差小。最后介绍了文中算法在雷达和红外两种传感器跟踪机动目标中的应用,仿真结果验证了该算法的有效性。
- 推广卡尔曼滤波（EKF）; 目标跟踪; 分布估计; 数据融合
Abstract: A multisensor distributed extended Kalman filtering algorithm is presented for nonlinear systems, in which the dynamic equations of the systems and the equations of sensor s measurements are linearized in the global estimates and global predictions respectively, and the suboptimal global estimates based on all available information can be reconstructed from the estimates computed by local sensors based solely on their own local information and transmitted to the data fusion center. An analysis of the properties of the algorithm presented here shows that the global estimate has higher precision than the local one and smaller linearization error than the existing method. Finally, an application of the algorithm to radar/IR, tracking of a maneuvering target is illustrated. Simulation results show the effectiveness of the algorithm.

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参考文献(1)

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