Multisensor Fusion Estimation Theory and Application, 1st ed. 2021

Introduction to Optimal Fusion Estimation and Kalman Filtering: Preliminaries.- Kalman Filtering of Discrete Dynamic Systems.- Optimal Kalman filtering Fusion for Linear Dynamic Systems with Cross-Correlated Sensor Noises.- Distributed Data Fusion for Multirate Sensor Networks.- Optimal Estimation for Multirate Systems with Unreliable Measurements and Correlated Noise.- Fusion Estimation for Asynchronous Multirate Multisensor Systems with Unreliable Measurements and Coupled Noises.- Multi-sensor Distributed Fusion Estimation for Systems with Network Delays, Uncertainties and Correlated Noises.- Event-triggered Centralized Fusion Estimation for Dynamic Systems with Correlated Noises.- Event-triggered Distributed Fusion Estimation for WSN Systems.- Event-triggered Sequential Fusion Estimation for Dynamic Systems with Correlated Noises.- Distributed Fusion Estimation for Multisensor Systems with Heavy-tailed Noises.- Sequential FusionEstimation for Multisensor Systems with Heavy-tailed Noises.

Liping Yan was born in Henan Province, China, in 1979. She received her B.S. degree and M.S. degree both in Mathematics from Henan University, Kaifeng city, Henan Province, P. R. China, in 2000 and 2003, respectively, and received her Ph.D. degree in Control Science and Engineering from Tsinghua University, Beijing, China, in 2007. From January 2007 to July 2009, she was a Postdoctoral Research Associate in the Equipment Academy of Airforce. Since July 2009, she has been with the School of Automatic Control, Beijing Institute of Technology, Beijing, first as an Assistant Professor, then, since 2011, as an Associate Professor. From March 2012 to March 2013, supported by CSC, she was a Visiting Scholar in the University of New Orleans, New Orleans, LA, USA. From September 2018 to August 2019, supported by CSC, she was a Visiting Scholar in the University of Windsor, Windsor, ON, Canada. She has co-authored five books and more than 60 journal and conference papers. Currently, she is an Associate Professor and Ph.D. supervisor in BIT. Her research interests include multisensor data fusion, state estimation, image registration, intelligent navigation and integrated navigation, etc.

Lu Jiang was born in Shandong Province, China, in 1990. She received her B.S. degree in Automation from Qingdao University, Qingdao city, Shandong Province, P. R. China, in 2013, and received her Ph.D. degree in Control Science and Engineering from Beijing Institute of Technology, Beijing, China, in 2019. She is currently an Assistant Professor in Beijing Technology and Business University. Her research interests include multisensor data fusion, optimal state estimation, etc.

Yuanqing Xia was born in Anhui Province, China, in 1971, and graduated from the Department of Mathematics, Chuzhou University, Chuzhou, China, in 1991. He received his M.S. degree in Fundamental Mathematics from Anhui University, China, in 1998, and his Ph.D. degree in Control Theory and Control Engineering fro

Addresses multisensor data fusion state estimation both in theory and practice Studies comprehensively state fusion estimation methods in case of networked transmission problems Presents the design of event-triggered strategies and the state fusion estimation algorithms in case of event-triggered conditions Provides in-depth state fusion estimation algorithms in case of non-Gaussian but heavy-tailed noises, including the information filter for heavy-tailed systems