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Proceedings Paper

Parallelization of a large-scale IMM-based multitarget tracking algorithm
Author(s): Robert L. Popp; Krishna R. Pattipati; Yaakov Bar-Shalom
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Paper Abstract

The Interacting Multiple Model (IMM) estimator has been shown to be superior, in terms of tracking accuracy, to a well-tuned Kalman filter when applied to tracking maneuvering targets. However, because of the increasing number of filter modules necessary to cover the possible target maneuvers, the IMM estimator also imposes an additional computational burden. Hence, in an effort to design a real-time IMM-based multitarget tracking algorithm that is independent of the number of modules used in the IMM estimator, we propose a `coarse- grained' (dynamic) parallel implementation that is superior, in terms of computational performance, to previous `fine-grained' (static) parallelizations of the IMM estimator. In addition to having the potential of realizing superlinear speedups, the proposed implementation scales to larger multiprocessor systems and is robust. We demonstrate the performance results both analytically and using a measurement database from two FAA air traffic control radars.

Paper Details

Date Published: 1 September 1995
PDF: 10 pages
Proc. SPIE 2561, Signal and Data Processing of Small Targets 1995, (1 September 1995); doi: 10.1117/12.217711
Show Author Affiliations
Robert L. Popp, Univ. of Connecticut (United States)
Krishna R. Pattipati, Univ. of Connecticut (United States)
Yaakov Bar-Shalom, Univ. of Connecticut (United States)


Published in SPIE Proceedings Vol. 2561:
Signal and Data Processing of Small Targets 1995
Oliver E. Drummond, Editor(s)

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