推广的Pei-Radman特殊矩阵求逆及其应用  

The Inverse of Extended Pei-Radman Matrix and Its Application

作　　者：陈建国[1] 

机构地区：[1]绵阳职业技术学院,绵阳621000

出　　处：《科学技术与工程》2010年第30期7541-7544,共4页Science Technology and Engineering

摘　　要：当矩阵的维数比较高的时候,该矩阵求逆就相当麻烦,且计算量很大。为了克服这个缺点,对于带相同对角元素且其他位置元素也一样的Pei-Radman矩阵,提出了一种能减少计算负担的求逆算法。将该求逆结果应用到带公共干扰噪声的多传感器的观测系统,基于加权最小二乘准则,得到了简化的融合观测和融合的观测噪声形式。该算法能明显减少计算负担,提高融合效率,具有很大的实际应用价值。一个温度观测的仿真例子证明了Pei-Radman特殊矩阵求逆算法的正确性,融合观测及其噪声的有效性。When the matrix has high dimension,the computational burden of the inversion is very large.In order to overcome this drawback,a new extended algorithm is presented for the inversion of the Pei-Radman matrix,which can reduce the computational load.Based on the weighted least squares（WLS） method,this inversion result can be applied to the multi-sensor measurement fusion system with common disturbance noise.This algorithm can obviously reduce the computational burden,and has application value.A example for the temperature measurement is given,which proves the correctness of the inversion of the Pei-Radman matrix and verifies the validity of the fused measurement and the fused measurement noise.

关 键 词：Pei-Radman矩阵 矩阵求逆 加权观测融合 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]