This book includes papers from the section “Multisensor Information Fusion”, from Sensors between 2018 to 2019. It focuses on the latest research results of current multi-sensor fusion technologies and represents the latest research trends, including traditional information fusion technologies, estimation and filtering, and the latest research, artificial intelligence involving deep learning.
Xue-Bo Jin
linear regression covariance matrix data association sensor fusing SLAM multi-sensor data fusion conflicting evidence Dempster–Shafer evidence theory belief entropy similarity measure data classification fault diagnosis Bar-Shalom Campo Covariance Projection method data fusion