For the multisensor systems with correlated measurement noises and different measurement matrices,two correlated measurement fusion steady-state Kalman filtering algorithms are presented by using the weighted least squares (WLS)method.

Multi-sensor optimal information fusion steady-state Kalman filter weighted by scalars;

Two-sensor information fusion steady-state Kalman filter weighted by diagonal matrices;

This paper presents a new way to estimate the measurement variance of noise in the analytical chemistry signals for the Kalman filter by means of implementing the wavelet analysis, according to that wavelet transformation can separate the noise in high frequency band from the original signal.

Compared with traditional ones such as Kalman filter and least squares, the technique results in more accurate estimations of OD split proportions.

Based upon the principles of Kalman filter method,the authors defined a new parameter,relative chemomic error(ε),to evaluate the asynchronous nature of the components in TCMs,and a derivative parameter as synchronization factor(SF) to quantify the synchronicity of the chemome .

The comparison of three residuals in Kalman filtering model;

Kalman filtering identification of Winkler foundation’s parameter based on Mindlin theory;

SINS refined initial alignment based on Elman neural network and Kalman filtering;