Joint Optimization of Target Assignment and Resource Allocation for Multi-Target Tracking in Phased Array Radar Network

Shi, Chenguang; Ding, Lintao; Qiu, Wei; Wang, Fei; Zhou, Jianjiang

doi:10.1109/radarconf2043947.2020.9309151

Cited by 5 publications

(2 citation statements)

References 22 publications

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“…Meanwhile, with the development of systemic confrontation, multitarget systematic operation is an inevitable trend. It is of great significance to investigate the process and the mechanism of MRA tracking multi-targets [4,5]. Specifically, the transmit resource management of multiple radars system plays a key role in this research field, which is the focus of this paper [6][7][8][9].…”

Section: Introduction 1| Background and Literature Reviewmentioning

confidence: 99%

Low probability of intercept‐based cooperative node selection and transmit resource allocation for multi‐target tracking in multiple radars architecture

Ding

Shi

Wang

et al. 2022

IET Signal Processing

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A low probability of intercept (LPI)-based cooperative node selection and transmit resource allocation (CNS-TRA) strategy is proposed for multi-target tracking in multiple radars architecture (MRA). The key idea of the proposed CNS-TRA strategy is to coordinate the radar node selection and the transmit resource that is, dwell time, transmit power, and effective bandwidth allocation to improve the LPI performance, under the constraints of predefined target tracking accuracy requirement and several resource budgets. By incorporating the above controllable parameters, the Bayesian Cramér-Rao lower bound is calculated and used as the accuracy metric for target tracking. Subsequently, this paper develops a fast and effective two-stage-based solution methodology to solve the resulting non-convex and non-linear optimisation problem. Specifically, the optimisation problem can be decomposed into two sub-problems, that is, the radar node selection sub-problem and the transmit resource allocation sub-problem. The active-set method and the interior point approach are utilised to solve those two sub-problems, respectively. Simulation results demonstrate that the CNS-TRA strategy has superiority over other existing algorithms and can achieve better LPI performance for MRA.

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Section: Introduction 1| Background and Literature Reviewmentioning

confidence: 99%

Low probability of intercept‐based cooperative node selection and transmit resource allocation for multi‐target tracking in multiple radars architecture

Ding

Shi

Wang

et al. 2022

IET Signal Processing

Self Cite

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“…Despite great interest in recent research, in particular in China [1,2] micromanagement of sensors by centralized command and control drives possible inefficiencies and risk into operations. Tactical decision making and execution by headquarters usually fail to achieve the speed necessary to meet rapid changes.…”

Section: Introductionmentioning

confidence: 99%

Multi-Radar Tracking Optimization for Collaborative Combat

Nour¹,

Belhaj-Soullami²,

Buron³

et al. 2020

Preprint

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Smart Grids of collaborative netted radars accelerate kill chains through more efficient cross-cueing over centralized command and control. In this paper, we propose two novel reward-based learning approaches to decentralized netted radar coordination based on blackbox optimization and Reinforcement Learning (RL). To make the RL approach tractable, we use a simplification of the problem that we proved to be equivalent to the initial formulation. We apply these techniques on a simulation where radars can follow multiple targets at the same time and show they can learn implicit cooperation by comparing them to a greedy baseline.

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Cooperative Node Selection and Resource Allocation for Search and Track Applications in Radar Network

Shi

Salous

et al. 2023

Lecture Notes in Electrical Engineering

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Joint Optimization of Target Assignment and Resource Allocation for Multi-Target Tracking in Phased Array Radar Network

Cited by 5 publications

References 22 publications

Low probability of intercept‐based cooperative node selection and transmit resource allocation for multi‐target tracking in multiple radars architecture

Low probability of intercept‐based cooperative node selection and transmit resource allocation for multi‐target tracking in multiple radars architecture

Multi-Radar Tracking Optimization for Collaborative Combat

Cooperative Node Selection and Resource Allocation for Search and Track Applications in Radar Network

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