The Inverse of Extended Pei-Radman Matrix and Its Application

Abstract

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.