Rose, Kenneth and Gurewitz, Eitan and Fox, Geoffrey (1990) A Nonconvex Cost Optimization Approach to Tracking Multiple Targets by a Parallel Computational Network. In: Proceedings of the Fifth Distributed Memory Computing Conference, 1990. IEEE , Piscataway, NJ, pp. 78-84. ISBN 0-8186-2113-3. https://resolver.caltech.edu/CaltechAUTHORS:20170628-173206820
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Abstract
The problem of tracking multiple targets in the presence of displacement noise and clutter is formulated as a nonconvex optimization problem. The form of the suggested cost function is shown to be suitable for the Graduated Non-Convexity algorithm, which can be viewed as deterministic annealing. The method is first derived for the two-dimensional (spatial/ temporal) case, and then generalized to the multi-dimensional case. The complexity grows linearly with the number of targets. Computer simulations show the performance with crossing trajectories.
| Item Type: | Book Section | |||||||||
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| Additional Information: | © 1990 IEEE. | |||||||||
| DOI: | 10.1109/DMCC.1990.555365 | |||||||||
| Record Number: | CaltechAUTHORS:20170628-173206820 | |||||||||
| Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20170628-173206820 | |||||||||
| Official Citation: | K. Rose, E. Gurewitz and G. Fox, "A Nonconvex Cost Optimization Approach to Tracking Multiple Targets by a Parallel Computational Network," Proceedings of the Fifth Distributed Memory Computing Conference, 1990., 1990, pp. 78-84. doi: 10.1109/DMCC.1990.555365 | |||||||||
| Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | |||||||||
| ID Code: | 78681 | |||||||||
| Collection: | CaltechAUTHORS | |||||||||
| Deposited By: | Kristin Buxton | |||||||||
| Deposited On: | 29 Jun 2017 01:41 | |||||||||
| Last Modified: | 15 Nov 2021 17:42 |
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