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CONCIE TRACK CHARACTERIZATION OF MANEUVERING TARGETS



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Concise Track Characterization of Maneuvering Targets Stephen Linder Matthew Ryan Richard Quintin This material is based on work supported by Dr Teresa McMullen through the Office of Naval Research under Contract No N00039 D 0042 Delivery Order No D O 278 February 2001 SUNY Plattsburgh Problem Context A weaving target track constructed of linked coordinated turns February 2001 SUNY Plattsburgh Research Goals Improve instantaneous estimation of target velocity and acceleration for use by guidance law Perform data compression on track data so that a succinct description of target track can be obtained Target traveled at heading of 20 for 100 yards Turned left at 10 sec to heading of 100 Use track characterization to dynamically select and tune guidance law parameters Classification of target from pattern of motion Computational feasibility for a real time in water system February 2001 SUNY Plattsburgh Approach Segmenting Track Identifier STI Support multiple localized nonlinear models of target motion Most current tracking techniques require linear motion models Use batch processing of data Do not attempt to calculate globally optimal solution rather Generate locally optimal track segments by February 2001 minimizing mean square error of each track segment and then matching the position and velocity of consecutive segments at the knots connecting the segments SUNY Plattsburgh Target models Target models used by current trackers Turns maneuvers are modeled by the Singer maneuver model Maneuvers are time correlated with a specified time constant and acceleration variance Locally linear models of coordinated models STI target model February 2001 Target runs at only several discrete speeds Target performs only coordinated turn maneuvers Continuity in position and velocity between segments SUNY Plattsburgh Linking coordinated turns knots February 2001 SUNY Plattsburgh Position and velocity continuity Match position Match velocity February 2001 SUNY Plattsburgh Knot Placement Approach Phase I initial segmentation Calculate if knot is needed after every measurement Place knot if RMSE error of current spline begins to increase Err on the side of generating two many knots and then recombine knots in second phase of processing Make initial position velocity and acceleration estimate Phase II refine segmentation After second knot is placed go back and search for a knot position that optimizes February 2001 continuity conditions for position and velocity of the splines at knot and minimize total least square fit of both splines to measured data SUNY Plattsburgh Knot placement flow diagram Sn 2 Sn 2 Sn 1 Sn 3 Sn No Can segmen t Sn 1 and Sn 2 be merged Sn 3 Sn 1 Sn Sn 1 Yes Sn 2 Sn Acquire new segment Merge successive segments Sn 2 Sn 1 Sn 1 Sn 3 Sn Sn 2 Optimize knot between Sn 1 and Sn February 2001 Sn Optimize knot between Sn 2 and Sn 1 SUNY Plattsburgh Cost functions The total least squares term for a line segment QL is p QL i 1 2 yi mxi b 2 m 1 The total



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