Multi-Sensor Planning and Scheduling of Dual Unmanned Flight Platforms

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Multi-Sensor Planning and Scheduling of Dual Unmanned Flight Platforms

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[1]ZHAO Kun,SUI Xudong,LIANG Jing,et al.Multi-Sensor Planning and Scheduling of Dual Unmanned Flight Platforms[J].Journal of Zhengzhou University (Engineering Science),2023,44(04):67-73.[doi:10.13705/j.issn.1671-6833.2023.04.007]

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Journal of Zhengzhou University (Engineering Science)[ISSN 1671-6833/CN 41-1339/T] Volume: 44卷 Number of periods: 2023 04 Page number: 67-73 Column: Public date: 2023-06-01

Title:: Multi-Sensor Planning and Scheduling of Dual Unmanned Flight Platforms

Author(s):: ZHAO Kun¹; SUI Xudong²; LIANG Jing²; YUE Caitong²; LI Gongping²; YU Kunjie²; 1.27th Institute of China Electronics Technology Group Corporation, Zhengzhou 450001, Henan, 2.School of Electrical and Information Engineering, Zhengzhou University, 450001, Zhengzhou, Henan

Keywords:: dual unmanned flight platforms; sensor scheduling; collaborative work; capture target; task migration

CLC:: TP212；O231

DOI:: 10.13705/j.issn.1671-6833.2023.04.007

Abstract:: The multi-sensor scheduling problem of dual unmanned flight platforms has a complex coupling relationship, and how to reasonably match flight segments, sensors and targets is an intricate part of the problem. To solve the multi-sensor scheduling problem of dual unmanned flight platforms, firstly, this paper proposes a flight segment task allocation mechanism, which assigns tasks through the position relationship between the flight segment and the target. This mechanism can effectively split the tasks and solve the task coupling problem of the two platforms. Secondly, pre-processing targets and sensors are carried out to identify scarce sensor resources and independent targets in advance to guide subsequent scheduling matching. Then, sensor-target matching is carried out to plan the scheduling of sensors based on the task revenue. The scheduling of conflicting segments is adjusted according to the availability of sensor resources. Finally, task migration is carried out for targets who still need to complete their assigned tasks. The available free sensors in the corresponding flight segments are matched according to the target task remaining to improve the task revenue. In order to verify the effectiveness of the proposed algorithm in this paper, existing algorithms were compared through simulation experiments on 10 test problems. The experimental results show that this algorithm outperforms existing algorithms in task revenue and stability with a significant reduction in running time.

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Last Update: 2023-07-01