Target Tracking with Random Finite Sets - Tapa dura

Acerca del autor

Weihua Wu is an associate professor at Air Force Early Warning Academy. His research direction is target tracking based on random finite sets. He is a candidate of young talent support project of Chinese association for science and technology. He presided over the completion of a number of scientific research projects such as the National Natural Science Foundation. He was funded and has published three books in National Defense Industry Press: “Target Tracking With Random Finite Sets”, “Target Tracking Technology for Moving Sensors”, and “Multi-Sensor Data Fusion”. He has published about 30 papers (including well-known journals such as IEEE Transactions on Signal Processing, Signal Processing, Aerospace Science & Technology, Digital Signal Processing, etc.).

Hemin Sun is a professor from Air Force Early Warning Academy. His research direction is radar networking and data fusion. He was funded and has published two books in National Defense Industry Press: “Multi-Sensor DataFusion” and “Target Tracking With Random Finite Sets”. He has published about 30 papers.

Mao Zheng is a lecturer from Air Force Early Warning Academy. His research direction is target tracking and data fusion. He has co-published a book about “Multi-Sensor Data Fusion”. He has published about 20 papers.

Weiping Huang is a lecturer from Air Force Early Warning Academy. Her research direction is target tracking and data association. She received her doctor's degree with Target Tracking. She completed some scientific research projects such as the National Coastal Defense Monitoring System and has published a book about distribution system. She has published about 30 papers.

De la contraportada

This book focuses on target tracking and information fusion with random finite sets. Both principles and implementations have been addressed, with more weight placed on engineering implementations. This is achieved by providing in-depth study on a number of major topics such as the probability hypothesis density (PHD), cardinalized PHD, multi-Bernoulli (MB), labeled MB (LMB), d-generalized LMB (d-GLMB), marginalized d-GLMB, together with their Gaussian mixture and sequential Monte Carlo implementations. Five extended applications are covered, which are maneuvering target tracking, target tracking for Doppler radars, track-before-detect for dim targets, target tracking with non-standard measurements, and target tracking with multiple distributed sensors. The comprehensive and systematic summarization in target tracking with RFSs is one of the major features of the book, which is particularly suited for readers who are interested to learn solutions in target tracking with RFSs. The book benefits researchers, engineers, and graduate students in the fields of random finite sets, target tracking, sensor fusion/data fusion/information fusion, etc.