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Proceedings Paper

IMM modeling for AEW applications
Author(s): Robert Schutz; Bruce Engelberg; Warren Soper; Robert Mottl
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Paper Abstract

Previous papers (1997, 1999, 2000) have described a tracking approach which utilized a Combined Kalman Filter (CKF), adaptive tracking for maneuver tracking, and the JVC association algorithm for reports to tracks, for use in Airborne Early Warning (AEW) applications. In this paper we present our incorporation of Interacting Multiple Model (IMM) tracking. First our previous AEW tracking approach is briefly reviewed as most of this approach is still utilized and forms our baseline. The new IMM approach and equations are then described. Then the two IMM tracking approaches used are discussed. One involves a two model IMM containing two constant velocity models, one a low process noise and the other a high process noise model. The other approach involves three IMM filter models, a coordinated turn filter model, and the same two constant velocity filter models as in the two model IMM approach. Results for both IMM approaches and the baseline tracker are shown. The results presented involve a 120 target scenario with two second update time with simulated radar data. In addition computer timing results are presented. These results indicate that while the three model IMM approach provides the best tracking results, it does so at a substantial computational cost. The two model IMM provides comparable tracking improvement but at a far less computational cost.

Paper Details

Date Published: 26 November 2001
PDF: 12 pages
Proc. SPIE 4473, Signal and Data Processing of Small Targets 2001, (26 November 2001); doi: 10.1117/12.492774
Show Author Affiliations
Robert Schutz, Northrop Grumman Corp. (United States)
Bruce Engelberg, Northrop Grumman Corp. (United States)
Warren Soper, Northrop Grumman Corp. (United States)
Robert Mottl, Northrop Grumman Corp. (United States)


Published in SPIE Proceedings Vol. 4473:
Signal and Data Processing of Small Targets 2001
Oliver E. Drummond, Editor(s)

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