An Integrated Model for Robust Multisensor Data Fusion

An Integrated Model for Robust Multisensor Data Fusion

This paper presents an integrated model aimed at obtaining robust and reliable results in decision level multisensor data fusion applications. The proposed model is based on the connection of Dempster-Shafer evidence theory and an extreme learning machine. It includes three main improvement aspects: a mass constructing algorithm to build reasonable basic belief assignments (BBAs); an evidence s...

Multisensor Data Fusion

Multisensor Data Fusion

IMultisensor data fusion refers to the acquisition, processing and synergistic combination of information gathered by various knowledge sources and sensors to provide a better understanding of a phenomenon. It is a fascinating and rapidly evolving field that has generated a lot of excitement in the research and development community. These concepts are being applied to a wide variety of fields ...

Approaches to Multisensor Data Fusion

s part of an Office of Naval Research–funded science and technology development task, APL is developing an identification (ID) sensor data fusion testbed. The testbed is driven by an APL-modified version of the Joint Composite Tracking Network pilot benchmark called the Composite Combat ID Analysis Testbed (CAT). The CAT provides accurate tracking for realistic scenarios involving multiple targ...

A New Method for Multisensor Data Fusion Based on Wavelet Transform in a Chemical Plant

This paper presents a new multi-sensor data fusion method based on the combination of wavelet transform (WT) and extended Kalman filter (EKF). Input data are first filtered by a wavelet transform via Daubechies wavelet “db4” functions and the filtered data are then fused based on variance weights in terms of minimum mean square error. The fused data are finally treated by extended Kalman filter...