Abstract
The radar resource management problem in a multitarget tracking scenario is considered. The problem is solved using a dynamic budget balancing algorithm. It models the different sensor tasks as partially observable Markov decision processes and solves them by applying a combination of Lagrangian relaxation and policy rollout. The algorithm has a generic architecture and can be applied to different radar or sensor systems and cost functions.This is shown through simulations of two-dimensional tracking scenarios. Moreover, it is demonstrated how the algorithm allocates the sensor time budgets dynamically to a changing environment in a nonmyopic fashion. Its performance is compared with different resource allocation techniques and its computational load is investigated with respect to several input parameters.
Original language | English |
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Pages (from-to) | 31 |
Number of pages | 47 |
Journal | ISIF Journal of Advances in Information Fusion |
Volume | 16 |
Issue number | 1 |
Publication status | Published - 2021 |
Bibliographical note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-careOtherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Keywords
- Radar Resource Management
- Partially Observable Markov Decision Process
- Lagrangian Relaxation