IMM algorithm and aperiodic data

W. Dale Blair; Gregory A. Watson

doi:10.1117/12.138208

25 November 1992 IMM algorithm and aperiodic data

W. Dale Blair, Gregory A. Watson

Proceedings Volume 1697, Acquisition, Tracking, and Pointing VI; (1992) https://doi.org/10.1117/12.138208
Event: Aerospace Sensing, 1992, Orlando, FL, United States

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 p_ij 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.

Citation Download Citation

W. Dale Blair and Gregory A. Watson "IMM algorithm and aperiodic data", Proc. SPIE 1697, Acquisition, Tracking, and Pointing VI, (25 November 1992); https://doi.org/10.1117/12.138208

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