Optimal Balancing of Multi-Function Radar Budget for Multi-Target Tracking Using Lagrangian Relaxation

Max Ian Schöpe; Hans Driessen; Alexander Yarovoy

Optimal Balancing of Multi-Function Radar Budget for Multi-Target Tracking Using Lagrangian Relaxation

Max Ian Schöpe, Hans Driessen, Alexander Yarovoy

Microwave Sensing, Signals & Systems

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

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Abstract

The radar resource management problem in a multitarget tracking scenario for multi-function radar is considered. To solve it, an optimal balancing of the sensor budget by applying Lagrangian relaxation and the subgradient method is proposed. In a time-invariant scenario it is shown that the proposed method will lead to balanced budgets based on track parameters like maneuverability and measurement uncertainty. Moreover, since real world applications quickly lead to time-varying scenarios, it is demonstrated how the approach can be extended to such cases. Furthermore the proposed method is compared with other budget assignment strategies. This paper is the first step into exploring optimal non-myopic solutions using a POMDP framework for surveillance radar applications involving detection, tracking and classification.

Original language	English
Title of host publication	2019 22nd International Conference on Information Fusion (FUSION)
Subtitle of host publication	Proceedings
Publisher	IEEE
Pages	1-8
Number of pages	8
ISBN (Electronic)	978-0-9964527-8-6
ISBN (Print)	978-1-7281-1840-6
Publication status	Published - 2020
Event	22nd International Conference on Information Fusion (FUSION 2019) - Shaw Centre, Ottawa, Canada Duration: 2 Jul 2019 → 5 Jul 2019

Conference

Conference	22nd International Conference on Information Fusion (FUSION 2019)
Abbreviated title	FUSION 2019
Country/Territory	Canada
City	Ottawa
Period	2/07/19 → 5/07/19

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
Lagrangian relaxation
Steady-state Kalman filter
Subgradient method

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https://ieeexplore.ieee.org/document/9011230Licence: Unspecified

Cite this

@inproceedings{fe517c68e1454ad48af102cfb6113982,

title = "Optimal Balancing of Multi-Function Radar Budget for Multi-Target Tracking Using Lagrangian Relaxation",

abstract = "The radar resource management problem in a multitarget tracking scenario for multi-function radar is considered. To solve it, an optimal balancing of the sensor budget by applying Lagrangian relaxation and the subgradient method is proposed. In a time-invariant scenario it is shown that the proposed method will lead to balanced budgets based on track parameters like maneuverability and measurement uncertainty. Moreover, since real world applications quickly lead to time-varying scenarios, it is demonstrated how the approach can be extended to such cases. Furthermore the proposed method is compared with other budget assignment strategies. This paper is the first step into exploring optimal non-myopic solutions using a POMDP framework for surveillance radar applications involving detection, tracking and classification.",

keywords = "Radar Resource Management, Lagrangian relaxation, Steady-state Kalman filter, Subgradient method",

author = "Sch{\"o}pe, {Max Ian} and Hans Driessen and Alexander Yarovoy",

note = "Green Open Access added to TU Delft Institutional Repository {\textquoteleft}You share, we take care!{\textquoteright} – 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.; 22nd International Conference on Information Fusion (FUSION 2019), FUSION 2019 ; Conference date: 02-07-2019 Through 05-07-2019",

year = "2020",

language = "English",

isbn = "978-1-7281-1840-6",

pages = "1--8",

booktitle = "2019 22nd International Conference on Information Fusion (FUSION)",

publisher = "IEEE",

address = "United States",

}

Schöpe, MI, Driessen, H & Yarovoy, A 2020, Optimal Balancing of Multi-Function Radar Budget for Multi-Target Tracking Using Lagrangian Relaxation. in 2019 22nd International Conference on Information Fusion (FUSION): Proceedings. IEEE, pp. 1-8, 22nd International Conference on Information Fusion (FUSION 2019), Ottawa, Ontario, Canada, 2/07/19. <https://ieeexplore.ieee.org/document/9011230>

Optimal Balancing of Multi-Function Radar Budget for Multi-Target Tracking Using Lagrangian Relaxation. / Schöpe, Max Ian; Driessen, Hans ; Yarovoy, Alexander.
2019 22nd International Conference on Information Fusion (FUSION): Proceedings. IEEE, 2020. p. 1-8.

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

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AU - Schöpe, Max Ian

AU - Driessen, Hans

AU - Yarovoy, Alexander

N1 - 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.

PY - 2020

Y1 - 2020

N2 - The radar resource management problem in a multitarget tracking scenario for multi-function radar is considered. To solve it, an optimal balancing of the sensor budget by applying Lagrangian relaxation and the subgradient method is proposed. In a time-invariant scenario it is shown that the proposed method will lead to balanced budgets based on track parameters like maneuverability and measurement uncertainty. Moreover, since real world applications quickly lead to time-varying scenarios, it is demonstrated how the approach can be extended to such cases. Furthermore the proposed method is compared with other budget assignment strategies. This paper is the first step into exploring optimal non-myopic solutions using a POMDP framework for surveillance radar applications involving detection, tracking and classification.

AB - The radar resource management problem in a multitarget tracking scenario for multi-function radar is considered. To solve it, an optimal balancing of the sensor budget by applying Lagrangian relaxation and the subgradient method is proposed. In a time-invariant scenario it is shown that the proposed method will lead to balanced budgets based on track parameters like maneuverability and measurement uncertainty. Moreover, since real world applications quickly lead to time-varying scenarios, it is demonstrated how the approach can be extended to such cases. Furthermore the proposed method is compared with other budget assignment strategies. This paper is the first step into exploring optimal non-myopic solutions using a POMDP framework for surveillance radar applications involving detection, tracking and classification.

KW - Radar Resource Management

KW - Lagrangian relaxation

KW - Steady-state Kalman filter

KW - Subgradient method

M3 - Conference contribution

SN - 978-1-7281-1840-6

SP - 1

EP - 8

BT - 2019 22nd International Conference on Information Fusion (FUSION)

PB - IEEE

T2 - 22nd International Conference on Information Fusion (FUSION 2019)

Y2 - 2 July 2019 through 5 July 2019

ER -

Optimal Balancing of Multi-Function Radar Budget for Multi-Target Tracking Using Lagrangian Relaxation

Abstract

Conference

Bibliographical note

Keywords

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Cite this