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 released chemomic levels of TCMs were processed by Kalman filter method with stochastic simulation data as an illustration of the methodology feasibility.

And combined with project example,it introduces the application of Kalman filter method in linear control,points out that the key problem of linear control is deciding the construction camber of beams.

Multi-sensor information fusion optimal white noise de-convolution filter based on Kalman filtering method;

By using the Kalman filtering method and the linear minimum variance optimal fusion rule weighted by matrices,a multisensor information fusion Wiener filter is presented for the multichannel autoregressive moving average(ARMA) signals with white observation noise.

The scheme is based on Kalman filtering algorithm and its fast convergencey speed.

In this paper, we introduce the approach of constant range correction, Kalman filtering correction and trace along trajectory correction.

Based on different defect velocities in the simulated model, the stability of the extending Kalman filtering method is illustrated by the simulation calculation.