Editors

Martin E. Liggins II is an engineer with The MITRE Corporation working with the Office of Naval Research. He has more than 20 years of research and development experience in industry and with the Department of Defense. Mr. Liggins has performed fusion research in a number of areas including sensor and data fusion, multisensor and multitarget tracking, radar, high-performance computing, and program management. He is the author of more than 30 technical and research papers. Mr. Liggins has served as the chairman of the National Symposium of Sensor and Data Fusion (1995, 2002, and 2003) and has been an active senior committee member, since 1990. He has also been active in the SPIE Aerosense Conference on Signal Processing, Sensor Fusion, and Target Recognition since 1992. He was awarded the Veridian Medal Paper Award in fusion research (2002) and the first Rome Air Development Center Major General John J. Toomay Award for advances in multispectral fusion technology (1989).

Dr. David L. Hall is a professor in the College of Information Sciences and Technology at the Pennsylvania State University, where he also leads the Center for Network Centric Cognition and Information Fusion. He has more than 30 years of experience in research, research management, and systems development in both industrial and academic environments. Dr. Hall has performed research in a wide variety of areas including celestial mechanics, digital signal processing, software engineering, automated reasoning, and multisensor data fusion. During the past 15 years, his research has focused on multisensor data fusion. He is the author of more than 200 technical papers, reports, book chapters, and books. Dr. Hall is a member of the Joint Directors of Laboratories (JDL) Data Fusion Working Group. He serves on the Advisory Board of the Data Fusion Center based at the State University of New York at Buffalo. In addition, he has served on the National Aeronautics and Space Administration (NASA) Aeronautics and Space Transportation Technology Advisory Committee. In 2001, Dr. Hall was awarded the Joe Mignona award to honor his contributions as a national leader in the data fusion community. The Data Fusion Group instituted the award in 1994 to honor the memory of Joseph Mignona. Dr. Hall was named as an IEEE Fellow in 2003 for his research in data fusion.

Dr. James Llinas has more than 30 years of experience in multisource information processing and data fusion technology extending over research, teaching, and business development activities. He is an internationally recognized expert in sensor, data, and information fusion; coauthored the first integrated book on multisensor data fusion; and has lectured internationally for over 20 years on this topic. He was coeditor of the first edition of the Handbook of Multisensor Data Fusion also Dr. Llinas received the definitive U.S. defense community award from the data fusion community, the Joe Mignona Award, in 1999. In addition, reflecting his international interests and stature, Dr. Llinas was voted as the first president of the International Society for Information Fusion in 1998, and maintains a position on the Executive Board. He has frequently provided high-level assessments of the state-of-the-art in data fusion, most recently to the U.S. Army for their Future Combat Systems program, and previously to the U.S. Air Force Scientific Advisory Board. Dr. Llinas has provided similar high-level guidance to international clients including an invited personal review of the data fusion programs of the Australian Defense Science and Technology Organization (DSTO), and consultations to the Swedish Defense Agency FOI, and the Canadian Defense R&D Canada organization. Dr. Llinas created the concept for and is the executive director for the Center for Multisource Information Fusion located at the State University of New York at Buffalo. This first-of-its-kind, university-based research center has received sponsorship from a broad base of defense and industrial R&D organizations, and is conducting basic research in distributed situational estimation, distributed learning, and correlation science, among a wide variety of other programs.