Statistical Multisource-Multitarget Information Fusion

Information fusion is the process of gathering, filtering, correlating and integrating relevant information from various sources into one representational format. It is used by signal processing engineers and information operations specialists to help them make decisions involving tasks like sensor management, tracking, and system control. This comprehensive resource provides practitioners with an in-depth understanding of finite-set statistics (FISST) - a recently developed method that has been gaining much attention among professionals because it unifies information fusion, utilizing statistics that most engineers learn as undergraduates. The book helps professionals use FISST to create efficient information fusion systems that can be implemented to address real-world challenges in the field.

Ronald P.S. Mahler is a staff scientist at Lockheed Martin MS2 Tactical Systems with over 25 years of industry experience. He earned his B.E.E. degree at the University of Minnesota and his Ph.D. in Mathematics at Brandeis University. He has served on technology planning workshops for many prominent organizations, including the Electronics Division of the Army Research Office. Dr. Mahler was also a reviewer of the DARPA Dynamic Data Base (DDB) project.