Featuring a unified framework to derive different grid-based nonlinear estimation algorithms from a numerical integration perspective, this book discusses the fundamental concepts of many widely used nonlinear estimation techniques.
Featuring a unified framework to derive different grid-based nonlinear estimation algorithms from a numerical integration perspective, this book discusses the fundamental concepts of many widely used nonlinear estimation techniques.
Bin Jia is a Project Manager at Intelligent Fusion Technology, Inc. in Germantown, Maryland, a research and development company focusing on information fusion technologies from fundamental research to industry transition and product development and support. Dr. Jia received a Ph.D. in Aerospace Engineering from Mississippi State University in 2012, a M.S from Graduate University of the Chinese Academy of Sciences, and a B.S from Jilin University, China, in 2007 and 2004, respectively. From 2012 to 2013, he worked as a postdoctoral research scientist at Columbia University. Dr. Jia's research experience includes Bayesian estimation, multi-sensor multi-target tracking, information fusion, guidance and navigation, and space situational awareness. Ming Xin is an Associate Professor in the Department of Mechanical and Aerospace Engineering at University of Missouri-Columbia. He received his B.S. and M.S. degrees from Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 1993 and 1996, respectively, both in Automatic Control. He received his Ph.D. in Aerospace Engineering from Missouri University of Science and Technology in 2002. His research interests include guidance, navigation, and control of aerospace vehicles, flight mechanics, estimation theory and applications, cooperative control of multi-agent systems, and sensor networks. Dr. Xin was the recipient of the National Science Foundation CAREER Award in 2009. He is an Associate Fellow of AIAA and a Senior Member of IEEE and AAS.
Inhaltsangabe
Preliminary Estimation Concepts. Dynamic System Description. Linear Estimation of Dynamic Systems. Nonlinear Estimation: Conventional Filters . Nonlinear Estimation: Grid-based Filtering and Smoothing. Nonlinear Estimation: Gaussian Mixture Filters. Multiple Sensor Estimation. Applications: Uncertainty Propagation. Applications: Target Tracking. Applications: Guidance, Navigation, and Control of Spacecraft.
