Currently there exist three multisensor measurement fusion methods, namely, augmented method, pseudo-sequential filtering method, and combined measurement filtering method.

A multi-sensor fusion and control system was designed,with a dual-CPU structure based on ADμC812 and TMS320F206.

Based on analyzing the factors mainly affect the accuracy of the measurement, microwave technique and capacitance technology which combined with the specific resistivity of fly ash is adopted to construct a multi-sensor fusion-based measuring system, and then BP neural network is utilized to fuse the multi-s.

The basic principles of multi-sensor fusion,architecture and function model of data fusion,data fusion meth- ods,and the scope of applications are introduced,the applications of data fusion in the radar networks system are intro- duced.

Based on the multi-sensor data fusion technique and D-S theory,the method to control and monitor welding quality was designed and experiment system was established.

For dealing with aerial target recognition data with uncertainty and fuzzyness,and improving the precision and reliability of multi-sensor fusion for aerial target,a multi-sensor data fusion model was put forward based on fuzzy Bayesian network structure.

Aiming at the problem of detection performance of infrared(IR) images,from the typical flow of multi-sensor data fusion algorithm,the relationship among the detection performances of single IR image,IR image sequence,and multi-sensor data fusion algorithm was deduced.

Research on Multisensor Fusion and Navigation for Robot Mower;

An on-line surface roughness estimating method based on multisensor fusion via neural networks is presented for the requirement of machine tool intelligent machining.

The application of multisensor fusion technology in train speed and position measurement is introduced.