TRACKING-FILTER STRUCTURES FOR AUTOMATIC TRACK-WHILE-SCAN SURVEILLANCE SYSTEMS

Authors
  1. Bridgewater, A.W.
Corporate Authors
Communications Research Centre, Ottawa ONT (CAN)
Abstract
In an automatic track-while-scan air-surveillance radar system, the role of the target-tracking filter is to support the plot-to-track association process by providing reliable estimates of the current track state, on which to base predictions of subsequent track states. The Kalman filter is the most general solution of the recursive linear mean-square estimation problem, its drawback being its computational cost. An analysis of various one-dimensional forms of filter, derived from the Kalman, results in reduced-Kalman classes of tracking filter, which often form the basis for the design of the practical two- and three-dimensional trackers required in air-surveillance systems and which combine good track-following ability, ease of adaptation to changes in tracking conditions and low computational cost. Both recursive and steady-state adaptive versions of these one-dimensional structures are described.
Report Number
1341 —
Date of publication
15 Mar 1981
Number of Pages
46
DSTKIM No
81-03688
CANDIS No
34447
Format(s):
Hardcopy;Originator's fiche received by DSIS

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