立方星编队或星座构成分布式空间传感器网络，可提高立方星执行复杂空间任务的能力。然而立方星易发生故障，其故障时间不确定性也导致了传感器网络性能的不稳定，这凸显了对立方星网络进行在轨维护的重要性。考虑立方星传感器网络的功能维持问题，描述了一种网络维护架构，通过定期发射、在轨备份立方星以及时更换故障立方星，从而提高网络对单星随机失效事件的快速响应与恢复能力。建立了该架构的运行成本模型，包括固定成本、储存成本和短缺成本。收集整理了真实的立方星寿命数据，并使用最大化拟合优度参数估计方法得到最优立方星寿命的随机模型。采用基于蒙特卡罗仿真的遗传算法优化备用立方星的补给时刻和补给数量，在备份成本与系统性能下降所带来的损失之间进行权衡，使得系统的综合收益最优。
CubeSat formations or constellations can form distributed space sensor networks, enhancing the ability of the CubeSat to execute sophisticated space missions. However, CubeSats are prone to malfunction, and the uncertainty of their failure time causes the performance instability of the sensor network, highlighting the importance of on-orbit maintenance of CubeSat networks. In view of the function maintenance of space CubeSat sensor networks, a maintenance architecture is described. It can improve the rapid responsiveness and recovery capability to a single CubeSat fault event of the network by launching CubeSats regularly, making backup CubeSats on the orbit and replacing damaged CubeSats in time. The operation cost model of this architecture is built, involving fixed costs, storage costs and shortage costs. The practical CubeSat lifetime data is collected to acquire the optimal CubeSat lifetime stochastic model with the parameter estimation optimization method of maximizing the coefficient of determination. The supply time and quantity of spare CubeSats are optimized by a Monte-Carlo-simulation-based genetic algorithm. This solution is a trade-off between the costs of backups and the losses caused by the system performance decline, finally achieving an optimal comprehensive income.
[1] HEIDT H, PUIG-SUARI J, MOORE A, et al. CubeSat:A new generation of picosatellite for education and industry low-cost space experimentation[C]//14th Annual AIAA/USU Conference on Small Satellites. Reston:AIAA, 2000.
[2] SHIROMA W A, MARTIN L K, AKAGI J M, et al. CubeSats:A bright future for nanosatellites[J]. Open Engineering, 2011, 1(1):9-15.
[3] CHIN A, COELHO R, NUGENT R, et al. CubeSat:The pico-satellite standard for research and education[C]//AIAA SPACE 2008 Conference & Exposition. Reston:AIAA, 2008.
[4] ZHANG H, GURFIL P. Nanosatellite cluster keeping under thrust uncertainties[J]. Journal of Guidance, Control, and Dynamics, 2014, 37(5):1406-1414.
[5] POGHOSYAN A, GOLKAR A. CubeSat evolution:Analyzing CubeSat capabilities for conducting science missions[J]. Progress in Aerospace Sciences, 2017, 88:59-83.
[6] Planet Labs Inc. Planet imagery and archive[EB/OL].[2019-11-01]. https://www.planet.com/products/planet-imagery/.
[7] PERAL E, TANELLI S, HADDAD Z, et al. Raincube:A proposed constellation of precipitation profiling radars in CubeSat[C]//2015 IEEE International Geoscience and Remote Sensing Symposium. Piscataway:IEEE Press, 2015:1261-1264.
[8] CHEN H R, LIU J K, LONG L, et al. Lunar far side positioning enabled by a CubeSat system deployed in an Earth-Moon halo orbit[J]. Advances in Space Research, 2019, 64(1):28-41.
[9] BANDYOPADHYAY S, FOUST R, SUBRAMANIAN G P, et al. Review of formation flying and constellation missions using nanosatellites[J]. Journal of Space and Rockets, 2016, 53(3):567-578.
[10] WEN C X, ZHANG H, GURFIL P. Orbit injection considerations for cluster flight of nanosatellites[J]. Journal of Spacecraft and Rockets, 2014, 52(1):196-208.
[11] VILLELA T, COSTA C A, BRANDÃO A M, et al. Towards the thousandth CubeSat:A statistical overview[J]. International Journal of Aerospace Engineering, 2019(3):1-13.
[12] RIESING K. Orbit determination from two line element sets of ISS-deployed cubesats[C]//29th Annual AIAA/USU Conference on Small Satellites. Reston:AIAA, 2015.
[13] 项军华, 张育林. 基于卫星可靠度和MTTR星座空间备份策略设计[J]. 系统工程与电子技术, 2007, 29(9):1576-1580. XIANG J H, ZHANG Y L. Design of spatial backup strategy for constellation based on satellite reliability and MTTR[J]. Systems Engineering and Electronics, 2007, 29(9):1576-1580(in Chinese).
[14] DU JONCHAY T S, HO K. Impact evaluation of an orbital depot on on-orbit servicing infrastructures dedicated to modularized earth-orbiting platforms[J]. Acta Astronautica, 2017, 132:192-203.
[15] 胡敏, 宋旭民, 杨雪榕. 基于Petri网的Walker导航星座备份策略研究[J]. 航天器工程, 2017, 26(2):14-21. HU M, SONG X M, YANG X R. Research on spare stratege of Walker navigation constellation based on Petri net[J]. Spacecraft Engineering, 2017, 26(2):14-21(in Chinese).
[16] ZHANG H, MENG D B, ZONG Y Y, et al. A modeling and analysis strategy of constellation availability using on-orbit and ground added launch backup and its application in the reliability design for a remote sensing satellite[J]. Advances in Mechanical Engineering, 2018, 10(4):1-6.
[17] GU J Y, ZHANG G Q, LI K W. Efficient aircraft spare parts inventory management under demand uncertainty[J]. Journal of Air Transport Management, 2015, 42:101-109.
[18] CASTET J F, SALEH J H. Satellite and satellite subsystems reliability:Statistical data analysis and modeling[J]. Reliability Engineering & System Safety, 2009, 94(11):1718-1728.
[19] GUO J, MONAS L, GILL E. Statistical analysis and modelling of small satellite reliability[J]. Acta Astronautica, 2014, 98(1):97-110.
[20] CASTET J F, SALEH J H. Satellite reliability:Statistical data analysis and modeling[J]. Journal of Spacecraft and Rockets, 2009, 46(5):1065-1076.
[21] CROWDER M J, KIMBER A C, SMITH R L, et al. Statistical analysis of reliability data[M]. London:Routledge,2017:16-27.
[22] ERIK K. Nanosats database[EB/OL].[2018-11-01]. https://www.nanosats.eu/.
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