Game Model in Multi-Target Imaging Task Allocation

Liu, Xiaowen; Zhang, Qun; Liang, Bi-shuai; Liang, Jia; Zhang, Hui-Wei

doi:10.1109/apsar46974.2019.9048276

Cited by 1 publication

(1 citation statement)

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“…However, imaging needs to occupy most of the resources, so the reasonable allocation of imaging resources can save more resources for the radar to perform more tasks. [12][13][14] The model established in Ref. 15 optimizes resource allocation for multiobjective imaging tasks in radar networks, but it uses the traditional Rang-Doppler (RD) imaging algorithm, which, although effective for traditional algorithm, is not as superior as CS.…”

Section: Introductionmentioning

confidence: 99%

Resource scheduling algorithm optimization for multitarget inverse synthetic aperture radar imaging in radar network

Wang

Liao

Ouyang

et al. 2021

J. Appl. Rem. Sens.

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Aiming at optimizing the allocation problem of limited resources in a radar network, a resource scheduling algorithm combining pulse interleaving with preallocation is proposed for multitarget inverse synthetic aperture radar imaging. The imaging method adopts compressed sensing, which only needs to emit a small number of pulses so that we can set the algorithms to schedule the allocation of the pulses over a period of time. The authors point out the problem of pulse conflict, which is ignored in the process of the scheduling algorithm and proposes a preallocation method to avoid the occurrence of the conflict. Meanwhile, pulse interleaving is added to increase the positions of the dispatchable pulses. Moreover, the combined algorithm can perform adaptive scheduling on the radar time resource according to the feature parameters after target feature cognitive. Finally, the feasibility of the combined algorithm is verified by the simulation, and two performance indicators, the hit value rate and the pulse utilization rate, are improved by the proposed algorithm. © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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