Multisensor Data Fusion Based on Modified Belief Entropy in Dempster–Shafer Theory for Smart Environment

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...

Entropy-Based Markov Chains for Multisensor Fusion

This paper proposes an entropy based Markov chain (EMC) fusion technique and demonstrates its applications in multisensor fusion. Self-entropy and conditional entropy, which measure how uncertain a sensor is about its own observation and joint observations respectively, are adopted. We use Markov chain as an observation combination process because of two major reasons: (a) the consensus output ...

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 wavelettransform (wt) and extended kalman filter (ekf). input data are first filtered by a wavelettransform via daubechies wavelet “db4” functions and the filtered data are then fused based onvariance weights in terms of minimum mean square error. the fused data are finally treated byextended kalman filter for...

Conflict management based on belief function entropy in sensor fusion

Wireless sensor network plays an important role in intelligent navigation. It incorporates a group of sensors to overcome the limitation of single detection system. Dempster-Shafer evidence theory can combine the sensor data of the wireless sensor network by data fusion, which contributes to the improvement of accuracy and reliability of the detection system. However, due to different sources o...

Multisensor Data Fusion