Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
Satellite hardware has reached a level of development that enables imaging satellites to realize applications in the area of meteorology and environmental monitoring. As the requirements in terms of feasibility and the actual profit achieved by satellite applications increase, we need to comprehensively consider the actual status, constraints, unpredictable information, and complicated requirements. The management of this complex information and the allocation of satellite resources to realize image acquisition have become essential for enhancing the efficiency of satellite instrumentation. In view of this, we designed a satellite auto mission planning system, which includes two sub-systems: the imaging satellite itself and the ground base, and these systems would then collaborate to process complicated missions: the satellite mainly focuses on mission planning and functions according to actual parameters, whereas the ground base provides auxiliary information, management, and control. Based on the requirements analysis, we have devised the application scenarios, main module, and key techniques. Comparison of the simulation results of the system, confirmed the feasibility and optimization efficiency of the system framework, which also stimulates new thinking for the method of monitoring environment and design of mission planning systems.
Czasopismo
Rocznik
Tom
Strony
59--70
Opis fizyczny
Bibliogr. 43 poz., rys., tab.
Twórcy
autor
- National University of Defense Technology, College of Information System and Management, Sanyi Road, Changsha 410073, China
autor
- National University of Defense Technology, College of Information System and Management, Sanyi Road, Changsha 410073, China
autor
- National University of Defense Technology, College of Information System and Management, Sanyi Road, Changsha 410073, China
autor
- National University of Defense Technology, College of Information System and Management, Sanyi Road, Changsha 410073, China
Bibliografia
- 1. J. C. Li, Album of world satellites in orbit, Beijing: National Defense Industry Press, 1-32. ( In Chinese) (2014).
- 2. B. N. Zhang, Survey on technical development of optical remote sensor on Chinese resource satellite, Chinese Space Science and Space Exploration Society of Professional Committee of Twenty-Sixth National Symposium on Space Exploration, 327-333(In Chinese) (2013).
- 3. S. Baek, S. Han, K. Cho, et al., “Development of a scheduling algorithm and GUI for autonomous satellite missions.” Acta Astronaut. 68(7), 1396-1402 (2011).
- 4. C. Pralet, G. Verfaillie. “Using Constraint Networks on Timelines to Model and Solve Planning and Scheduling Problems,” in ICAPS 8, 272-279 (2008).
- 5. L. Shumin, Z. Zheng, C. Kai-Yuan. Robust task scheduling of multi-satellite parallel test. Control Conference (CCC), 2011 30th Chinese. IEEE, 2152-2157 (2011).
- 6. S. Chien, R. Sherwood, D. Tran, et al., “Using autonomy flight software to improve science return on Earth Observing One,” J. Aeros. Comp, Inf. Commun. 2(4), 196-216 (2005).
- 7. S. J. Delany, S. Ontañón. Case-based reasoning research and development, 8th International Conference on CaseBased Reasoning. Washinton, USA. 20-23 (2009).
- 8. Z. Lian, Y. Tan, Y. Xu, Static and Dynamic Models of Observation Toward Earth by Agile Satellite Coverage, Proceedings of International Workshop on Planning and Scheduling for Space. Darmstadt, Germany: ESOC. 1-6 (2011).
- 9. R. L. Sherwood, S. Chien, D. Tran et al., Intelligent systems in space: the EO-1 Autonomous Sciencecraft. Pasadena, CA: Jet Propulsion Laboratory, National Aeronautics and Space Administration (2005).
- 10. H. J. You, W. N. Chen, X. G. Zhou et al., “Scalable architecture model for Spacecraft‘s electronic system,” Syst. Eng. Electron. 35(2):263-269 (2013) (In Chinese).
- 11. S. Laubach. Calculation of Operations Efficiency Factors for Mars Surface Missions, SpaceOps 2014, Pasadena, CA. AAIA, 1778-1786 (2014).
- 12. M. L. Pinedo, Scheduling: theory, algorithms, and systems. Springer Science & Business Media, 252-374 (2012).
- 13. R. Knight, G. Rabideau, S. Chien et al. “Casper: Space exploration through continuous planning,” Intelligent Systems, IEEE 16(5), 70-75 (2001).
- 14. S. Chien, D. Tran, G. Rabideau et al., “Planning Operations of the Earth Observing Satellite EO-1: Representing and reasoning with spacecraft operations constraints,” ( 2009).
- 15. F. Ip, J. M. Dohm, V. R. Baker et al., “Flood detection and monitoring with the Autonomous Sciencecraft Experiment onboard EO-1,” Remote Sens. Env. 101(4), 463-481 (2006).
- 16. G. Rabideau, R. Knight, S. Chien, A. Fukunaga, A. Govindjee, Iterative Repair Planning for Spacecraft Operations in the ASPEN System, International Symposium on Artificial Intelligence Robotics and Automation in Space, Noordwijk, The Netherlands, (1999).
- 17. B. Zhukov, E. Lorenz, D. Oertel et al., “Spaceborne detection and characterization of fires during the bi-spectral infrared detection (BIRD) experimental small satellite mission (2001–2004),” Remote Sens. Env. 100(1), 29-51 (2006).
- 18. G. Ruecker, E. Lorenz, A. A. Hoffmann et al., High Resolution Active Fire Monitoring for Global Change Analysis: The Upcoming FireBIRD Satellite Mission, The 5th International Wildland Fire Conference, Sun City, South Africa. 134-144 (2011).
- 19. W. Jiang, H. C. Hao, Y. J. Li, “Review of task scheduling research for the Earth observing satellites,” Syst. Eng. Electron. 35(9):1878-1885 (2013) ( In Chinese ).
- 20. M. A. Gleyzes, L. Perret, P. Kubik, “Pleiades system architecture and main performances,” Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci, 39: B1, 537-542 (2012).
- 21. D. Greslou, F. de Lussy, J. M. Delvit, et al., “Pleiades-HR innovative techniques for geometric image quality commissioning,” Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci, 39: B1, 543-547 (2012).
- 22. G. Beaumet, G. Verfaillie, M. C. Charmeau, “Autonomous planning for an agile earth-observing satellite,” in iSAIRAS, pp. 1-6, (2008).
- 23. M. K. Griffin, K. B. Hsiao-hua, D. Mandl et al., Cloud cover detection algorithm for EO-1 Hyperion imagery, AeroSense 2003. International Society for Optics and Photonics 483494 (2003).
- 24. Y. H. Guo. Research on the key technology of combining multiple types of EOSs with multiple types of data transmitting resources. Changsha: National University of Defense Technology, 2009. (In Chinese)
- 25. A. G. Davies, S. Chien, D. Tran et al., “The NASA Volcano Sensor Web, advanced autonomy and the remote sensing of volcanic eruptions: a review,” Geological Society, London, Special Publications 426, SP426. 3 (2015).
- 26. G. Beaumet, G. Verfaillie, M. C. Charmeau, “Feasibility of autonomous decision making on board an agile earth- observing satellite,” Comput. Intelligence, 27(1): 123-139, (2011).
- 27. D. Izzo, L. Pettazzi, “Autonomous and distributed motion planning for satellite swarm,” J. Guid. Control Dynam. 30(2), 449-459 (2007).
- 28. Y. Long, P. Wang, Z. Zhang et al., “Uplink Task Scheduling Model and Heuristic Algorithm of Satellite Navigation System,” Adv. Inf. Sci. Service Sci. 4(16), 450-461 (2012).
- 29. G. Beaumet, “Continuous planning for the control of an autonomous agile satellite,” ICAPS 2006, 13 (2006).
- 30. N. Chen, X. Wang, X. Yang, “A direct registry service method for sensors and algorithms based on the process model,” Comp. Geosci. 56, 45-55 (2013).
- 31. D. S. Qiu, J. J. Wang, C. B. Wu et al., “Emergency scheduling method of earth observation satellites based on task merging,” Syst. Eng. Electron. 35(7), 1430-1437 (2013) ( In Chinese).
- 32. S. Bernardini, M. Fox, D. Long, et al. Autonomous Search and Tracking via Temporal Planning, ICAPS. 481-489 (2013).
- 33. S. A. Chien, R. Knight, A. Stechert et al., Using Iterative Repair to Improve the Responsiveness of Planning and Scheduling, AIPS. 300-307 (2000).
- 34. G. Beaumet, G. Verfaillie, M. C. Charmeau, “Decisionmaking on-board an autonomous agile Earth-observing satellite,” ICAPS (SPARK) (2008).
- 35. A. Altinok, D. R. Thompson, B. Bornstein et al., “Real-Time Orbital Image Analysis Using Decision Forests, with a Deployment Onboard the IPEX Spacecraft,” J. Field Robot (2015).
- 36. M. Lemaître, G. Verfaillie, “Interaction between reactive and deliberative tasks for on-line decision-making”, in International Conference on Automated Planning and Scheduling, ICAPS’07 Workshop on Planning and Plan Execution for Real-World Systems, Providence, RI, USA (2007).
- 37. P. F. Maldague, A. Y. Ko, JIT planning: an approach to autonomous scheduling for space missions, Aerospace Conference, 1999. Proceedings. 1999 IEEE. IEEE, 1: 339349 (1999).
- 38. R. Knight, S. Chien, Producing Large Observation Campaigns Using Compressed Problem Representations, International Workshop on Planning and Scheduling for Space, Space Telescope Science Institute, Maryland (2006).
- 39. S. Chien, R. Knight, G. Rabideau, An empirical evaluation of the effectiveness of local search for replanning. Springer Berlin Heidelberg (2001).
- 40. E. Gat, “On three-layer architectures,” Artificial intelligence and mobile robots, 195: 210 (1998).
- 41. Adnan, F.A.F.; Hamylton, S.M.; Woodroffe, C.D., SurfSwash Interactions on a Low-Tide Terraced Beach, Journal of Coastal Research, SI75, 348-352 (2016).
- 42. D. R. Thompson, A. Altinok, B. Bornstein, et al., “Onboard machine learning classification of images by a cubesat in Earth orbit,” AI Matters, 4, 38-40 (2015).
- 43. Zieja, M; Wazny, M. A model for service life control of selected device systems. Polish Maritime Research, 21(2) 45-49 (2014).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-3600a6ce-2308-40a2-aa17-9093f98a0239