Accession Number : ADA304190
Title : Pattern Theoretic Bayesian Inference for Multisensor Fusion.
Descriptive Note : Final rept. 30 May 95-31 Jan 96,
Corporate Author : WAGNER (DANIEL H) ASSOCIATES PAOLI PA
Personal Author(s) : Belkin, Barry ; Suchower, Stephan J.
PDF Url : ADA304190
Report Date : 01 FEB 1996
Pagination or Media Count : 51
Abstract : The focus of our Phase I study was to develop and test an algorithm to track a single aircraft of known type using the jump-diffusion method for state estimation. This technique avoids the limitations of conventional state estimation methods (most notably Kalman filtering) in dealing with the discrete state variables (such as target type) and the nonlinear/non-Gaussian measurements encountered in multisensor data fusion problems. The jump-diffusion technique operates by using Monte Carlo simulation to directly sample from the Bayes posterior distribution for the target state. The method is applied to the tracking of a maneuvering air target based on a combination of radar point tracking and optical imagery data. Numerical results show in particular that the aircraft orientation information extracted through the processing of optical images can significantly reduce tracking error relative to conventional point tracking methods. In Phase II we plan to continue the development of the Phase I algorithm by adding the capability to track multiple targets and to perform the automatic target recognition function when targets are of unknown type. (AN)
Descriptors : *IMAGE PROCESSING, *TARGET RECOGNITION, *PATTERN RECOGNITION, *DATA FUSION, MATHEMATICAL MODELS, ALGORITHMS, COMPUTERIZED SIMULATION, PARAMETRIC ANALYSIS, DATA MANAGEMENT, STATISTICAL INFERENCE, AIRCRAFT DETECTION, RADAR TRACKING, MOVING TARGETS, MULTIPLE TARGETS, KALMAN FILTERING, ACCURACY, PARALLEL PROCESSING, OPTICAL DATA, OPTICAL IMAGES, SYNTHETIC APERTURE RADAR, RADAR IMAGES, MONTE CARLO METHOD, HIGH RESOLUTION, AERIAL TARGETS, BAYES THEOREM, OPTICAL DETECTORS, PIXELS, OPTICAL TRACKING, MULTISENSORS, LOW RESOLUTION.
Subject Categories : Cybernetics
Optical Detection and Detectors
Active & Passive Radar Detection & Equipment
Distribution Statement : APPROVED FOR PUBLIC RELEASE