Application Researth on the Ensemble Kalman Filter (EnKF) with a Medium-Range Numerical Weather Prediction (NWP) Spectral Model at a T106L19 Resolution;

There is tremendous rationale that ensemble Kalman filtering apply to the numerical forecast data assimilation.

The performance of data assimilation using the “flow-dependent” statistics calculated from an ensemble of short-range forecasts (termed as Ensemble Kalman Filter, EnKF) with 100 members compared with Optimal Interpolation (OI) is examined in an idealized environment.

The Kalman filter data assimilation methods were applied in dynamical systems,the result of ensemble Kalman filter was compared with three dimension variational data assimilation,and the elementary properties of the ensemble Kalman filter data assimilation techniques were discussed.

The Application of Combined Kalman Filtering to the Kinematic GPS Positioning;

GPS/DR Integrated Vehicle Navigation System Based on MEMS and Design of Federated Kalman Filter;

A federated Kalman filter algorithm based on multi-sensor fusion of several sensors in optoelectronic tracking system is proposed.

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 .