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Proceedings Paper

Variable structure IMM using minimal sub-model-set switching
Author(s): Xuezhi Wang; Subhash Challa; Rob Evans
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Paper Abstract

In this paper, the Variable Structure Multiple Model(VSMM) approach to the maneuvering target tracking problem is considered. A new VSMM design -- the Minimal Sub-Model-Set Switching (MSMSS) algorithm for tracking a maneuvering target is presented. In this algorithm: -- a core model is used to represent the most likely true system mode; -- edge models are used to represent other possible true system modes based on their connectivity with the core model; -- a sub-model-set is defined by the core and edge models and their transition probabilities as determined from the model transition probability matrix for the full model set. The MSMSS algorithm adaptively determines the minimal sub-model-set of models from the total model set and uses this to perform interacting multiple model (IMM) estimation. In addition, an iterative MSMSS algorithm with improved maneuver detection and termination properties is developed. Simulation results demonstrate that, compared to a standard IMM, the proposed algorithms require significantly lower computation while maintaining similar tracking performance. Alternatively, for a computational load similar to IMM, the new algorithms display significantly improved performance.

Paper Details

Date Published: 25 August 2003
PDF: 12 pages
Proc. SPIE 5096, Signal Processing, Sensor Fusion, and Target Recognition XII, (25 August 2003); doi: 10.1117/12.485830
Show Author Affiliations
Xuezhi Wang, Univ. of Melbourne (Australia)
Subhash Challa, Univ. of Melbourne (Australia)
Rob Evans, Univ. of Melbourne (Australia)


Published in SPIE Proceedings Vol. 5096:
Signal Processing, Sensor Fusion, and Target Recognition XII
Ivan Kadar, Editor(s)

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