量测噪声相关条件情况下的多传感器状态融合估计  

Multi-sensor state estimation fusion with correlated measurement noise

作　　者：邓奎彪[1] 秦超英[1] 张在利[1] 

机构地区：[1]西北工业大学理学院应用数学系,陕西西安710129

出　　处：《计算机工程与设计》2009年第18期4248-4250,共3页Computer Engineering and Design

摘　　要：对于量测噪声相关的多传感器系统,采用Cholesky分解和单位下三角阵的求逆方法,将其转化为量测噪声互不相关的等价模型,从而可以直接利用现有的融合算法进行状态融合,由此给出了量测噪声相关情况下多传感器的状态融合算法。该算法和已有的算法相比具有两大优点,该算法不仅考虑了量测噪声相关而且简单可行,而且该算法和已有的算法相比更具有一般性,对于有特征值相同的情形同样适用。数值仿真结果表明了该算法的有效性。By using the Cholesky factorization and inverse method unit lower triangular matrix, the multi-sensor measurement model with correlated measurement noise is transformed to an equivalent model with uncorrelated measurement noise. State fusion algorithms can be carry on firstly, and on basis of it derive form multi-sensor state fusion with correlated measure noise. This algorithm has two merits compared with other algorithms. Firstly, this algorithm not only consider correlated measurement noise but also is simply feasible. Secondly, this algorithm is universal with the existing algorithm. Numerical simulation results are provided to demonstrate the validity of the algorithm.

关 键 词：状态估计 CHOLESKY分解 相关量测噪声 KALMAN滤波 仿真 

分 类 号：TP212[自动化与计算机技术—检测技术与自动化装置]