Some recursive filtering algorithms were developed for tracking ships when observations are sporadic and imprecise. Tracking with position-only observations was emphasized, but a procedure was also developed for utilizing possible independent observations of ship velocity. Two basic algorithms are considered: a Kalman filter with adaptive driving noise for generating estimates (and containment ellipses) for current and future ship positions, and a corresponding Bayesian smoother for generating estimates of past positions. The driving noise was treated as a velocity term in a continuous-time model of ship's motion. The details of these two algorithms were developed for tracking on a plane, on a sphere in geographical coordinates, and on a sphere in three-dimensional rectilinear coordinates. A FORTRAN implementation and some corresponding numerical results were developed for the planar case.


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    Title :

    Recursive Filtering Algorithms for Ship Tracking


    Contributors:

    Publication date :

    1976


    Size :

    50 pages


    Type of media :

    Report


    Type of material :

    No indication


    Language :

    English





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