AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (6 MB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Open Access

Adaptive Dwell Scheduling Based on Dual-Side Time Pointers for Simultaneous Multi-Beam Radar

Siyu HengTing Cheng( )Jiaming SongZishu HeLuqing LiuYuanqing Wang
School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
Show Author Information

Abstract

Adaptive dwell scheduling is essential to achieve full performance for a simultaneous multi-beam radar system. The dwell scheduling for such a radar system considering desired execution time criterion is studied in this paper. The primary objective of this model is to achieve maximum scheduling gain and minimum scheduling cost while adhering to not only time, aperture, and frequency constraints, but also electromagnetic compatibility (EMC) constraint. The dwell scheduling algorithm is proposed to solve the above optimization problem, where several separation points are set on the timeline, so that each separator divides the scheduling interval into two sides. For the two sides, the dual-side time pointers are introduced, which move from the separator to both ends of the scheduling interval. The dwell tasks are analyzed in sequence at each analysis point based on their two-level synthetical priority. These tasks are then executed simultaneously by sharing the whole aperture under various constraints to accomplish multiple tasks concurrently. The above process is respectively conducted at each separator, and the final scheduling result is the one with the minimal cost among all. Simulation results prove that the proposed algorithm can achieve real-time dwell scheduling and outperform the existing algorithms in terms of scheduling performance.

References

[1]

C. Pell, Phased-array radars, IEE Rev., vol. 34, no. 9, p. 363, 1988.

[2]

A. J. Orman, C. N. Potts, A. K. Shahani, and A. R. Moore, Scheduling for a multifunction phased array radar system, Eur. J. Oper. Res., vol. 90, no. 1, pp. 13–25, 1996.

[3]
X. Zhi, K. Huang, and L. Ran, Design of simultaneous multi-beam forming method, in Proc. 2022 IEEE MTT-S International Microwave Biomedical Conference (IMBioC), Suzhou, China, 2022, pp. 40–42.
[4]

J. Yan, H. Liu, B. Jiu, B. Chen, Z. Liu, and Z. Bao, Simultaneous multibeam resource allocation scheme for multiple target tracking, IEEE Trans. Signal Process., vol. 63, no. 12, pp. 3110–3122, 2015.

[5]

J. Yan, B. Jiu, H. Liu, B. Chen, and Z. Bao, Prior knowledge-based simultaneous multibeam power allocation algorithm for cognitive multiple targets tracking in clutter, IEEE Trans. Signal Process., vol. 63, no. 2, pp. 512–527, 2015.

[6]

J. Yan, W. Pu, J. Dai, H. Liu, and Z. Bao, Resource allocation for search and track application in phased array radar based on Pareto bi-objective optimization, IEEE Trans. Veh. Technol., vol. 68, no. 4, pp. 3487–3499, 2019.

[7]

J. B. Lu, W. D. Hu, and W. X. Yu, Study on real-time task scheduling of multifunction phased array radars, (in Chinese), Acta Electronica Sinica, vol. 34, no. 4, pp. 732–736, 2006.

[8]

H. Zhang, J. Xie, B. Zong, W. Lu, and C. Sheng, Dynamic priority scheduling method for the air-defence phased array radar, IET Radar Sonar Navig., vol. 11, no. 7, pp. 1140–1146, 2017.

[9]

H. S. Mir and A. Guitouni, Variable dwell time task scheduling for multifunction radar, IEEE Trans. Automat. Sci. Eng., vol. 11, no. 2, pp. 463–472, 2014.

[10]

D. Liu, Y. Zhao, X. Cai, B. Xu, and T. Qiu, Adaptive scheduling algorithm based on CPI and impact of tasks for multifunction radar, IEEE Sens. J., vol. 19, no. 23, pp. 11205–11212, 2019.

[11]

G. Zeng, J. Lu, and W. Hu, Research on adaptive scheduling algorithm for multifunction phased array radar, (in Chinese), Modern Radar, vol. 6, no. 6, pp. 14–18, 2004.

[12]
Z. Qu, Z. Ding, and P. Moo, Dual-side scheduling for radar resource management, in Proc. 2020 21st Int. Radar Symp. (IRS), Warsaw, Pakistan, 2020, pp. 260–263.
[13]

T. Cheng, Z. He, and T. Tang, Dwell scheduling algorithm for multifunction phased array radars based on the scheduling gain, J. Syst. Eng. Electron., vol. 19, no. 3, pp. 479–485, 2008.

[14]

Q. Tan, T. Cheng, and X. Li, Online adaptive dwell scheduling based on dynamic template for PAR, J. Syst. Eng. Electron., vol. 32, no. 5, pp. 1119–1129, 2021.

[15]

T. Cheng, Z. Li, Q. Tan, S. Wang, and C. Yue, Real-time adaptive dwell scheduling for digital array radar based on virtual dynamic template, IEEE Trans. Aerosp. Electron. Syst., vol. 58, no. 4, pp. 3197–3208, 2022.

[16]

H. Zhang, J. Xie, J. Ge, J. Shi, and Z. Zhang, Hybrid particle swarm optimization algorithm based on entropy theory for solving DAR scheduling problem, Tsinghua Science and Technology, vol. 24, no. 3, pp. 282–290, 2019.

[17]

H. Zhang, J. Xie, J. Ge, Z. Zhang, and B. Zong, A hybrid adaptively genetic algorithm for task scheduling problem in the phased array radar, Eur. J. Oper. Res., vol. 272, no. 3, pp. 868–878, 2019.

[18]
M. Shaghaghi and R. S. Adve, Task selection and scheduling in multifunction multichannel radars, in Proc. IEEE Radar Conf. (RadarConf), Seattle, WA, USA, 2017, pp. 969–974.
[19]
L. Xu and T. Zhang, Reinforcement learning based dynamic task scheduling for multifunction radar network, in Proc. IEEE Radar Conf. (RadarConf20), Florence, Italy, 2020, pp. 1–5.
[20]
T. George, K. Wagner, and P. Rademacher, Deep Q-network for radar task-scheduling problem, in Proc. IEEE Radar Conf. (RadarConf22), New York, NY, USA, 2022, pp. 1–5.
[21]
Z. Qu, Z. Ding, and P. Moo, A neural network based algorithm selector for radar task scheduling, in Proc. IEEE 19th Int. Conf. Cognitive Informatics & Cognitive Computing (ICCI*CC), Beijing, China, 2020, pp. 119–124.
[22]

J. Chen, Z. Tian, L. Wang, W. Zhang, and J. Cao, Adaptive simultaneous multi-beam dwell scheduling algorithm for multifunction phased array radars, J. Inf. Comput. Sci., vol. 8, no. 14, pp. 3051–3061, 2011.

[23]
G. Xue, Z. Du, W. Wang, and L. Hu, Multi-beam dwell adaptive scheduling algorithm for helicopter-borne radar, in Proc. IEEE 7th Joint Int. Information Technology and Artificial Intelligence Conference, Chongqing, China, 2014, pp. 401–404.
[24]

C. Chen, X. Ma, R. Yang, and W. Cheng, Task scheduling based on aperture partition for multifunctional electronic system, (in Chinese), Journal of Air & Space Early Warning Research, vol. 26, no. 6, pp. 412–418, 2012.

[25]

W. C. Qi, R. J. Yang, X. B. Li, X. Y. Chen, and W. Cheng, Research on task scheduling algorithm for multifunction integrated radar, Radar Sci. Technol., vol. 10, pp. 150–155, 2012.

[26]

L. Huang, Y. Zhang, Q. Li, C. Pan, and J. Song, Task-scheduling scheme based on greedy algorithm in integrated radar and communication systems, (in Chinese), The Journal of Engineering, vol. 2019, no. 19, pp. 5864–5867, 2019.

[27]

X. Zhu, R. Yang, X. Li, and K. Yuan, Multifunctional integrated system resource scheduling based on improved GA-PSO, (in Chinese), Journal of Air & Space Early Warning Research, vol. 35, no. 3, pp. 202–206, 2021.

[28]

S. Heng, T. Cheng, Z. He, Y. Wang, and Z. Li, Adaptive dwell scheduling for simultaneous multi-beam radar system based on array element selection with different polarization characteristics, Digit. Signal Process., vol. 140, p. 104093, 2023.

[29]

J. Rong, F. Liu, Y. Miao, H. Zhu, and C. Wu, Adaptive task scheduling algorithm for multifunction integrated system with joint radar–communications waveform, Electronics, vol. 12, no. 7, p. 1560, 2023.

Tsinghua Science and Technology
Pages 1190-1200
Cite this article:
Heng S, Cheng T, Song J, et al. Adaptive Dwell Scheduling Based on Dual-Side Time Pointers for Simultaneous Multi-Beam Radar. Tsinghua Science and Technology, 2025, 30(3): 1190-1200. https://doi.org/10.26599/TST.2023.9010161

26

Views

1

Downloads

0

Crossref

0

Web of Science

0

Scopus

0

CSCD

Altmetrics

Received: 03 August 2023
Revised: 21 December 2023
Accepted: 24 December 2023
Published: 30 December 2024
© The Author(s) 2025.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).

Return