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Proceedings Paper

IMM algorithm and aperiodic data
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Paper Abstract

The interacting multiple method (IMM) algorithm is an effective technique for tracking maneuvering targets. The IMM algorithm uses multiple models that interact through state mixing to track a target maneuvering through an arbitrary trajectory. The state estimates are mixed according to their model probabilities and the model switching probabilities that are governed by an underlying Markov chain. In the IMM algorithm, the probability pij of switching from model i to model j is often assumed to be uniform between each measurement update. However, for multiple sensors operating asynchronously or a sensor with a probability of detection less than one, the data will be aperiodic. To overcome this limitation, the model switching probabilities are modeled as time-dependent. IMM algorithms with constant and time-dependent model switching probabilities are evaluated for the cases of a two sensor tracking system and a sensor with a probability of detection of detection less than one.

Paper Details

Date Published: 25 November 1992
PDF: 9 pages
Proc. SPIE 1697, Acquisition, Tracking, and Pointing VI, (25 November 1992); doi: 10.1117/12.138208
Show Author Affiliations
W. Dale Blair, Naval Surface Warfare Ctr. (United States)
Gregory A. Watson, Naval Surface Warfare Ctr. (United States)


Published in SPIE Proceedings Vol. 1697:
Acquisition, Tracking, and Pointing VI
Michael K. Masten; Larry A. Stockum, Editor(s)

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