Optimal Resource Allocation for Multiple Target Tracking in Phased Array Radar Network

Dai, Jinhui; Yan, Junkun; Wang, Peng-Hui; Liu, Hongwei

doi:10.1109/iccais46528.2019.9074602

Cited by 3 publications

(2 citation statements)

References 13 publications

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“…In order to better utilise the potential of the MRA, it is necessary to propose a significant resource allocation strategy that can adaptively allocate the limited system resource. Recently, extensive works have been investigated for this purpose, which can be grouped into three categories: the system structure configuration [10][11][12][13], the transmit resource allocation [14][15][16][17][18][19], and the integration of the former two parts [20][21][22][23][24][25][26][27][28][29].…”

Section: Introduction 1| Background and Literature Reviewmentioning

confidence: 99%

“…The second aspect is to improve the low probability of intercept (LPI) performance while accomplishing a desired tracking accuracy requirement. For this goal, the authors in [17] develop a dwell time management approach for MTT in phased array radar (PAR) network, where the dwell time consumption can be minimised by employing CVX toolbox to solve the resulting problem. Ding et al [18] extend this work to joint dwell time and bandwidth optimisation case, which further improves LPI performance of radar network system.…”

Section: Introduction 1| Background and Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

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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