Sequence comparison techniques for multisensor data fusion and target recognition

• Published in: IEEE transactions on aerospace and electronic systems Vol. 32; no. 1; pp. 52 - 65
• Main Authors: Libby, E.W., Maybeck, P.S.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.01.1996; Institute of Electrical and Electronics Engineers
• Subjects: Applied sciences; Dynamic programming; Evaluation; Exact sciences and technology; Fuses; Information, signal and communications theory; Kinematics; Mathematical models; Parameter estimation; Pattern recognition; Sensor data fusion; Signal processing; Speech processing; State estimation; Target recognition; Target tracking; Telecommunications and information theory; Vectors; Vehicles; Moving target; Radar target; Image processing; Ambiguity function; Dynamic programming; Pattern recognition; Dynamic model; State estimation; Cramer Rao inequality
• ISSN: 0018-9251
• DOI: 10.1109/7.481249

A new class of techniques for multisensor fusion and target recognition is proposed using sequence comparison by dynamic programming and multiple model estimation. The objective is to fuse information on the kinematic state and "nonkinematic" signature of unclassified targets, assessing th...