A Cooperative Task Allocation Game for Multi-Target Imaging in Radar Networks

Wang, Dan; Li, Kaiming; Zhang, Qun; Lu, Xiaofei; Luo, Ying

doi:10.1109/jsen.2021.3049899

Cited by 10 publications

(2 citation statements)

References 24 publications

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“…Moreover, for the networked radar imaging resource scheduling problem, Reference [19] investigated the resource scheduling problem of distributed MIMO radar for multi-target imaging and solved the problem based on maximizing scheduling benefits. Furthermore, Reference [20] defined a cooperative game-theoretic framework for task assignment optimization in radar network multi-target imaging, achieving efficient distribution and scheduling of radar nodes to minimize total imaging duration. However, it is important to note that most existing research in this area assumes that the motion state of the target remains unchanged during the observation period, whereas, as the observation distance increases and the observation time lengthens, the motion state of the target will change during the observation period.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Resource Scheduling Algorithm for Multi-Target ISAR Imaging in Radar Systems

Yao,

Lou,

Wang

et al. 2024

Remote Sensing

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Inverse synthetic-aperture radar (ISAR) can achieve precise imaging of targets, which enables precise perception of battlefield information, and it has become one of the most important tasks for radar systems. In multi-target scenarios, a resource scheduling method is required to improve the sensing ability and the overall efficiency of a radar system due to the limited resources. Considering the motion state of the target will change as the observation distance increases and image defocusing can occur due to the prolonged coherence accumulation time and significant changes in the target’s motion state, the optimal observation period should be an important consideration factor in the resource scheduling method to further improve the imaging efficiency of radar system, which has not yet been involved in existing research. In this paper, we first derive the expressions of the target’s effective rotation angle and the equivalent rotation angular velocity and then define the target’s optimal observation period. Then, for multi-target imaging scenarios, we allocate pulse resources within a given time period based on sparse-aperture ISAR imaging technology. An adaptive radar resource scheduling algorithm for multi-target ISAR imaging is proposed, which prioritizes allocating resources based on the optimal observation periods for the targets. In the algorithm, a radar resource scheduling model for multi-target ISAR imaging is established, and a feedback-based closed-loop search optimization method is proposed to solve the model. Finally, the best scheduling strategy can be obtained, which includes imaging task duration and the pulse allocation sequence for each target. Simulation results validate the effectiveness of the algorithm.

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Section: Introductionmentioning

confidence: 99%

Adaptive Resource Scheduling Algorithm for Multi-Target ISAR Imaging in Radar Systems

Yao,

Lou,

Wang

et al. 2024

Remote Sensing

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“…Note that, the current work mainly focuses on searching task, tracking task and anti-jamming task, etc., while few work involves the imaging task. In our previous work, we have proposed several game-theoretic based task allocation methods for ISAR imaging in radar network [20][21]. However, the task scheduling problem for multi-target 3-D imaging is much more complicated and the previous work cannot be directly applied to the problem.…”

Section: Introductionmentioning

confidence: 99%

An Adaptive Task Scheduling Algorithm for 3-D Target Imaging in Radar Network

Qun

Wang

Luo

et al. 2022

Preprint

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An effective task scheduling method is the premise and guarantee for cooperative imaging in radar network. In this article, an adaptive task scheduling algorithm for three- dimensional (3-D) target imaging in radar network is investigated. The aim of our strategy is to achieve the multiple 3-D target imaging tasks with the minimal task time. Firstly, the 3-D target image can be reconstructed by high-resolution inverse imaging aperture radar (ISAR) images from three views, and the sparse imaging algorithm based on compressed sensing (CS) is adopted to acquire the ISAR images of the targets. Then, the adaptive task scheduling optimization model is constructed. Through the steps of target Information perception, radar selection and adjustment of imaging terminal time, the optimal task scheduling strategy is obtained and the resource utilization of radar network is significantly improved. Finally, the experiments highlight the effectiveness of our proposed task scheduling method.

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