RECURSIVE FILTERING ALGORITHMS FOR SHIP TRACKING

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.

  • Corporate Authors:

    Naval Research Laboratory

    4555 Overlook Avenue, SW
    Washington, DC  USA  20375-5320
  • Authors:
    • Willman, W W
  • Publication Date: 1976-4-6

Media Info

  • Pagination: 50 p.

Subject/Index Terms

Filing Info

  • Accession Number: 00170775
  • Record Type: Publication
  • Source Agency: National Technical Information Service
  • Report/Paper Numbers: NRL-7969 Intrm Rpt.
  • Files: TRIS
  • Created Date: Mar 14 1978 12:00AM