Paper
10 May 2007 Impact point prediction of small ballistic munitions with an interacting multiple model estimator
Steve Conover, J. Clayton Kerce, George Brown, Lisa Ehrman, David Hardiman
Author Affiliations +
Abstract
The interacting multiple model (IMM) estimator, which mixes and blends results of multiple filters according to their mode probabilities, is frequently used to track targets whose motion is not well-captured by a single model. This paper extends the use of an IMM estimator to computing impact point predictions (IPPs) of small ballistic munitions whose motion models change when they reach transonic and supersonic speeds. Three approaches for computing IPPs are compared. The first approach propagates only the track from the most likely mode until it impacts the ground. Since this approach neglects inputs from the other modes, it is not desirable if multiple modes have near-equal probabilities. The second approach for computing IPPs propagates tracks from each model contained in the IMM estimator to the ground independent of each other and combines the resulting state estimates and covariances on the ground via a weighted sum in which weights are the model probabilities. The final approach investigated here is designed to take advantage of the computational savings of the first without sacrificing input from any of the IMM's modes. It fuses the tracks from the models together and propagates the fused track to the ground. Note that the second and third approaches reduce to the first if one of the models has a mode probability of one. Results from all three approaches are compared in simulation.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Steve Conover, J. Clayton Kerce, George Brown, Lisa Ehrman, and David Hardiman "Impact point prediction of small ballistic munitions with an interacting multiple model estimator", Proc. SPIE 6569, Acquisition, Tracking, Pointing, and Laser Systems Technologies XXI, 656905 (10 May 2007); https://doi.org/10.1117/12.723567
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Motion models

Motion estimation

Error analysis

Time metrology

Filtering (signal processing)

Process modeling

Sensors

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