NDLI: Data fusion and tracking of complex target maneuvers with a simplex-trained neural network-based architecture

Content Provider	IEEE Xplore Digital Library
Author	Yee Chin Wong Sundareshan, M.K.
Copyright Year	1998
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Arizona Univ., Tucson, AZ, USA (Yee Chin Wong)
Abstract	The capabilities of trained neural networks to perform fusion of data collected from dissimilar sensors employed in target surveillance and tracking environments facilitate an attractive framework for developing advanced target tracking architectures. We present a scheme that employs an integration of a multilayer neural network trained with features extracted from multisensor data and a Kalman filter that yields a reliable tracking algorithm capable of following even noncooperative targets executing complex evasive maneuvers. A learning strategy based on a simplex optimization algorithm that seeks the global minimum of the training error and a progressive network growing procedure are employed to develop the required capabilities underlying the desirable tracking performance delivered by the neural network tracking algorithm. Some representative performance validation studies are given in the form of tracking experiments involving targets executing not only straight line acceleration maneuvers but also complex turns in environments characterized by severe noise and clutter. A fundamental characteristic that deserves emphasis in the proposed target tracking architecture is the role of the neural network in performing data fusion and in providing assistance to a simple linear Kalman filter for tracking the maneuvering target, which provides an intelligent way of implementing an overall nonlinear tracking filter without any attendant increases in computational complexity.
Starting Page	1024
Ending Page	1029
File Size	642251
Page Count	6
File Format	PDF
ISBN	0780348591
ISSN	10987576
DOI	10.1109/IJCNN.1998.685912
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1998-05-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Target tracking Neural networks Multi-layer neural network Sensor fusion Surveillance Feature extraction Data mining Acceleration Working environment noise Computer architecture
Content Type	Text
Resource Type	Article

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