面向对地成像观测任务的高空飞艇应急调度

Abstract

Abstract: The main constraints for the scheduling of a high-altitude airship (HAA) for imaging tasks in an emergency environment are analyzed, and a constrain satisfaction problem (CSP) model is built taking task benefit (TB) and road distance as optimization objectives. Specifically, considering the swinging capability of reconnaissance sensors, meta tasks are composed within the constraint of view coverage and resolution. In addition, this paper proposes the concepts of meta task and composite task, and then provides a composition method and its steps. The HAA scheduling task is divided into a main problem (task ranking) and a sub-problem (route choosing), which are employed in our proposed improved particle swarm optimization (IPSO) algorithm and key node search (KNS) algorithm to solve the scheduling issue. Meanwhile, such relevant operations as encoding, decoding, movement, chaos initialization and tabu search (TS) strategy, are introduced in detail. Through extensive simulation experiments, the effectiveness of the proposed algorithm is sufficiently verified.

Key words: high-altitude airship, scheduling, imaging reconnaissance, PSO algorithm, task composition, chaos

CLC Number:

V274
TP183

HE Chuan, QIU Dishan, XU Guang, ZHU Xiaomin. Emergency Scheduling of Earth-observing Imaging Tasks on High-altitude Airships[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2012, 33(11): 2082-2092.

References

[1] Guzik T G, Besse S, Calongne A, et al. Development of the high altitude student platform. Advances in Space Research, 2008, 42(10): 1704-1714.
[2] Gan X H, Guo Y. Introduction to airship technology. Beijing: National Defense Industry Press, 2005: 139-144. (in Chinese) 甘晓华, 郭颖. 飞艇技术概论. 北京: 国防工业出版社, 2005: 139-144.
[3] Thornton J. Broadband communications from a high-altitude platform: the European Helinet programme. Electronics & Communication Engineering Journal, 2001, 13(3): 138-144.
[4] Sdmidt D K, Stevents J, Roney J. Near-space station-keeping performance of a large high-altitude notional airship. Journal of Aircraft, 2007, 44(2): 611-615.
[5] Yu B, Yang Z Z, Yao B Z. A hybrid algorithm for vehicle routing problem with time windows. Expert Systems with Applications, 2011, 38(1): 435-441.
[6] Zhu Y H, Zhen T. Hybrid ant colony algorithm based on vehicle routing problem with time windows. International Conference on Information Engineering. Taiyuan: IEEE Computer Society, 2009: 50-53.
[7] Abel G N, John A B. An improved multi-objective evolutionary algorithm for the vehicle routing problem with time windows. Computers and Operations Research, 2011, 38(1): 287-300.
[8] Zhang L M, Lin Y H, Yang G F, et al. Emergency resources scheduling based on adaptively mutate genetic algorithm. Computers in Human Behavior, 2011, 27(5): 1493-1498.
[9] Gan Y, Qiao Y H, Jin B H. Research of multi-stage emergency resource scheduling model. International Conference on Emergency Management and Management Sciences. Beijing: Association for Computing Machinery, 2010: 306-309.
[10] He C, Zhu X M, Guo H, et al. Rolling-horizon scheduling for energy constrained distributed real-time embedded systems. Journal of Systems and Software, 2012, 85(4): 780-794.
[11] Li J F, Yao F, Bai B C, et al. A decomposition-based algorithm for imaging satellites scheduling problem. International Conference on Information Engineering and Computer Science. Wuhan: IEEE Computer Society, 2009: 1-6.
[12] Yao F, Li J F, Bai B C, et al. Earth observation satellites scheduling based on decomposition optimization algorithm. International Journal of Image, Graphics and Signal, 2010, 2(1): 10-18.
[13] Bai B C, He R J, Li J F, et al. Imaging satellite observation scheduling with task merging. Acta Aeronautica et Astronautica Sinica, 2009, 30(11): 2165-2171. (in Chinese) 白保存, 贺仁杰, 李菊芳, 等. 考虑任务合成的成像卫星调度问题. 航空学报, 2009, 30(11): 2165-2171.
[14] Hu X H, Ouyang J C, Yang Z H, et al. An IPSO algorithm for grid task scheduling based on satisfaction rate. Proceedings of the 2009 International Conference on Intelligent Human-Machine Systems and Cybernetics. Hangzhou: IEEE Computer Society, 2009: 262-265.
[15] Fang H Q, Chen L, Shen Z Y. Application of an improved PSO algorithm to optimal tuning of PID gains for water turbine governor. Energy Conversion and Management, 2011, 52(4): 1763-1770.
[16] Zhang C S, Ning J X, Lu S, et al. A novel hybrid differential evolution and particle swarm optimization algorithm for unconstrained optimization. Operations Research Letters, 2009, 37(2): 117-122.
[17] Yan P, Ding M Y, Zhou C P. On-line real-time multiple-mission route planning for air vehicle. Acta Aeronautica et Astronautica Sinica, 2004, 25(5): 485-489. (in Chinese) 严平, 丁明跃, 周成平. 飞行器多任务在线实时航迹规划. 航空学报, 2004, 25(5): 485-489.
[18] Zheng C, Ding M, Zhou C. Real-time route planning for unmanned air vehicle with an evolutionary algorithm. International Journal of Pattern Recognition and Artificial Intelligence, 2003, 17(1): 63-81.
[19] Szczerba R J, Galkowski P, Glickstein I S, et al. Robust algorithm for real-time route planning. IEEE Transactions on Aerospace and Electronic System, 2000, 36(3): 869-878.
[20] Chang Y H, Hou Y C. Dynamic programming decision path encoding of genetic algorithms for production allocation problems. Computers and Industrial Engineering, 2008, 54(1): 879-886.
[21] Lin B M T, Lu C Y, Shyu S J, et al. Development of new features of ant colony optimization for flowshop scheduling. International Journal of Production Economics, 2008, 112(2): 742-755.
[22] Li M, Li W, Yang C W. An improved cooperative PSO algorithm. Proceedings of the 8th World Congress on Intelligent Control and Automation. Jinan: Institute of Electrical and Electronics Engineers Inc., 2010: 3256-3260.

Emergency Scheduling of Earth-observing Imaging Tasks on High-altitude Airships

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments

[1]	Feng HE, Li ZHANG, Sifan YU, Xuan ZHOU. Schedulability analysis for multi-window partition based on network calculus model [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2023, 44(2): 326581-326581.
[2]	SUN Gang, PENG Shuang, CHEN Hao, WU Jiangjiang, LI Jun. Multi-objective optimization method oriented to integrated scenario of TT & C resources and data transmission resources [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(9): 326114-326114.
[3]	LUO Zexiong, QU Guoyuan, YAN Long, TANG Xueqian. A scheduling table generation method for time-triggered flows based on importance sampling [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(3): 325209-325209.
[4]	LIU Fang, CHENG Mowen, CHEN Lizhi. Anti-blind estimation transmission method for chaotic DSSS signals [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(2): 325108-325108.
[5]	ZHANG Ruipeng, FENG Yanxiang, YANG Yikang. Hybrid particle swarm algorithm for multi-UAV cooperative task allocation [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(12): 326011-326011.
[6]	WAN Bing, SU Xichao, GUO Fang, HAN Wei, LIANG Yong. Proactive robust scheduling of aircraft carrier flight deck operations with uncertain activity durations [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(12): 325971-325971.
[7]	ZHAO Huan, GAO Zhenghong, XIA Lu. Efficient robust aerodynamic design optimization method for high-speed NLF airfoil [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(1): 124894-124894.
[8]	ZHANG Guobin, ZHANG Qingbin, FENG Zhiwei, CHEN Qingquan, YANG Tao. Uncertainty analysis on binding force of hose-drogue aerial refueling [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021, 42(9): 224517-224517.
[9]	HE Feng, LI Ershuai, ZHOU Xuan, LI Haoruo, GONG Zijie. Design optimization and evaluation method for time-triggered communication scheduling in airborne networks [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021, 42(7): 324258-324258.
[10]	SUN Gang, CHEN Hao, PENG Shuang, DU Chun, LI Jun. Multi-objective optimization algorithm for satellite range scheduling based on preference MOEA [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021, 42(4): 524475-524475.
[11]	ZHAO Jian, HUANG Yuechen, LI Haiyang, HE Xiangyue. Uncertainty optimization for return trajectory of vertical takeoff and vertical landing launch vehicle [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021, 42(11): 524829-524829.
[12]	CHEN Jiangtao, ZHANG Chao, LIU Xiao, ZHAO Hui, HU Xingzhi, WU Xiaojun. Uncertainty quantification analysis with sparse polynomial chaos method [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2020, 41(3): 123382-123382.
[13]	JIA Baohui, DENG Wanyi, WANG Yiqiang. Improvement of economical analysis model with three-indenture and three-echelon for civil aircraft repair level [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2020, 41(3): 323468-323468.
[14]	LIU Yiming, SHENG Wen, HU Bing, ZHANG Lei. Long time tracking beam scheduling and waveform optimization strategy for phased array radar [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2020, 41(3): 323519-323519.
[15]	XI Zhifei, XU An, KOU Yingxin, LI Zhanwu, YANG Aiwu. Target maneuver trajectory prediction based on Volterra series identified by improved particle swarm algorithm [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2020, 41(12): 324183-324183.