Approximately Optimal Radar Resource Management for Multi-Sensor Multi-Target Tracking

Bas  van der Werk; Max Ian Schöpe; Hans Driessen

Approximately Optimal Radar Resource Management for Multi-Sensor Multi-Target Tracking

Bas van der Werk, Max Ian Schöpe, Hans Driessen

Microwave Sensing, Signals & Systems

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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Abstract

Radar Resource Management in a multi-sensor multi-target scenario is considered. A dynamic resource balancing algorithm is proposed which optimizes target task parameters assuming an underlying partially observable Markov decision process (POMDP). By applying stochastic optimization methods, such as policy rollout, the POMDP is solved non-myopically. The approximately optimal approach is formulated assuming a central processor. Subsequently, a distributed implementation is introduced that converges to the same results as given by the centralized implementation and requires less computational resources. The performance of the proposed approach for both centralized and distributed implementation is demonstrated through dynamic tracking scenarios.

Original language	English
Title of host publication	2021 IEEE 24th International Conference on Information Fusion (FUSION)
Subtitle of host publication	Proceedings
Publisher	IEEE
Pages	1-8
Number of pages	8
ISBN (Electronic)	978-1-7377497-1-4
ISBN (Print)	978-1-6654-1427-2
Publication status	Published - 2021
Event	2021 IEEE 24th International Conference on Information Fusion (FUSION) - Hybrid at Sun City, South Africa Duration: 1 Nov 2021 → 4 Nov 2021 Conference number: 24th

Conference

Conference	2021 IEEE 24th International Conference on Information Fusion (FUSION)
Abbreviated title	Fusion 2021
Country/Territory	South Africa
City	Hybrid at Sun City
Period	1/11/21 → 4/11/21

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-care

Otherwise 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
Distributed Sensor Network
Constrained Optimization
POMDP

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https://ieeexplore.ieee.org/document/9627058

Cite this

@inproceedings{1be9a23b2ae944f390ee30ce7391fab1,

title = "Approximately Optimal Radar Resource Management for Multi-Sensor Multi-Target Tracking",

abstract = "Radar Resource Management in a multi-sensor multi-target scenario is considered. A dynamic resource balancing algorithm is proposed which optimizes target task parameters assuming an underlying partially observable Markov decision process (POMDP). By applying stochastic optimization methods, such as policy rollout, the POMDP is solved non-myopically. The approximately optimal approach is formulated assuming a central processor. Subsequently, a distributed implementation is introduced that converges to the same results as given by the centralized implementation and requires less computational resources. The performance of the proposed approach for both centralized and distributed implementation is demonstrated through dynamic tracking scenarios.",

keywords = "Radar Resource Management, Distributed Sensor Network, Constrained Optimization, POMDP",

author = "{van der Werk}, Bas and Sch{\"o}pe, {Max Ian} and Hans Driessen",

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-care Otherwise 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.; 2021 IEEE 24th International Conference on Information Fusion (FUSION), Fusion 2021 ; Conference date: 01-11-2021 Through 04-11-2021",

year = "2021",

language = "English",

isbn = "978-1-6654-1427-2",

pages = "1--8",

booktitle = "2021 IEEE 24th International Conference on Information Fusion (FUSION)",

publisher = "IEEE",

address = "United States",

}

van der Werk, B, Schöpe, MI & Driessen, H 2021, Approximately Optimal Radar Resource Management for Multi-Sensor Multi-Target Tracking. in 2021 IEEE 24th International Conference on Information Fusion (FUSION): Proceedings., 9627058, IEEE, pp. 1-8, 2021 IEEE 24th International Conference on Information Fusion (FUSION), Hybrid at Sun City, South Africa, 1/11/21. <https://ieeexplore.ieee.org/document/9627058>

Approximately Optimal Radar Resource Management for Multi-Sensor Multi-Target Tracking. / van der Werk, Bas ; Schöpe, Max Ian; Driessen, Hans.
2021 IEEE 24th International Conference on Information Fusion (FUSION): Proceedings. IEEE, 2021. p. 1-8 9627058.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

TY - GEN

T1 - Approximately Optimal Radar Resource Management for Multi-Sensor Multi-Target Tracking

AU - van der Werk, Bas

AU - Schöpe, Max Ian

AU - Driessen, Hans

N1 - Conference code: 24th

PY - 2021

Y1 - 2021

N2 - Radar Resource Management in a multi-sensor multi-target scenario is considered. A dynamic resource balancing algorithm is proposed which optimizes target task parameters assuming an underlying partially observable Markov decision process (POMDP). By applying stochastic optimization methods, such as policy rollout, the POMDP is solved non-myopically. The approximately optimal approach is formulated assuming a central processor. Subsequently, a distributed implementation is introduced that converges to the same results as given by the centralized implementation and requires less computational resources. The performance of the proposed approach for both centralized and distributed implementation is demonstrated through dynamic tracking scenarios.

AB - Radar Resource Management in a multi-sensor multi-target scenario is considered. A dynamic resource balancing algorithm is proposed which optimizes target task parameters assuming an underlying partially observable Markov decision process (POMDP). By applying stochastic optimization methods, such as policy rollout, the POMDP is solved non-myopically. The approximately optimal approach is formulated assuming a central processor. Subsequently, a distributed implementation is introduced that converges to the same results as given by the centralized implementation and requires less computational resources. The performance of the proposed approach for both centralized and distributed implementation is demonstrated through dynamic tracking scenarios.

KW - Radar Resource Management

KW - Distributed Sensor Network

KW - Constrained Optimization

KW - POMDP

M3 - Conference contribution

SN - 978-1-6654-1427-2

SP - 1

EP - 8

BT - 2021 IEEE 24th International Conference on Information Fusion (FUSION)

PB - IEEE

T2 - 2021 IEEE 24th International Conference on Information Fusion (FUSION)

Y2 - 1 November 2021 through 4 November 2021

ER -

Approximately Optimal Radar Resource Management for Multi-Sensor Multi-Target Tracking

Abstract

Conference

Bibliographical note

Keywords

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