面向效能优化的复杂多卫星系统综合建模与仿真方法研究
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摘要
随着信息时代的来临,构建综合性的空间信息获取系统对于社会发展和国家安全具有重大战略意义。而智能化的多卫星分布式自主协同工作,将是此系统的主要运行模式。如何分析、评估和优化其总体效能,以寻求最满意设计方案,是迫切需要研究的重要课题。
论文分析指出,唯有采用普适性的顶层分析和优化设计框架,才能够有效解决面临的种种复杂性问题。而基于进化计算的优化方法,采用自适应随机搜索全局优化技术,具有广泛的适应性和包容性;基于多Agent的建模与仿真方法,则能够胜任复杂智能系统的综合效能仿真分析任务。为此,提出采用基于进化计算的仿真优化设计框架,并以对地观测多卫星系统为主要研究对象,重点对其效能分析方法、效能测度的确定及其求解模型、综合建模与仿真方法及相应软件的研制等方面展开了研究与实践。
首先,研究了多卫星系统具有的诸多复杂性特征;分析和归纳了多种典型构成形态;从时空、物理和功能特性等方面,研究了多颗卫星之间的分布与协同特性;对智能化自主协同运行多卫星系统的总体功能、特性、实现机制及其组织结构进行了分析。
然后,对一般性系统效能分析的几种主要方法进行了简要述评,提出了基于仿真的多卫星系统效能分析方法的总体框架。遵循此框架,界定了多卫星系统的层次结构;就复杂大系统中子系统效能的分析方法进行了讨论,给出两种基本方法:任务要求分解法和全系统效能敏感性分析法;提出了系统信息获取的四元组效能测度:内容、范围、质量和时效性,并将其具体化为遥感信息获取的空间(Space)、频谱(Spectrum)、能量(Energy)、时间(Time)(简称SSET)四维空间的相应测度。
接着,提出了离散化SSET空间的信息粒模型,给出了单个遥感器信息获取容量的计算模型,并对多卫星系统的时间、空间、频谱和能量维信息容量进行了分析;面向效能分析,提出了“物理覆盖”、“有效覆盖”、“充分信息量”等概念,并通过一典型示例系统,给出了基于仿真的效能测度求解方法及其基本模型;针对系统覆盖区域的非规则性,设计和实现了“池中投石法”、“油环点火法”和“逐步吸收法”等基于仿真的覆盖区域通用求解算法。
分析了复杂系统可靠性模型和可靠度综合计算的特点,提出了复合逻辑树(Composite Logic Tree Model,简称CLTM)综合建模方法及其可靠度递归综合算法,并设计和实现了相应的软件系统,论文对其设计思想、总体结构、主要功能及其实现机制进行了阐述。
此后,主要针对复杂多卫星系统的综合建模与仿真方法展开了研究。首先分析指出,所建模型应为分解结构描述水平上的多学科混合异构层次化系统整体同构模型。分析了面向对象的建模与仿真方法对此提供的支持机制及其局限性,提出了基于多Agent/Object的整体建模与仿真方法,并给出其总体框架。然后,分别就Object与Agent共存机制、实体属性和行为的确定原则、基于进化计算的多学科优化对系统整体建模的要求、Agent/Object模型粒度确定等方面进行了讨论,分别给出了面向Object和面向Agent的解构与重构方法,
With the coming of information era, it is of great significance for society development and nation security to construct integrated space information acquisition system, which will operate in intelligent, distributed, collaborative, autonomous, multi-satellite mode. How to analyze, evaluate and optimize the integrated effectiveness of the complex systems to get the most satisfying one is a crucial problem which must be answered as early as possible.We made a detailed analysis and concluded that only if a general system analysis and optimization framework were adopted can we solve the multitudinous complex problems. The Evolutionary Computation (EC) based optimization methods, adopting self-adaptive stochastic searching technology for global optimization, possess comprehensive adaptability and compatibility, moreover, the Multi-Agent Based Modeling and Simulation (MABMS) methods are competent for analyzing the integrated effectiveness of complex intelligent systems. So, we presented an EC based simulation optimization design framework for Multi-Satellite Systems (MSSs). Under the framework, emphasizing on earth observation MSSs, we have done some research mainly to propose effective methods for system effectiveness analysis, establish Measures of Effectiveness (MoEs) and their solving models, set forth integrated Modeling and Simulation (M&S) methods, and construct corresponding M&S software environment.First, we investigated the various complexity characteristics existing in MSSs in detail, analyzed and induced typical composing configuration of MSSs, explored their distribution and collaboration relationships from the aspects of space, time, physics and function, and analyzed the overall functions, main characteristics, implementation mechanisms and organization structures of MSSs operating in the intelligent, autonomous, collaborative mode.Then, we reviewed briefly several main general methods for effectiveness analysis, and put forward the overall framework of effectiveness analysis methods based on M&S. According to the framework, we defined the hiberarchy of MSSs, discussed how to analyze the effectiveness of the subsystems in System of Systems and gave two basic methods: mission requirements decomposing and effectiveness sensitivity analysis of holistic system, set forth the four-element group of MoEs for information acquisition: Content, Area, Quality, Response time, and concretized them into corresponding MoEs in four-dimension space (Space, Spectrum, Energy, Time, SSET for short) of information acquisition by remote sensing.And then, we put forward an information grid model in discrete SSET space, deduced the models for computing total information capability of one single remote sensor, analyzed the information capability of MSSs in respective dimension of the SSET space, and set forth the following concepts: physical coverage, effective coverage, sufficient information quantity.
Through a typical example, we provided simulation based approaches and models to solve the MoEs for the system in detail. In order to search the points in or on the edge of the irregular coverage regions, we designed and implemented several general algorithms and named them throwing a stone into a pond, igniting an oiled hoop, absorbing step by step. The main ideas and contents of them are expounded.By analyzing the characteristics of the models and integrated computing for reliability of complex large systems, we set forth a new model named Composite Logic Tree Model (CLTM) and its modeling principles, and designed a recursive algorithm based on CLTM, and developed the corresponding software. The design ideas, architecture and main functions, implementation mechanisms of the software are introduced.And then, we pointed that, the models built for holistic system optimization should be integrated multidisciplinary isomorphic Hybrid Heterogeneous Hierarchical Models (HHHMs) in the description level of decomposing structure. By analyzing the supporting mechanisms and limits of the Object-Oriented M&S (OOMS) methodology, and the excellent characteristics of the MABMS methodology, we presented the Multi-Agent/Object (MAO) based M&S and optimization method framework for complex MSSs. Then, we discussed the mechanisms of Agent/Object co-existence, the principles of choosing the granularity of the Agents/Objects and defining their attributes and behaviors, the requirements to integrated system modeling by EC based Multidisciplinary Design Optimization (MDO), and presented the methods of Agent/Object oriented structure decomposition and re-construction, constructed class diagrams of objects in MSSs, set forth the rules for hierarchical entity decomposition and aggregation. Taking example for satellites, we presented their various Agent models. At last, the main organization models of Multi-Agent Systems (MAS) in MSSs are presented.Adopting above ideas, methods and models, we have designed and implemented the Modeling and Simulation Software for Integrated Effectiveness of Multi-Satellite Systems (MSSE for short). With powerful visualization and interactive capabilities, it can be used to build HHHMs of complex MSSs, configure the missions flexibly, monitor the whole simulation process, present all-around reports of data analysis and display vivid 2-D and 3-D animations, and eventually provide powerful supports for the design, evaluation and optimization of the MSSs. Finally, the design concepts, architecture, functions, and implementation mechanisms of the software are expounded.
论文分析指出,唯有采用普适性的顶层分析和优化设计框架,才能够有效解决面临的种种复杂性问题。而基于进化计算的优化方法,采用自适应随机搜索全局优化技术,具有广泛的适应性和包容性;基于多Agent的建模与仿真方法,则能够胜任复杂智能系统的综合效能仿真分析任务。为此,提出采用基于进化计算的仿真优化设计框架,并以对地观测多卫星系统为主要研究对象,重点对其效能分析方法、效能测度的确定及其求解模型、综合建模与仿真方法及相应软件的研制等方面展开了研究与实践。
首先,研究了多卫星系统具有的诸多复杂性特征;分析和归纳了多种典型构成形态;从时空、物理和功能特性等方面,研究了多颗卫星之间的分布与协同特性;对智能化自主协同运行多卫星系统的总体功能、特性、实现机制及其组织结构进行了分析。
然后,对一般性系统效能分析的几种主要方法进行了简要述评,提出了基于仿真的多卫星系统效能分析方法的总体框架。遵循此框架,界定了多卫星系统的层次结构;就复杂大系统中子系统效能的分析方法进行了讨论,给出两种基本方法:任务要求分解法和全系统效能敏感性分析法;提出了系统信息获取的四元组效能测度:内容、范围、质量和时效性,并将其具体化为遥感信息获取的空间(Space)、频谱(Spectrum)、能量(Energy)、时间(Time)(简称SSET)四维空间的相应测度。
接着,提出了离散化SSET空间的信息粒模型,给出了单个遥感器信息获取容量的计算模型,并对多卫星系统的时间、空间、频谱和能量维信息容量进行了分析;面向效能分析,提出了“物理覆盖”、“有效覆盖”、“充分信息量”等概念,并通过一典型示例系统,给出了基于仿真的效能测度求解方法及其基本模型;针对系统覆盖区域的非规则性,设计和实现了“池中投石法”、“油环点火法”和“逐步吸收法”等基于仿真的覆盖区域通用求解算法。
分析了复杂系统可靠性模型和可靠度综合计算的特点,提出了复合逻辑树(Composite Logic Tree Model,简称CLTM)综合建模方法及其可靠度递归综合算法,并设计和实现了相应的软件系统,论文对其设计思想、总体结构、主要功能及其实现机制进行了阐述。
此后,主要针对复杂多卫星系统的综合建模与仿真方法展开了研究。首先分析指出,所建模型应为分解结构描述水平上的多学科混合异构层次化系统整体同构模型。分析了面向对象的建模与仿真方法对此提供的支持机制及其局限性,提出了基于多Agent/Object的整体建模与仿真方法,并给出其总体框架。然后,分别就Object与Agent共存机制、实体属性和行为的确定原则、基于进化计算的多学科优化对系统整体建模的要求、Agent/Object模型粒度确定等方面进行了讨论,分别给出了面向Object和面向Agent的解构与重构方法,
With the coming of information era, it is of great significance for society development and nation security to construct integrated space information acquisition system, which will operate in intelligent, distributed, collaborative, autonomous, multi-satellite mode. How to analyze, evaluate and optimize the integrated effectiveness of the complex systems to get the most satisfying one is a crucial problem which must be answered as early as possible.We made a detailed analysis and concluded that only if a general system analysis and optimization framework were adopted can we solve the multitudinous complex problems. The Evolutionary Computation (EC) based optimization methods, adopting self-adaptive stochastic searching technology for global optimization, possess comprehensive adaptability and compatibility, moreover, the Multi-Agent Based Modeling and Simulation (MABMS) methods are competent for analyzing the integrated effectiveness of complex intelligent systems. So, we presented an EC based simulation optimization design framework for Multi-Satellite Systems (MSSs). Under the framework, emphasizing on earth observation MSSs, we have done some research mainly to propose effective methods for system effectiveness analysis, establish Measures of Effectiveness (MoEs) and their solving models, set forth integrated Modeling and Simulation (M&S) methods, and construct corresponding M&S software environment.First, we investigated the various complexity characteristics existing in MSSs in detail, analyzed and induced typical composing configuration of MSSs, explored their distribution and collaboration relationships from the aspects of space, time, physics and function, and analyzed the overall functions, main characteristics, implementation mechanisms and organization structures of MSSs operating in the intelligent, autonomous, collaborative mode.Then, we reviewed briefly several main general methods for effectiveness analysis, and put forward the overall framework of effectiveness analysis methods based on M&S. According to the framework, we defined the hiberarchy of MSSs, discussed how to analyze the effectiveness of the subsystems in System of Systems and gave two basic methods: mission requirements decomposing and effectiveness sensitivity analysis of holistic system, set forth the four-element group of MoEs for information acquisition: Content, Area, Quality, Response time, and concretized them into corresponding MoEs in four-dimension space (Space, Spectrum, Energy, Time, SSET for short) of information acquisition by remote sensing.And then, we put forward an information grid model in discrete SSET space, deduced the models for computing total information capability of one single remote sensor, analyzed the information capability of MSSs in respective dimension of the SSET space, and set forth the following concepts: physical coverage, effective coverage, sufficient information quantity.
Through a typical example, we provided simulation based approaches and models to solve the MoEs for the system in detail. In order to search the points in or on the edge of the irregular coverage regions, we designed and implemented several general algorithms and named them throwing a stone into a pond, igniting an oiled hoop, absorbing step by step. The main ideas and contents of them are expounded.By analyzing the characteristics of the models and integrated computing for reliability of complex large systems, we set forth a new model named Composite Logic Tree Model (CLTM) and its modeling principles, and designed a recursive algorithm based on CLTM, and developed the corresponding software. The design ideas, architecture and main functions, implementation mechanisms of the software are introduced.And then, we pointed that, the models built for holistic system optimization should be integrated multidisciplinary isomorphic Hybrid Heterogeneous Hierarchical Models (HHHMs) in the description level of decomposing structure. By analyzing the supporting mechanisms and limits of the Object-Oriented M&S (OOMS) methodology, and the excellent characteristics of the MABMS methodology, we presented the Multi-Agent/Object (MAO) based M&S and optimization method framework for complex MSSs. Then, we discussed the mechanisms of Agent/Object co-existence, the principles of choosing the granularity of the Agents/Objects and defining their attributes and behaviors, the requirements to integrated system modeling by EC based Multidisciplinary Design Optimization (MDO), and presented the methods of Agent/Object oriented structure decomposition and re-construction, constructed class diagrams of objects in MSSs, set forth the rules for hierarchical entity decomposition and aggregation. Taking example for satellites, we presented their various Agent models. At last, the main organization models of Multi-Agent Systems (MAS) in MSSs are presented.Adopting above ideas, methods and models, we have designed and implemented the Modeling and Simulation Software for Integrated Effectiveness of Multi-Satellite Systems (MSSE for short). With powerful visualization and interactive capabilities, it can be used to build HHHMs of complex MSSs, configure the missions flexibly, monitor the whole simulation process, present all-around reports of data analysis and display vivid 2-D and 3-D animations, and eventually provide powerful supports for the design, evaluation and optimization of the MSSs. Finally, the design concepts, architecture, functions, and implementation mechanisms of the software are expounded.
引文
[1] 郭华东.感知天地—信息获取与处理技术.北京:科学出版社,2000.
[2] 庄逢甘,陈述彭.遥感与新世纪.北京:气象出版社,1999.
[3] Al Core. The Digital Earth: Understanding our planet in the 21th century. Open GIS Consortium, California, 31 Jan. 1998.
[4] 常显奇等.军事航天学.北京:国防工业出版社,2002.
[5] Jackon J A, et al. An operational analysis for air force 2025: an application of value-focused thinking to future air and space capabilities. A Reaearch Paper Presented to Air Force 2025. 1996.
[6] Scott W. New USAF roadmaps spotlight space warfare technologies. AW&ST, 1997 (6) : 61-63.
[7] Mohammed J L. Spacecaps: Automated mission planning for the techsat 21 formation-flying cluster experiment. Susan M. Hailer, Gene Simmons. Proceedings of the Fifteenth International Florida Artificial Intelligence Research Society Conference. Pensacola Beach, Florida, USA: AAAIPress, 2002.
[8] Schetter T, Campbell M, Surka D. Multiple agent-based autonomy for satellite constellations, www. elsevier, com, Artificial Intelligence2003, 145 : 147-180.
[9] Shaw G B, Miller D W, Hastings D E. Generalized characteristics of communication, sensing, and navigation satellite systems. Journal of Spacecraft and Rockets, 2000, 37 (6) : 801-811.
[10] Budianto I A, Olds J R. A collaborative optimization approach to design and deployment of a space based infrared system constellation. Proceedings of 2000 IEEE Aerospace Conference. Piscataway, NJ: IEEE Inc. , 2000. (1) : 385-393.
[11] Frank H Bauer, et al. Enabling spacecraft formation flying through spaceborne GPS and enhanced automation technologies. 1999 ION-GPS Conference. Nashville, TN, 1999.
[12] Christopher R. Autonomy in future space missions. Henry H, Rino F C. Autonomy, Delegation, and Control: From Inter-Agent to Groups. Papers from AAAI Workshop Technical Report WS-02-03, AAAI Press. 2000. 57-63.
[13] 林来兴.微小卫星编队飞行及应用论文集.北京:国家高技术航天领域专家委员会微小卫星技术组,2000.
[14] 朱述龙,张占睦.遥感图像获取与分析.北京:科学出版社,2000.
[15] 陈述彭,童庆禧,郭华东.遥感信息机理研究.北京:科学出版社,1998.
[16] Bradley J C, Anthony C B. Coordination Challenges for Autonomous Spacecraft. AAMAS-02 workshop notes on Toward an Application Science: MAS Problem Spaces and Their Implications to Achieving Globally Coherent Behavior, 2002.
[17] Zhou G Q, Kafatos M. Future intelligent earth observing satellites. Proceedings of International Workshop on Future Intelligent Earth Observing Satellites (FIEOS). Denver, Colorado, USA, 2002.
[18] Surka D M, Brito M C, Harvey C G. The real-time ObjectAgent software architecture for distributed satellite systems. Proceedings of 2001 IEEE Aerospace Conference. Piscataway, NJ: IEEE Inc. , 2001. (6) : 2731-2741.
[19] Schetter T, Campbell M, Surka D. Multiple agent-based autonomy for satellite constellations. Second International Symposium on Agent System and Applications Proceedings. Zurich, Switzerland, 2000.
[20] Chien S, et al. The Techsat-21 autonomous sciencecrafl constellation. Proceeding of the 6th International Symposium on Artificial Intelligence and Robotics & Automation in Space. St-Hubert, Quebec, Canada: Canadian Space Agency, 2001.
[21] Penne(?)ot Y, Atkins E, Sanner R. Intelligent spacecraft formation management and path planning. 40th AIAA Aerospace Sciences Meeting & Exhibit. Reno, Nevada, 2002. AIAA 2002-1072.
[22] 王希季,李大耀.卫星设计学.上海:上海科学技术出版社,1997.
[23] (德)迪·德尔纳著,王志刚译.失败的逻辑.上海:上海科技教育出版社,1999.
[24] 向开恒,肖业伦.卫星星座的系统仿真研究.北京航空航天大学学报,1999,25(6):629-633.
[25] Wertz J R, Larson W J. Space mission analysis and design (Third Edition). Torrance, California: Microcosm Press. Dordrecht: Kluwer Academic Publishers, 1999.
[26] Thomas B. Evolutionary algorithms in theory and practice. New York: Oxford University Press, 1996.
[27] Fukunaga A S., Chien S, Mutz D, Sherwood R L, Stechert A D. Automating the process of optimization in spacecraft design. Proceedings of the 1997 IEEE Aerospace Conference. Piscataway, NJ: IEEE Inc. , 1997. (4): 411-428.
[28] 高存厚,荣明宗.飞行器系统工程.北京:宇航出版社,1996.
[29] 秦寿康.综合评价原理与应用.北京:电子工业出版社,2003.
[30] 李廷杰.导弹武器系统的效能及其分析.北京:国防工业出版社,2000.
[31] 张卓,刘伊林等.作战效能评估.北京:军事科学出版社,1996.
[32] 张玉锟.卫星编队飞行的动力学与控制技术研究.长沙:国防科技大学研究生院,2002.
[33] 贺勇军,戴金海,李连军,王海丽,张玉锟.多卫星系统综合效能仿真分析软件技术报告.长沙:国防科技大学航天与材料工程学院,2001.
[34] 贺勇军,戴金海,李连军.复杂多卫星系统的综合建模与仿真.系统仿真学报,2004,16(5):871—875.
[35] 贺勇军,戴金海,李连军.多卫星系统综合建模与仿真环境的设计与实现.计算机仿真,2004,21(5):28-31,35.
[36] He YJ, Dai JH, Wang HL. Design and implementation of the integrated modeling and simulation environment for multisatellite earth observation systems. International Conference on Geoinformatics &GeographicalSystems Modeling and Fifth Beijing International Workshopin GIS. Beijing, China, 2004.
[37] 陈浩光,李云芝.空间作战系统效能评估初探.装备指挥技术学院学报,2002,13(4):40-44.
[38] Marshall S R. , Patrick R C. STK4. 21 user's manual. USA.. AGI., 1997.
[39] 孙兆伟,徐国栋,林晓辉,曹喜滨.小卫星设计、分析与仿真一体化系统.系统仿真学报,2001,13(5):623-626.
[40] 徐福祥.卫星工程学讲义.北京:中国空间技术研究院,1999.
[41] Mosher T. Spacecraft design using a genetic algorithm optimization approach. IEEE Proceedings of 1998 Aerospace Conference. Piscataway, NJ: IEEE Inc., 1998. (3): 123-134.
[42] Mosher, T. Applicability of selected multidisciplinary design optimization methods to conceptual spacecraft design. Proceedings of the 6th AIAA/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization. Bellevue, WA, AIAA-96-4052,1996. 664-671.
[43] Mason W J, Victoria C C.Optimal Earth Orbiting Satellite constellations via a Pareto Genetic Algorithm.Paper No. AIAA 98-43 81.Proceedings of the 1998 AIAA/AAS Astrodynamics Specialist Conference and Exhibit, Boston, MA, August 1998.169-177.
[44] Matossian M. Earth observing system mission design: constrained optimization of the eos constellation configuration design. 46th International Astronautical Congress, Oslo, Norway, 1995.
[45] Matossian M. Distributed task constellation design optimization: an operations research approach to earth observing system configuration design . 47th International Astronautical Congress. Beijing, China, 1996.
[46] Crossley W A. Optimization for aerospace conceptual design through the use of genetic algorithms . Proceedings of the First NASA/DOD Workshop on Evolvable Hardware. 1999. 200-207.
[47] Ely T A, Crossley W A, Williams E A. Satellite constellation design for zonal coverage using genetic algorithms. The Journal of the Astronautical Sciences, 1999, 47(3, 4) : 207-228.
[48] Seereeram, Li, Ravichandran, Mehra, Smith R, Beard R. Multi-spacecraft trajectory optimization and control using genetic algorithm techniques. Proceedings of the 2000 IEEE Aerospace Conference. Piscataway, NJ: IEEE Inc. , 2000. (7) : 99-108.
[49] Frayssinhes E, et al. Investigating new satellite constellation geometric with genetic algorithms. AIAA/AAS Astrodynamics conference, San Diego, 1996. AIAA 96-3636(A96-34770) .
[50] Sobieszczanski-Sobieski J, Haftka T. Multidisciplinary aerospace design optimization: survey of recent developments. AIAA 96-0711.
[51] Acton D E, Olds J R. Computational frameworks for collaborative multidisciplinary design of complex systems . 7th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Design and Optimization. St. Louis, MO, 1998.
[52] Zink P S, et al. New approach to high speed civil transport multidisciplinary design and optimization. Proceedings of the 2000 IEEE Aerospace Conference. Piscataway, NJ: IEEE Inc. , 2000. (1) 355-370.
[53] Jilla C D. A multiobjective multidisciplinary design optimization methodology for the conceptual design of distributed satellite systems. USA: Massachusetts Institute of Technology , 2002.
[54] Olds J. The suitability of selected multidisciplinary design and optimization techniques to conceptual vehicle design . 4th AIAA/USAF/NASA/OAI Symposium on Multidisciplinary Analysis and Optimization. Cleveland, OH, 1992.
[55] Tester J T, Robinson, D G. Multidisciplinary modeling and design of a space system . Proceedings of IEEE International Conference on Systems Engineering. 1991. 446-449.
[56] Taylor E R. Evaluation of multidisciplinary design optimization techniques as applied to spacecraft design. Proceedings of the 2000 IEEE Aerospace Conference. Piscataway, NJ: IEEE Inc. , 2000. (1) : 371-384.
[57] Taylor, Riddle E. Evaluation of multidisciplinary design optimization techniques as applied to the spacecraft design process. Colorado, USA: Faculty of the Graduate School of the University of Colorado, 1999.
[58] 李明.遥感卫星总体参数分析与优化设计方法研究.北京:中国空间技术研究院,1996.
[59] 张帆.光学遥感卫星总体参数优化方法研究.哈尔滨:哈尔滨工业大学,1998.
[60] 白鹤峰.卫星星座的分析设计和控制方法研究.长沙:国防科技大学研究生院,1999.
[61] 王海丽,陈磊,任萱.卫星星座全球连续覆盖的仿真分析与优化.中国空间科学技术,2001,(1).
[62] 王海丽.军用侦察卫星星座的问题研究.长沙:国防科技大学研究生院,2001.
[63] 陈琪锋.飞行器分布式协同进化多学科设计优化方法研究.长沙:国防科技大学研究生院,2003.
[64] Von B L. General system theory. New York: George Braziller Inc. , 1968.
[65] 潘正君,康立山,陈毓屏.演化计算.北京:清华大学出版社,广西科学技术出版社,1998.
[66] Back, Thomas. Evolutionary algorithms in theory and practice. New York: Oxford University Press, 1996.
[67] Clymer J R. Optimization of simulated system effectiveness using evolutionary algorithms. Simulation, 1999, 73 (6): 334-340.
[68] Khatib W, Fleming P J . Evolutionary computing for multidisciplinary optimization. Second International Conference On Genetic Algorithms In Engineering Systems: Innovations And Applications. Conf. Publ. No. 446, 1997. 7-12.
[69] Fonseca C M, Fleming P J. Multiobjective optimization and multiple constraint handling with evolutionary algorithms. I. A unified formulation. IEEE Transactions on Systems, Man and Cybernetics, Part A, 1998 , 28 (1) 26-37.
[70] Abbattista F, Abbattista N, Caponetti L. An evolutionary and cooperative agents model for optimization. Proceedings of IEEE International Conference on Evolutionary Computation. 1995. (2) : 668-671 .
[71] 许国志.系统科学.上海:上海科学教育出版社,2000.
[72] (美)约翰·霍兰著,陈禹等译.涌现—从混沌到有序.上海:上海科学技术出版社,2001.
[73] (美)西蒙H著,武夷山译.人工科学.北京:商务印书馆,1987.
[74] (德)哈肯H著,郭治安等译.大脑工作原理—脑活动、行为和认知的协同性研究.上海:上海科学技术出版社,2000.
[75] (比)普利高津著,湛敏译.确定性的终结—时间、混沌与新自然法则.上海:上海科学技术出版社,1998.
[76] (德)迈因策尔K著,曾国屏译.复杂性中的思维—物质、精神和人类的复杂动力学.北京:中央编译出版社,1999.
[77] (美)约翰·霍兰著,周晓牧等译.隐秩序—适应性造就复杂性.上海:上海科技教育出版社,2000.
[78] 孙家捅,舒宁,关泽群.遥感原理、方法与应用.北京:测绘出版社,1997.
[79] 张钧屏,方艾里,万志龙.对地观测与对空监视.北京:科学出版社,2001.
[80] 李小文,汪骏发,王锦地,柳钦火.多角度与热红外对地遥感.北京:科学出版社,2001.
[81] 肖峰.人造地球卫星轨道摄动理论.长沙:国防科技大学出版社,1997.
[82] 李济生.人造卫星精密轨道确定.北京:解放军出版社,1995.
[83] (日)遥感研究会编,刘勇卫,贺雪鸿译.遥感精解.北京:测绘出版社,1993.
[84] M.I.斯科尔尼克主编,谢卓译.雷达手册.北京:国防工业出版社,1978.
[85] 承继成,郭华东,史文中.遥感数据的不确定性问题.北京:科学出版社,2004.
[86] 魏钟铨等.合成孔径雷达卫星.北京:科学出版社,2001.
[87] 李德毅,史雪梅,孟海军.隶属云和隶属云发生器.计算机研究和发展,1995,42(8):32—41.
[88] Schoeberl M, Bristow J, Raymond C. Intelligent distributed spacecraft infrastructure. Earth Science Enterprise Technology Planning Workshop, 2001.
[89] Hughes S P, Hall C D. Mission performance measures for spacecraft formation flying. Proceedings of the 1999 Flight Mechanics Symposium. God- dard Space Flight Center, 1999. 309-318.
[90] Mandutianu S, Hadaegh F, Elloit P. Multi-agent syatem for formation flying missions. IEEE Aerospace and Electronic Systems Society. Proceedings of the 2001 IEEE Aerospace Conference. Piscataway, NJ: IEEE Inc. , 2001. (6) : 2793-2802.
[91] Kang W, Sparks A, Banda S. Multi-satellite formation and reconfiguration. Proceedings of the 2000 American Control Conference. 2000. 1 (6) : 379-383.
[92] Mandutianu S, Hadaegh F, Elliot P. Multi-agent system for formation flying missions. Proceedings of 2001 IEEE Aerospace Conference. Piscataway, NJ: IEEE Inc. , 2001. (6) : 2793-2802.
[93] Knoblock EJ, Wallett T M, Konangi V K, Bhasin K B. Network configuration analysis for formation flying satellites Proceedings of 2001 IEEE Aerospace Conference. Piscataway, NJ: IEEEInc. , 2001. (2) : 991-1000.
[94] Chien S, et al. The techsat-21 autonomous space science agent. AAMAS'02, Bologna, Italy, 2002.
[95] Barrett A. Autonomy architectures for a constellation of spacecraft. International Symposium on Artificial Intelligence Robotics and Automation in Space (ISAIRAS). Noordwijk, The Netheflands, 1999.
[96] Stroupe A W, et al. Technology for autonomous space system. CMU-RI-TR-00-02, Carnegie Mellon University, 2002.
[97] Sherwood R, et al. Next generation autonomous operations on a current generation satellite. 5th International Symposium on Reducing the Cost of Spacecraft Ground Systems and Operations (RCSGSO 2003). Pasadena, CA. 2003.
[98] Bernard D, et al. Spacecraft autonomy flight experience: the DS1 remote agent experiment. AIAA-99-4512. 1999.
[99] Campbell M E, Bohringer K F. Intelligent satellite teams for space systems. 2nd International Conference on Integrated Micro-nanotechnology for Space Applications. 1999.
[100] Rouff C, Truszkowski W. A process for introducing agent technology into Space missions. Proceedings of 2001 IEEE Aerospace Conference. Piscataway, NJ: IEEE Inc. 2001. (6) : 2743-2750.
[101] Schetter T, Campbell M, Surka D. Comparison of multiple agent-based organizations for satellite constellations. 2000 FLAIRS AI Conference Proceedings. Orlando, Florida, 2000.
[102] Zetocha P. Satellite cluster command and control. IEEE Aerospace and Electronic Systems Society. Proceedings of 2000 IEEE Aerospace Conference. Piscataway, NJ: IEEE Inc. , 2000. (7) : 49-54.
[103] 吴志革.陆军武器系统分析.北京:兵器工业部兵器系统工程研究所,1985
[104] Dersin P, Levis A H. Large system effectiveness analysis[R]. LIDS—FR—1072, 1981.
[105] Levis A H, Houpt P K, Andreadakis S K. Effectiveness Analysis of Automotive Systems[R]. LIDS—P—1383, 1984.
[106] Sproles N. The difficult problem of establishing measures of effectiveness for command and control: a system engineering perspective. System Engineering, 2000, 4 (2).
[107] 李树楷,薛永祺.高效三维遥感集成技术系统.北京:科学出版社,2000。
[108] 韩心志,焦世举.航天光学遥感辐射度学.哈尔滨:哈尔滨工业大学出版社,1994.
[109] 赵英时等.遥感应用分析原理与方法.北京:科学出版社,2003.
[110] 中国大百科全书编辑委员会.中国大百科全书—自动控制与系统工程卷.北京:中国大百科全书出版社,1991.
[111] 林象平.雷达对抗原理.西安:西北电讯工程学院出版社,1985.
[112] 马蔼乃.遥感信息模型.北京:北京大学出版社,1997.
[113] 张守信.GPS卫星测量定位理论与应用.长沙:国防科技大学出版社,1996.
[114] Tollefson M V. , Preiss B K. Space based radar constellation optimization. Proceedings of 1998 IEEE Aerospace Conference. Piscataway, NJ: IEEE Inc. , 2000. (3) : 379-390.
[115] 谢红卫,宫二玲,贺勇军.时变结构多阶段任务系统的可靠度研究.国防科技大学学报,1999,21(5):41-45.
[116] 贺勇军.载人航天测控网系统可靠性综合计算.长沙:国防科技大学研究生院,1999.
[117] Bavoso S J, Rothman E, et al. HiRel: Hybrid Automated Reliability Predictor(HARP) integrated reliability tool system(Ver7. 0). NTIS NO. N95-22603/1/HDM, 1995.
[118] 周广涛.计算机辅助可靠性工程.北京:宇航出版社,1990.
[119] 潘吉安.可靠性评估及其应用软件的开发.电子产品可靠性和环境实验,1997,(5):7-11.
[120] 曹晋华,程侃.可靠性数学引论.北京:科学出版社,1986.
[121] 梅启智等.系统可靠性工程基础.北京:科学出版社,1987.
[122] 贺勇军,谢红卫.复杂系统可靠度的CLTM建模及递归综合算法.国防科技大学学报,2003,25(4):102—106.
[123] 贺勇军.复杂系统可靠度综合计算平台的设计实现.航空计算技术,2003,33(3):51-55.
[124] Zeigler B P. Theory of modelling and simulation. New York: John Wiley & Sons, Inc. , 1976.
[125] 艾什比.大脑设计.北京:商务印书馆,1991.
[126] 王维平,朱一凡,华雪倩,张汉江.离散事件系统建模与仿真.长沙:国防科技大学出版社,1997.
[127] Khosla R. Intelligent hybrid multi-agent computational architecture for complex systems. Systems,.Man, and Cybernetics, 1997. 1997 IEEE International Conference on Computational Cybernetics and Simulation. 1997. (5): 4471-4476
[128] 许国志.系统科学与工程研究.上海:上海科学教育出版社,2000.
[129] (英)欧阳莹之著,田宝国等译.复杂系统理论基础.上海:上海科技教育出版社,2002.
[130] 王连成.工程系统论.北京:中国宇航出版社,2002.
[131] Dahl O J, Nygard K. Simula—an algol-based simulation language. Communications ACM, 1996, 9: 671-678.
[132] Marciniak J. Encyclopedia of software engineering. NewYork: John Wiley&Sons, 1994.
[133] Zeigler B P. Object-oriented simulation with hierarchical, modular models: intelligent agents and endomorphie systems. New York: Academic Press, 1990.
[134] Fishwick P A. Multi-modeling as a unified modeling framework. Proceedings of the 1993 Winter Simulation Conference. Piscataway, NJ: IEEE Inc. 1993. 580-581.
[135] Miller V T., Fishwick P A. Graphic modeling using heterogeneous hierarchical models. Proceedings of the 1993 Winter Simulation Conference. Piscataway, NJ: IEEE Inc. 1993. 612-617.
[136] Miller V T, Fishwick P A. Hybrid heterogeneous hierarchical models for system simulations. International Journal in Computer Simulation, 1995, (5): 209-227.
[137] Zeigler B P, Praehofe H, Kim T G. Theory of modeling and simulation (Second Edition). San Diego, USA: Academic Press, 2000.
[138] Corbin M J, Butler G F. MulTiSIM: An object-based distributed framwork for mission simulation. Simulation Practice and Theory. 1996 (3): 383-399.
[139] Wiant, Michael, Mitrione, Michael F, Backer, Kim. Object-oriented architectures for simulation of complex systems. The Proceedings of the Summer Computer Simulation Conference. 1996. 306-309.
[140] Wooldridge M. An introduction to multiagent systems. New York: John Wiley& Sons Inc., 2002.
[141] Gerd Wagner, Florin Tulba. Agent-oriented modeling and agent-based simulation. Giorgini P and Henderson-Sellers B. Proceedings of 5th Int. Workshop on Agent-Oriented Information Systems (AOIS-2003), ER2003 Workshops. Springer-Verlag, LNCS, 2003.
[142] Seungman L, Pritchett A, Goldsman D. Hybrid agent-based simulation for analyzing the National Airspace System. Proceedings of the 2001 Winter Simulation Conference. Piscataway, NJ: IEEE Inc. 2001. (2): 1029-1037.
[143] Sanchez S M, Lucas T W. Exploring the world of agent-based simulations: simple models, complex analyses. Proceedings of the 2002 Winter Simulation Conference. Piscataway, NJ: IEEE Inc. 2002. (1): 116-126.
[144] Marietto M B, et al. Requirements analysis of agent-based simulation, platforms: state of the art and new prospects. Proceedings of the MABS 2002 (Workshop on Multi-Agent Based Simulation), First International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS2002), Bologna, July 15-17, 2002.
[145] Drogoul A, Vanbergue D, Meurisse T. Multi-agent based simulation: where are the agents. Sichman J S, Bousquet F, Davidsson P. Multi-Agent-Based Simulation, Third International Workshop, MABS 2002, Bologna, Italy, July 15-16, 2002, Revised Papers. Lecture Notes in Computer Science 2581, Springer, 2003.
[146] Davidsson P. Multi agent based simulation: beyord social simulation. Scott Moss, Paul Davidsson. Multi-Agent-Based Simulation, Second International Workshop, MABS 2000, Boston, MA, USA: July, 2000. Revised and Additional Papers. Lecture Notes in Computer Science 1979, Springer, 2001.
[147] Wickenberg T, Davidsson P. On multi agent based simulation of software development processes. Multi-Agent Based Simulation II, LNAI Vol. 2581, Springer, 2003.
[148] Papp Z, Hoeve H J. A multi-agent based modeling and execution framework for complex simulation , control and measuring tasks . http : //www. tpd. tno. nl/smartsite87. Html.
[149] Mardhana E, Far B H. Design issues on multi-agent system simulation framework: implications from agent design strategy and architecture. IECI Japan Workshop, 2001.
[150] Wooldridge M, Jennings N R. Intelligent agent: theory and practice. Knowledge Engineering Review, 1995, 10 (2) : 115-152.
[151] Weiss G . Multiagent System : A modern approach to distributed artifical intelligence. Cambridge, MA: MIT Press, 1999.
[152] Bradshaw J M. Software agent. Cambridge, MA: AAAI Press/MIT Press, 1997.
[153] Knapik M, Johnson J. Developing intelligent agents for distributed systems. New York: McGraw-Hill, 1998.
[154] Finin T, Fritzson R, McKay D, et al. An Overview of KQML: A Knowledge Query and Manipulation Language. Baltimore County, USA : Department of Computer Science, University of Maryland, 1992.
[155] Van H, Parunak D, Savit R, Riolo R L. Agent-based modeling vs. equation-based modeling: a case study and users' guide. Proceedings of Multi-agent systems and Agent-based Simulation (MABS'98). 10-25, Springer, LNAI 1534, 1998.
[156] Iglesias C A, GarijoM, Gonzalez JC. A survey of agent-oriented methodologies. In Muller, J. P. , Singh, M. , and Rao, A. S. , editors. Intelligent Agents V: Proceedings of the ATAL'98, LNAI 1555. Springer.
[157] Truszkowsk W , Zoch D , Smith D . Autonomy for constellations . http://agents, gsfc. nasa. gov/papers.
[158] Dorais G A, NicewarnerK. Adjustably autonomous multi-agent plan execution with an internal spacecraft free-flying robot prototype. Proceedings of ICAPS'03 Workshop on Plan Execution. Trento, Italy. June, 2003.
[159] Das S, Gonsalves P, Krikorian R, Truszkowski W. Multi-agent planning and scheduling environment for enhanced spacecraft autonomy. 5th International Symposium on Artificial Intelligence, Robotics and Automation in Space. ESTEC. Noordwijk, The Netherlands, 1999.
[160] Muler JP, Pischel M, Thiel M. Modeling reactive behavior in vertically layered agent architectures. M. Woodridge and N. R. Jennings. Intelligent Agent: Theories, Architectures and Languages, Lecture Notes in Artificial Intelligence 890. Berlin: Springer Verlag , 1995. 261-276.
[161] Kitts C, Swartwout M. Autonomous operations experiments for the distributed emerald nanosatellite mission. 14th Annual AIAA/USU Conference on Small Satellites. Logan, Utah, The United States: 2000.
[162] O'Hare G M P, Jennings NR. Foundation of distributed artificial intelligence. New York: John Willey & Sons, 1996.
[2] 庄逢甘,陈述彭.遥感与新世纪.北京:气象出版社,1999.
[3] Al Core. The Digital Earth: Understanding our planet in the 21th century. Open GIS Consortium, California, 31 Jan. 1998.
[4] 常显奇等.军事航天学.北京:国防工业出版社,2002.
[5] Jackon J A, et al. An operational analysis for air force 2025: an application of value-focused thinking to future air and space capabilities. A Reaearch Paper Presented to Air Force 2025. 1996.
[6] Scott W. New USAF roadmaps spotlight space warfare technologies. AW&ST, 1997 (6) : 61-63.
[7] Mohammed J L. Spacecaps: Automated mission planning for the techsat 21 formation-flying cluster experiment. Susan M. Hailer, Gene Simmons. Proceedings of the Fifteenth International Florida Artificial Intelligence Research Society Conference. Pensacola Beach, Florida, USA: AAAIPress, 2002.
[8] Schetter T, Campbell M, Surka D. Multiple agent-based autonomy for satellite constellations, www. elsevier, com, Artificial Intelligence2003, 145 : 147-180.
[9] Shaw G B, Miller D W, Hastings D E. Generalized characteristics of communication, sensing, and navigation satellite systems. Journal of Spacecraft and Rockets, 2000, 37 (6) : 801-811.
[10] Budianto I A, Olds J R. A collaborative optimization approach to design and deployment of a space based infrared system constellation. Proceedings of 2000 IEEE Aerospace Conference. Piscataway, NJ: IEEE Inc. , 2000. (1) : 385-393.
[11] Frank H Bauer, et al. Enabling spacecraft formation flying through spaceborne GPS and enhanced automation technologies. 1999 ION-GPS Conference. Nashville, TN, 1999.
[12] Christopher R. Autonomy in future space missions. Henry H, Rino F C. Autonomy, Delegation, and Control: From Inter-Agent to Groups. Papers from AAAI Workshop Technical Report WS-02-03, AAAI Press. 2000. 57-63.
[13] 林来兴.微小卫星编队飞行及应用论文集.北京:国家高技术航天领域专家委员会微小卫星技术组,2000.
[14] 朱述龙,张占睦.遥感图像获取与分析.北京:科学出版社,2000.
[15] 陈述彭,童庆禧,郭华东.遥感信息机理研究.北京:科学出版社,1998.
[16] Bradley J C, Anthony C B. Coordination Challenges for Autonomous Spacecraft. AAMAS-02 workshop notes on Toward an Application Science: MAS Problem Spaces and Their Implications to Achieving Globally Coherent Behavior, 2002.
[17] Zhou G Q, Kafatos M. Future intelligent earth observing satellites. Proceedings of International Workshop on Future Intelligent Earth Observing Satellites (FIEOS). Denver, Colorado, USA, 2002.
[18] Surka D M, Brito M C, Harvey C G. The real-time ObjectAgent software architecture for distributed satellite systems. Proceedings of 2001 IEEE Aerospace Conference. Piscataway, NJ: IEEE Inc. , 2001. (6) : 2731-2741.
[19] Schetter T, Campbell M, Surka D. Multiple agent-based autonomy for satellite constellations. Second International Symposium on Agent System and Applications Proceedings. Zurich, Switzerland, 2000.
[20] Chien S, et al. The Techsat-21 autonomous sciencecrafl constellation. Proceeding of the 6th International Symposium on Artificial Intelligence and Robotics & Automation in Space. St-Hubert, Quebec, Canada: Canadian Space Agency, 2001.
[21] Penne(?)ot Y, Atkins E, Sanner R. Intelligent spacecraft formation management and path planning. 40th AIAA Aerospace Sciences Meeting & Exhibit. Reno, Nevada, 2002. AIAA 2002-1072.
[22] 王希季,李大耀.卫星设计学.上海:上海科学技术出版社,1997.
[23] (德)迪·德尔纳著,王志刚译.失败的逻辑.上海:上海科技教育出版社,1999.
[24] 向开恒,肖业伦.卫星星座的系统仿真研究.北京航空航天大学学报,1999,25(6):629-633.
[25] Wertz J R, Larson W J. Space mission analysis and design (Third Edition). Torrance, California: Microcosm Press. Dordrecht: Kluwer Academic Publishers, 1999.
[26] Thomas B. Evolutionary algorithms in theory and practice. New York: Oxford University Press, 1996.
[27] Fukunaga A S., Chien S, Mutz D, Sherwood R L, Stechert A D. Automating the process of optimization in spacecraft design. Proceedings of the 1997 IEEE Aerospace Conference. Piscataway, NJ: IEEE Inc. , 1997. (4): 411-428.
[28] 高存厚,荣明宗.飞行器系统工程.北京:宇航出版社,1996.
[29] 秦寿康.综合评价原理与应用.北京:电子工业出版社,2003.
[30] 李廷杰.导弹武器系统的效能及其分析.北京:国防工业出版社,2000.
[31] 张卓,刘伊林等.作战效能评估.北京:军事科学出版社,1996.
[32] 张玉锟.卫星编队飞行的动力学与控制技术研究.长沙:国防科技大学研究生院,2002.
[33] 贺勇军,戴金海,李连军,王海丽,张玉锟.多卫星系统综合效能仿真分析软件技术报告.长沙:国防科技大学航天与材料工程学院,2001.
[34] 贺勇军,戴金海,李连军.复杂多卫星系统的综合建模与仿真.系统仿真学报,2004,16(5):871—875.
[35] 贺勇军,戴金海,李连军.多卫星系统综合建模与仿真环境的设计与实现.计算机仿真,2004,21(5):28-31,35.
[36] He YJ, Dai JH, Wang HL. Design and implementation of the integrated modeling and simulation environment for multisatellite earth observation systems. International Conference on Geoinformatics &GeographicalSystems Modeling and Fifth Beijing International Workshopin GIS. Beijing, China, 2004.
[37] 陈浩光,李云芝.空间作战系统效能评估初探.装备指挥技术学院学报,2002,13(4):40-44.
[38] Marshall S R. , Patrick R C. STK4. 21 user's manual. USA.. AGI., 1997.
[39] 孙兆伟,徐国栋,林晓辉,曹喜滨.小卫星设计、分析与仿真一体化系统.系统仿真学报,2001,13(5):623-626.
[40] 徐福祥.卫星工程学讲义.北京:中国空间技术研究院,1999.
[41] Mosher T. Spacecraft design using a genetic algorithm optimization approach. IEEE Proceedings of 1998 Aerospace Conference. Piscataway, NJ: IEEE Inc., 1998. (3): 123-134.
[42] Mosher, T. Applicability of selected multidisciplinary design optimization methods to conceptual spacecraft design. Proceedings of the 6th AIAA/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization. Bellevue, WA, AIAA-96-4052,1996. 664-671.
[43] Mason W J, Victoria C C.Optimal Earth Orbiting Satellite constellations via a Pareto Genetic Algorithm.Paper No. AIAA 98-43 81.Proceedings of the 1998 AIAA/AAS Astrodynamics Specialist Conference and Exhibit, Boston, MA, August 1998.169-177.
[44] Matossian M. Earth observing system mission design: constrained optimization of the eos constellation configuration design. 46th International Astronautical Congress, Oslo, Norway, 1995.
[45] Matossian M. Distributed task constellation design optimization: an operations research approach to earth observing system configuration design . 47th International Astronautical Congress. Beijing, China, 1996.
[46] Crossley W A. Optimization for aerospace conceptual design through the use of genetic algorithms . Proceedings of the First NASA/DOD Workshop on Evolvable Hardware. 1999. 200-207.
[47] Ely T A, Crossley W A, Williams E A. Satellite constellation design for zonal coverage using genetic algorithms. The Journal of the Astronautical Sciences, 1999, 47(3, 4) : 207-228.
[48] Seereeram, Li, Ravichandran, Mehra, Smith R, Beard R. Multi-spacecraft trajectory optimization and control using genetic algorithm techniques. Proceedings of the 2000 IEEE Aerospace Conference. Piscataway, NJ: IEEE Inc. , 2000. (7) : 99-108.
[49] Frayssinhes E, et al. Investigating new satellite constellation geometric with genetic algorithms. AIAA/AAS Astrodynamics conference, San Diego, 1996. AIAA 96-3636(A96-34770) .
[50] Sobieszczanski-Sobieski J, Haftka T. Multidisciplinary aerospace design optimization: survey of recent developments. AIAA 96-0711.
[51] Acton D E, Olds J R. Computational frameworks for collaborative multidisciplinary design of complex systems . 7th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Design and Optimization. St. Louis, MO, 1998.
[52] Zink P S, et al. New approach to high speed civil transport multidisciplinary design and optimization. Proceedings of the 2000 IEEE Aerospace Conference. Piscataway, NJ: IEEE Inc. , 2000. (1) 355-370.
[53] Jilla C D. A multiobjective multidisciplinary design optimization methodology for the conceptual design of distributed satellite systems. USA: Massachusetts Institute of Technology , 2002.
[54] Olds J. The suitability of selected multidisciplinary design and optimization techniques to conceptual vehicle design . 4th AIAA/USAF/NASA/OAI Symposium on Multidisciplinary Analysis and Optimization. Cleveland, OH, 1992.
[55] Tester J T, Robinson, D G. Multidisciplinary modeling and design of a space system . Proceedings of IEEE International Conference on Systems Engineering. 1991. 446-449.
[56] Taylor E R. Evaluation of multidisciplinary design optimization techniques as applied to spacecraft design. Proceedings of the 2000 IEEE Aerospace Conference. Piscataway, NJ: IEEE Inc. , 2000. (1) : 371-384.
[57] Taylor, Riddle E. Evaluation of multidisciplinary design optimization techniques as applied to the spacecraft design process. Colorado, USA: Faculty of the Graduate School of the University of Colorado, 1999.
[58] 李明.遥感卫星总体参数分析与优化设计方法研究.北京:中国空间技术研究院,1996.
[59] 张帆.光学遥感卫星总体参数优化方法研究.哈尔滨:哈尔滨工业大学,1998.
[60] 白鹤峰.卫星星座的分析设计和控制方法研究.长沙:国防科技大学研究生院,1999.
[61] 王海丽,陈磊,任萱.卫星星座全球连续覆盖的仿真分析与优化.中国空间科学技术,2001,(1).
[62] 王海丽.军用侦察卫星星座的问题研究.长沙:国防科技大学研究生院,2001.
[63] 陈琪锋.飞行器分布式协同进化多学科设计优化方法研究.长沙:国防科技大学研究生院,2003.
[64] Von B L. General system theory. New York: George Braziller Inc. , 1968.
[65] 潘正君,康立山,陈毓屏.演化计算.北京:清华大学出版社,广西科学技术出版社,1998.
[66] Back, Thomas. Evolutionary algorithms in theory and practice. New York: Oxford University Press, 1996.
[67] Clymer J R. Optimization of simulated system effectiveness using evolutionary algorithms. Simulation, 1999, 73 (6): 334-340.
[68] Khatib W, Fleming P J . Evolutionary computing for multidisciplinary optimization. Second International Conference On Genetic Algorithms In Engineering Systems: Innovations And Applications. Conf. Publ. No. 446, 1997. 7-12.
[69] Fonseca C M, Fleming P J. Multiobjective optimization and multiple constraint handling with evolutionary algorithms. I. A unified formulation. IEEE Transactions on Systems, Man and Cybernetics, Part A, 1998 , 28 (1) 26-37.
[70] Abbattista F, Abbattista N, Caponetti L. An evolutionary and cooperative agents model for optimization. Proceedings of IEEE International Conference on Evolutionary Computation. 1995. (2) : 668-671 .
[71] 许国志.系统科学.上海:上海科学教育出版社,2000.
[72] (美)约翰·霍兰著,陈禹等译.涌现—从混沌到有序.上海:上海科学技术出版社,2001.
[73] (美)西蒙H著,武夷山译.人工科学.北京:商务印书馆,1987.
[74] (德)哈肯H著,郭治安等译.大脑工作原理—脑活动、行为和认知的协同性研究.上海:上海科学技术出版社,2000.
[75] (比)普利高津著,湛敏译.确定性的终结—时间、混沌与新自然法则.上海:上海科学技术出版社,1998.
[76] (德)迈因策尔K著,曾国屏译.复杂性中的思维—物质、精神和人类的复杂动力学.北京:中央编译出版社,1999.
[77] (美)约翰·霍兰著,周晓牧等译.隐秩序—适应性造就复杂性.上海:上海科技教育出版社,2000.
[78] 孙家捅,舒宁,关泽群.遥感原理、方法与应用.北京:测绘出版社,1997.
[79] 张钧屏,方艾里,万志龙.对地观测与对空监视.北京:科学出版社,2001.
[80] 李小文,汪骏发,王锦地,柳钦火.多角度与热红外对地遥感.北京:科学出版社,2001.
[81] 肖峰.人造地球卫星轨道摄动理论.长沙:国防科技大学出版社,1997.
[82] 李济生.人造卫星精密轨道确定.北京:解放军出版社,1995.
[83] (日)遥感研究会编,刘勇卫,贺雪鸿译.遥感精解.北京:测绘出版社,1993.
[84] M.I.斯科尔尼克主编,谢卓译.雷达手册.北京:国防工业出版社,1978.
[85] 承继成,郭华东,史文中.遥感数据的不确定性问题.北京:科学出版社,2004.
[86] 魏钟铨等.合成孔径雷达卫星.北京:科学出版社,2001.
[87] 李德毅,史雪梅,孟海军.隶属云和隶属云发生器.计算机研究和发展,1995,42(8):32—41.
[88] Schoeberl M, Bristow J, Raymond C. Intelligent distributed spacecraft infrastructure. Earth Science Enterprise Technology Planning Workshop, 2001.
[89] Hughes S P, Hall C D. Mission performance measures for spacecraft formation flying. Proceedings of the 1999 Flight Mechanics Symposium. God- dard Space Flight Center, 1999. 309-318.
[90] Mandutianu S, Hadaegh F, Elloit P. Multi-agent syatem for formation flying missions. IEEE Aerospace and Electronic Systems Society. Proceedings of the 2001 IEEE Aerospace Conference. Piscataway, NJ: IEEE Inc. , 2001. (6) : 2793-2802.
[91] Kang W, Sparks A, Banda S. Multi-satellite formation and reconfiguration. Proceedings of the 2000 American Control Conference. 2000. 1 (6) : 379-383.
[92] Mandutianu S, Hadaegh F, Elliot P. Multi-agent system for formation flying missions. Proceedings of 2001 IEEE Aerospace Conference. Piscataway, NJ: IEEE Inc. , 2001. (6) : 2793-2802.
[93] Knoblock EJ, Wallett T M, Konangi V K, Bhasin K B. Network configuration analysis for formation flying satellites Proceedings of 2001 IEEE Aerospace Conference. Piscataway, NJ: IEEEInc. , 2001. (2) : 991-1000.
[94] Chien S, et al. The techsat-21 autonomous space science agent. AAMAS'02, Bologna, Italy, 2002.
[95] Barrett A. Autonomy architectures for a constellation of spacecraft. International Symposium on Artificial Intelligence Robotics and Automation in Space (ISAIRAS). Noordwijk, The Netheflands, 1999.
[96] Stroupe A W, et al. Technology for autonomous space system. CMU-RI-TR-00-02, Carnegie Mellon University, 2002.
[97] Sherwood R, et al. Next generation autonomous operations on a current generation satellite. 5th International Symposium on Reducing the Cost of Spacecraft Ground Systems and Operations (RCSGSO 2003). Pasadena, CA. 2003.
[98] Bernard D, et al. Spacecraft autonomy flight experience: the DS1 remote agent experiment. AIAA-99-4512. 1999.
[99] Campbell M E, Bohringer K F. Intelligent satellite teams for space systems. 2nd International Conference on Integrated Micro-nanotechnology for Space Applications. 1999.
[100] Rouff C, Truszkowski W. A process for introducing agent technology into Space missions. Proceedings of 2001 IEEE Aerospace Conference. Piscataway, NJ: IEEE Inc. 2001. (6) : 2743-2750.
[101] Schetter T, Campbell M, Surka D. Comparison of multiple agent-based organizations for satellite constellations. 2000 FLAIRS AI Conference Proceedings. Orlando, Florida, 2000.
[102] Zetocha P. Satellite cluster command and control. IEEE Aerospace and Electronic Systems Society. Proceedings of 2000 IEEE Aerospace Conference. Piscataway, NJ: IEEE Inc. , 2000. (7) : 49-54.
[103] 吴志革.陆军武器系统分析.北京:兵器工业部兵器系统工程研究所,1985
[104] Dersin P, Levis A H. Large system effectiveness analysis[R]. LIDS—FR—1072, 1981.
[105] Levis A H, Houpt P K, Andreadakis S K. Effectiveness Analysis of Automotive Systems[R]. LIDS—P—1383, 1984.
[106] Sproles N. The difficult problem of establishing measures of effectiveness for command and control: a system engineering perspective. System Engineering, 2000, 4 (2).
[107] 李树楷,薛永祺.高效三维遥感集成技术系统.北京:科学出版社,2000。
[108] 韩心志,焦世举.航天光学遥感辐射度学.哈尔滨:哈尔滨工业大学出版社,1994.
[109] 赵英时等.遥感应用分析原理与方法.北京:科学出版社,2003.
[110] 中国大百科全书编辑委员会.中国大百科全书—自动控制与系统工程卷.北京:中国大百科全书出版社,1991.
[111] 林象平.雷达对抗原理.西安:西北电讯工程学院出版社,1985.
[112] 马蔼乃.遥感信息模型.北京:北京大学出版社,1997.
[113] 张守信.GPS卫星测量定位理论与应用.长沙:国防科技大学出版社,1996.
[114] Tollefson M V. , Preiss B K. Space based radar constellation optimization. Proceedings of 1998 IEEE Aerospace Conference. Piscataway, NJ: IEEE Inc. , 2000. (3) : 379-390.
[115] 谢红卫,宫二玲,贺勇军.时变结构多阶段任务系统的可靠度研究.国防科技大学学报,1999,21(5):41-45.
[116] 贺勇军.载人航天测控网系统可靠性综合计算.长沙:国防科技大学研究生院,1999.
[117] Bavoso S J, Rothman E, et al. HiRel: Hybrid Automated Reliability Predictor(HARP) integrated reliability tool system(Ver7. 0). NTIS NO. N95-22603/1/HDM, 1995.
[118] 周广涛.计算机辅助可靠性工程.北京:宇航出版社,1990.
[119] 潘吉安.可靠性评估及其应用软件的开发.电子产品可靠性和环境实验,1997,(5):7-11.
[120] 曹晋华,程侃.可靠性数学引论.北京:科学出版社,1986.
[121] 梅启智等.系统可靠性工程基础.北京:科学出版社,1987.
[122] 贺勇军,谢红卫.复杂系统可靠度的CLTM建模及递归综合算法.国防科技大学学报,2003,25(4):102—106.
[123] 贺勇军.复杂系统可靠度综合计算平台的设计实现.航空计算技术,2003,33(3):51-55.
[124] Zeigler B P. Theory of modelling and simulation. New York: John Wiley & Sons, Inc. , 1976.
[125] 艾什比.大脑设计.北京:商务印书馆,1991.
[126] 王维平,朱一凡,华雪倩,张汉江.离散事件系统建模与仿真.长沙:国防科技大学出版社,1997.
[127] Khosla R. Intelligent hybrid multi-agent computational architecture for complex systems. Systems,.Man, and Cybernetics, 1997. 1997 IEEE International Conference on Computational Cybernetics and Simulation. 1997. (5): 4471-4476
[128] 许国志.系统科学与工程研究.上海:上海科学教育出版社,2000.
[129] (英)欧阳莹之著,田宝国等译.复杂系统理论基础.上海:上海科技教育出版社,2002.
[130] 王连成.工程系统论.北京:中国宇航出版社,2002.
[131] Dahl O J, Nygard K. Simula—an algol-based simulation language. Communications ACM, 1996, 9: 671-678.
[132] Marciniak J. Encyclopedia of software engineering. NewYork: John Wiley&Sons, 1994.
[133] Zeigler B P. Object-oriented simulation with hierarchical, modular models: intelligent agents and endomorphie systems. New York: Academic Press, 1990.
[134] Fishwick P A. Multi-modeling as a unified modeling framework. Proceedings of the 1993 Winter Simulation Conference. Piscataway, NJ: IEEE Inc. 1993. 580-581.
[135] Miller V T., Fishwick P A. Graphic modeling using heterogeneous hierarchical models. Proceedings of the 1993 Winter Simulation Conference. Piscataway, NJ: IEEE Inc. 1993. 612-617.
[136] Miller V T, Fishwick P A. Hybrid heterogeneous hierarchical models for system simulations. International Journal in Computer Simulation, 1995, (5): 209-227.
[137] Zeigler B P, Praehofe H, Kim T G. Theory of modeling and simulation (Second Edition). San Diego, USA: Academic Press, 2000.
[138] Corbin M J, Butler G F. MulTiSIM: An object-based distributed framwork for mission simulation. Simulation Practice and Theory. 1996 (3): 383-399.
[139] Wiant, Michael, Mitrione, Michael F, Backer, Kim. Object-oriented architectures for simulation of complex systems. The Proceedings of the Summer Computer Simulation Conference. 1996. 306-309.
[140] Wooldridge M. An introduction to multiagent systems. New York: John Wiley& Sons Inc., 2002.
[141] Gerd Wagner, Florin Tulba. Agent-oriented modeling and agent-based simulation. Giorgini P and Henderson-Sellers B. Proceedings of 5th Int. Workshop on Agent-Oriented Information Systems (AOIS-2003), ER2003 Workshops. Springer-Verlag, LNCS, 2003.
[142] Seungman L, Pritchett A, Goldsman D. Hybrid agent-based simulation for analyzing the National Airspace System. Proceedings of the 2001 Winter Simulation Conference. Piscataway, NJ: IEEE Inc. 2001. (2): 1029-1037.
[143] Sanchez S M, Lucas T W. Exploring the world of agent-based simulations: simple models, complex analyses. Proceedings of the 2002 Winter Simulation Conference. Piscataway, NJ: IEEE Inc. 2002. (1): 116-126.
[144] Marietto M B, et al. Requirements analysis of agent-based simulation, platforms: state of the art and new prospects. Proceedings of the MABS 2002 (Workshop on Multi-Agent Based Simulation), First International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS2002), Bologna, July 15-17, 2002.
[145] Drogoul A, Vanbergue D, Meurisse T. Multi-agent based simulation: where are the agents. Sichman J S, Bousquet F, Davidsson P. Multi-Agent-Based Simulation, Third International Workshop, MABS 2002, Bologna, Italy, July 15-16, 2002, Revised Papers. Lecture Notes in Computer Science 2581, Springer, 2003.
[146] Davidsson P. Multi agent based simulation: beyord social simulation. Scott Moss, Paul Davidsson. Multi-Agent-Based Simulation, Second International Workshop, MABS 2000, Boston, MA, USA: July, 2000. Revised and Additional Papers. Lecture Notes in Computer Science 1979, Springer, 2001.
[147] Wickenberg T, Davidsson P. On multi agent based simulation of software development processes. Multi-Agent Based Simulation II, LNAI Vol. 2581, Springer, 2003.
[148] Papp Z, Hoeve H J. A multi-agent based modeling and execution framework for complex simulation , control and measuring tasks . http : //www. tpd. tno. nl/smartsite87. Html.
[149] Mardhana E, Far B H. Design issues on multi-agent system simulation framework: implications from agent design strategy and architecture. IECI Japan Workshop, 2001.
[150] Wooldridge M, Jennings N R. Intelligent agent: theory and practice. Knowledge Engineering Review, 1995, 10 (2) : 115-152.
[151] Weiss G . Multiagent System : A modern approach to distributed artifical intelligence. Cambridge, MA: MIT Press, 1999.
[152] Bradshaw J M. Software agent. Cambridge, MA: AAAI Press/MIT Press, 1997.
[153] Knapik M, Johnson J. Developing intelligent agents for distributed systems. New York: McGraw-Hill, 1998.
[154] Finin T, Fritzson R, McKay D, et al. An Overview of KQML: A Knowledge Query and Manipulation Language. Baltimore County, USA : Department of Computer Science, University of Maryland, 1992.
[155] Van H, Parunak D, Savit R, Riolo R L. Agent-based modeling vs. equation-based modeling: a case study and users' guide. Proceedings of Multi-agent systems and Agent-based Simulation (MABS'98). 10-25, Springer, LNAI 1534, 1998.
[156] Iglesias C A, GarijoM, Gonzalez JC. A survey of agent-oriented methodologies. In Muller, J. P. , Singh, M. , and Rao, A. S. , editors. Intelligent Agents V: Proceedings of the ATAL'98, LNAI 1555. Springer.
[157] Truszkowsk W , Zoch D , Smith D . Autonomy for constellations . http://agents, gsfc. nasa. gov/papers.
[158] Dorais G A, NicewarnerK. Adjustably autonomous multi-agent plan execution with an internal spacecraft free-flying robot prototype. Proceedings of ICAPS'03 Workshop on Plan Execution. Trento, Italy. June, 2003.
[159] Das S, Gonsalves P, Krikorian R, Truszkowski W. Multi-agent planning and scheduling environment for enhanced spacecraft autonomy. 5th International Symposium on Artificial Intelligence, Robotics and Automation in Space. ESTEC. Noordwijk, The Netherlands, 1999.
[160] Muler JP, Pischel M, Thiel M. Modeling reactive behavior in vertically layered agent architectures. M. Woodridge and N. R. Jennings. Intelligent Agent: Theories, Architectures and Languages, Lecture Notes in Artificial Intelligence 890. Berlin: Springer Verlag , 1995. 261-276.
[161] Kitts C, Swartwout M. Autonomous operations experiments for the distributed emerald nanosatellite mission. 14th Annual AIAA/USU Conference on Small Satellites. Logan, Utah, The United States: 2000.
[162] O'Hare G M P, Jennings NR. Foundation of distributed artificial intelligence. New York: John Willey & Sons, 1996.