Cooperative Node Selection and Transmit Resource Allocation for Multi-Target Tracking in Multiple Radars Architecture

This paper puts forward a cooperative node selection and transmit resource allocation (CNS-TRA) strategy for multi-target tracking (MTT) in multiple radars architecture (MRA), whose objective is to improve the low probability of intercept (LPI) performance by jointly coordinating the radar node sche...

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Published inInternational Conference on Control, Automation and Information Sciences (Online) pp. 94 - 98
Main Authors Ding, Lintao, Shi, Chenguang, Zhou, Jianjiang, Yan, Junkun
Format Conference Proceeding
LanguageEnglish
Published IEEE 14.10.2021
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ISSN2475-7896
DOI10.1109/ICCAIS52680.2021.9624503

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Abstract This paper puts forward a cooperative node selection and transmit resource allocation (CNS-TRA) strategy for multi-target tracking (MTT) in multiple radars architecture (MRA), whose objective is to improve the low probability of intercept (LPI) performance by jointly coordinating the radar node scheduling, dwell time, transmit power and effective bandwidth of MRA subject to predefined target tracking accuracy requirement and several resource budgets. By incorporating the above controllable parameters, the Bayesian Cramér-Rao lower bound (BCRLB) 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 optimization problem. Simulation results demonstrate that the CNS-TRA strategy has superiority over other existing algorithms and can achieve better LPI performance for MRA.
AbstractList This paper puts forward a cooperative node selection and transmit resource allocation (CNS-TRA) strategy for multi-target tracking (MTT) in multiple radars architecture (MRA), whose objective is to improve the low probability of intercept (LPI) performance by jointly coordinating the radar node scheduling, dwell time, transmit power and effective bandwidth of MRA subject to predefined target tracking accuracy requirement and several resource budgets. By incorporating the above controllable parameters, the Bayesian Cramér-Rao lower bound (BCRLB) 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 optimization problem. Simulation results demonstrate that the CNS-TRA strategy has superiority over other existing algorithms and can achieve better LPI performance for MRA.
Author Ding, Lintao
Yan, Junkun
Zhou, Jianjiang
Shi, Chenguang
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Snippet This paper puts forward a cooperative node selection and transmit resource allocation (CNS-TRA) strategy for multi-target tracking (MTT) in multiple radars...
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StartPage 94
SubjectTerms Bandwidth
Bayesian Cramér-Ran lower bound (BCRLB)
Cooperative node selection and transmit resource allocation (CNS-TRA)
Measurement
multi-target tracking (MTT)
multiple radars architecture (MRA)
Radar clutter
Radar tracking
Resource management
Simulation
Target tracking
Title Cooperative Node Selection and Transmit Resource Allocation for Multi-Target Tracking in Multiple Radars Architecture
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