脉冲星信号的获取识别及其在编队相对导航中的应用研究
|
摘要
新世纪的太空资源争夺日趋激烈,世界各国开展了针对未来空间的应用研究,其间脉冲星导航作为传统导航技术的挑战者和有益补充,成为今后研究和探讨的焦点。采用脉冲星信号作为导航信息的来源,能够避免近地导航系统作用范围小的缺点,又完全独立,不受使用权限的限制,同时还能提供时间、姿态、位置等多方面的导航信息。对脉冲星的导航前景进行分析,同时对关键性技术进行攻关和突破,有利于在激烈的竞争中占据主导地位。本文结合“十一五”预研背景项目和国家高技术研究发展计划(863)项目,对脉冲星信号处理进行深入研究,重点解决导航信号的获取、识别问题以及基于脉冲星观测的姿态测量问题、航天器间相对距离测量问题,具体工作如下:
首先在分析课题的目的和意义,广泛地总结和分析现有导航系统的发展概况的基础上,通过与现有的导航系统进行对比,结合航天器编队飞行的特点,详细地阐述并分析了脉冲星信号获取、识别及其在空间应用等方面的研究现状。其次针对脉冲星的信号特性讨论了脉冲星的基本分类,对现有的脉冲星辐射机制、信号特性以及谱特性进行分析;对脉冲星特性进行研究,为后续脉冲星信号的识别以及测量奠定理论基础。
针对脉冲星信号的获取技术,提出采用多谱段时频相干接收的方法,通过扩大探测器对脉冲星光子的频率响应范围,降低对单一时间相干累积的依赖,同时利用EMD分解等多种手段用于对脉冲星信号进行去噪声处理,采用近似熵作为EMD信号复原所需测量的后向叠加算法判断阈值,并且在此基础上,提出无阈值的塔式EMD分解的噪声处理方法。
其后针对脉冲星的信号特点,提出了以脉冲星的瞬时频率和瞬时幅度作为不同脉冲星辨识的特征,并采用能量中心频率以及奇异值特征优化降维处理方法对数据进行压缩,再利用BP神经网络算法等方法对脉冲星信号进行自适应识别。第三章的研究方法涉及非平稳信号处理、神经网络以及模式识别方法等。
针对基于X射线脉冲星的姿态测量问题,提出了一种基于X射线脉冲星平行光线多平面观测的姿态测量方法,该方法引入了平行光线观测的设计方法,通过测量不同平面内接收的X射线脉冲星光子能量,以及测量值和各平面之间的相对几何关系,计算出脉冲星矢量的幅值和空间角,从而实现了脉冲星矢量的测量。通过对多颗脉冲星的观测,可以获得多个脉冲星矢量,利用多个矢量能够完成姿态的测量。
最后研究利用脉冲星观测确定航天器编队间相对距离确定的方法,针对脉冲星信号的特性以及编队卫星系统的特点,采用相关处理的方法实现编队航天器系统中相对距离的估计,并对相对距离测量观测所需的脉冲星类型及其频谱特性进行分析,同时针对脉冲星信号的周期特性以及目前星间相对距离估计方法的局限性提出了基于信号子空间旋转实现编队航天器系统中相对距离估计的方法,利用多个脉冲星敏感器的接收数据估计星间相对距离,同时结合脉冲星信号的特征,分析估计的精度,并且利用了实际脉冲星的观测数据进行了数学仿真,仿真结果表明基于子空间旋转的星间相对距离估计能够有效的提高测量的精度。
The competition of space resource in new epoch has undertaken among the countries worldwide and pulsar navigation as the effective substitute and challenge to the traditional counterpart becomes the focus of the research and exploration. Pulsar signal as the source of navigation information is beneficial in the navigation range and on the other hand independent from the usage license limitation. Meanwhile it supplies synchronization, vehicle attitude and position information for spacecraft navigation. Analysis towards pulsar navigation perspectives and key technology breakthrough leads to a predominant position in competition. This thesis combined with the eleventh five years project background and national high technology research development project explores the pulsar processing technology for its application in the navigation of formation flying spacecraft, mainly focus on pulsar signal denoising, identification, and attitude measurement as well as relative ranging based on pulsar navigation, the details as follows.
First of all, on the basis of current research statement, this thesis summarizes the research method and development of pulsars navigation for distributed satellite system, and then by analyzing the research method, this paper indicates the research direction of pulsars navigation for distributed satellite system in future researches.
Secondly the thesis discusses the pulsar classification according to the signal characeristic and the analysis covers the pulsar emission signals and spectrum characteristic which is the theoretical foundation of the pulsar identification and measurements.
Then considering the extraction of pulsar signals, the thesis presents a method of pulsar signal denoising based on empirical mode docomposition. Meawhile entropy is selected as the threshold to decide the operation of postfitting of the signal. Furthermore, a tower-like multiple EMD is derived later.
Considering the pulsar signal's characteristic it is proposed that the identification of pulsars is implemented via instantaneous amplitude and frequency extracted via Hilbert-huang Transformation; Then BP neural network algorithm are respectively applied to identify the different pulsars
Moreover, this paper describes the design, tests and preliminary results of a multiple-plane sensor detecting the X-ray pulsars vectors to acquire the spacecraft attitude. Comparing to the star sensors or other traditional attitude measuring, the multiple-plane sensor has made an adversary and new effort by inventing a multiple-plane structure, with the orthogonal vectors pointing towards the different directions. By measuring the power received by each plane and considering the geometry relationship of the planes, the sensor computes the pulsars vector from a certain pulsar. Therefore, the attitude of the spacecraft can be acquired if vectors from several different pulsars is recognized and specified. Accordingly the simulation is established and the result proves its charming feasibility in future spacecraft missions.
Finally, a novel method of intersatellite ranging calibration is presented based on the observation of pulsars. According to the method intersatellite range projected in the direction of pulsars can be directly determined by correlating the pulsar signals detected on different spacecrafts in a distributed satellite system. Meanwhile accuracy of the method is derived based on the analysis of the celestial sources and their spectras. The method is evaluated using the realistic simulation of the pulsars and orbit information of distributes spacecraft. The result verifies the feasibility of in the application of the future distributed satellite system. Then according to the method intersatellite range projected in the direction of pulsars can be directly determined by using the rotational invariance of the pulsar signals detected on different spacecrafts in a distributed satellite system. Meanwhile accuracy of the method is derived based on the analysis of the celestial sources and their spectrums. The method is evaluated using the realistic simulation of the pulsars and orbit information of distributed spacecraft. The result verifies the feasibility of in the application of the future distributed satellite system.
首先在分析课题的目的和意义,广泛地总结和分析现有导航系统的发展概况的基础上,通过与现有的导航系统进行对比,结合航天器编队飞行的特点,详细地阐述并分析了脉冲星信号获取、识别及其在空间应用等方面的研究现状。其次针对脉冲星的信号特性讨论了脉冲星的基本分类,对现有的脉冲星辐射机制、信号特性以及谱特性进行分析;对脉冲星特性进行研究,为后续脉冲星信号的识别以及测量奠定理论基础。
针对脉冲星信号的获取技术,提出采用多谱段时频相干接收的方法,通过扩大探测器对脉冲星光子的频率响应范围,降低对单一时间相干累积的依赖,同时利用EMD分解等多种手段用于对脉冲星信号进行去噪声处理,采用近似熵作为EMD信号复原所需测量的后向叠加算法判断阈值,并且在此基础上,提出无阈值的塔式EMD分解的噪声处理方法。
其后针对脉冲星的信号特点,提出了以脉冲星的瞬时频率和瞬时幅度作为不同脉冲星辨识的特征,并采用能量中心频率以及奇异值特征优化降维处理方法对数据进行压缩,再利用BP神经网络算法等方法对脉冲星信号进行自适应识别。第三章的研究方法涉及非平稳信号处理、神经网络以及模式识别方法等。
针对基于X射线脉冲星的姿态测量问题,提出了一种基于X射线脉冲星平行光线多平面观测的姿态测量方法,该方法引入了平行光线观测的设计方法,通过测量不同平面内接收的X射线脉冲星光子能量,以及测量值和各平面之间的相对几何关系,计算出脉冲星矢量的幅值和空间角,从而实现了脉冲星矢量的测量。通过对多颗脉冲星的观测,可以获得多个脉冲星矢量,利用多个矢量能够完成姿态的测量。
最后研究利用脉冲星观测确定航天器编队间相对距离确定的方法,针对脉冲星信号的特性以及编队卫星系统的特点,采用相关处理的方法实现编队航天器系统中相对距离的估计,并对相对距离测量观测所需的脉冲星类型及其频谱特性进行分析,同时针对脉冲星信号的周期特性以及目前星间相对距离估计方法的局限性提出了基于信号子空间旋转实现编队航天器系统中相对距离估计的方法,利用多个脉冲星敏感器的接收数据估计星间相对距离,同时结合脉冲星信号的特征,分析估计的精度,并且利用了实际脉冲星的观测数据进行了数学仿真,仿真结果表明基于子空间旋转的星间相对距离估计能够有效的提高测量的精度。
The competition of space resource in new epoch has undertaken among the countries worldwide and pulsar navigation as the effective substitute and challenge to the traditional counterpart becomes the focus of the research and exploration. Pulsar signal as the source of navigation information is beneficial in the navigation range and on the other hand independent from the usage license limitation. Meanwhile it supplies synchronization, vehicle attitude and position information for spacecraft navigation. Analysis towards pulsar navigation perspectives and key technology breakthrough leads to a predominant position in competition. This thesis combined with the eleventh five years project background and national high technology research development project explores the pulsar processing technology for its application in the navigation of formation flying spacecraft, mainly focus on pulsar signal denoising, identification, and attitude measurement as well as relative ranging based on pulsar navigation, the details as follows.
First of all, on the basis of current research statement, this thesis summarizes the research method and development of pulsars navigation for distributed satellite system, and then by analyzing the research method, this paper indicates the research direction of pulsars navigation for distributed satellite system in future researches.
Secondly the thesis discusses the pulsar classification according to the signal characeristic and the analysis covers the pulsar emission signals and spectrum characteristic which is the theoretical foundation of the pulsar identification and measurements.
Then considering the extraction of pulsar signals, the thesis presents a method of pulsar signal denoising based on empirical mode docomposition. Meawhile entropy is selected as the threshold to decide the operation of postfitting of the signal. Furthermore, a tower-like multiple EMD is derived later.
Considering the pulsar signal's characteristic it is proposed that the identification of pulsars is implemented via instantaneous amplitude and frequency extracted via Hilbert-huang Transformation; Then BP neural network algorithm are respectively applied to identify the different pulsars
Moreover, this paper describes the design, tests and preliminary results of a multiple-plane sensor detecting the X-ray pulsars vectors to acquire the spacecraft attitude. Comparing to the star sensors or other traditional attitude measuring, the multiple-plane sensor has made an adversary and new effort by inventing a multiple-plane structure, with the orthogonal vectors pointing towards the different directions. By measuring the power received by each plane and considering the geometry relationship of the planes, the sensor computes the pulsars vector from a certain pulsar. Therefore, the attitude of the spacecraft can be acquired if vectors from several different pulsars is recognized and specified. Accordingly the simulation is established and the result proves its charming feasibility in future spacecraft missions.
Finally, a novel method of intersatellite ranging calibration is presented based on the observation of pulsars. According to the method intersatellite range projected in the direction of pulsars can be directly determined by correlating the pulsar signals detected on different spacecrafts in a distributed satellite system. Meanwhile accuracy of the method is derived based on the analysis of the celestial sources and their spectras. The method is evaluated using the realistic simulation of the pulsars and orbit information of distributes spacecraft. The result verifies the feasibility of in the application of the future distributed satellite system. Then according to the method intersatellite range projected in the direction of pulsars can be directly determined by using the rotational invariance of the pulsar signals detected on different spacecrafts in a distributed satellite system. Meanwhile accuracy of the method is derived based on the analysis of the celestial sources and their spectrums. The method is evaluated using the realistic simulation of the pulsars and orbit information of distributed spacecraft. The result verifies the feasibility of in the application of the future distributed satellite system.
引文
[1] Sabol C, Burs R, Craig A, et al. Satellite Formation Flying Design and Evolution[J]. Journal of Spacecraft and Rockets, 2001, 38(2): 270-278.
[2] Fu Huiqing, Ling Mo, et al. Calibration specification for global positioning system (GPS Receiver)[J]. State Administration for Quality Inspection and Quarantine, 2004: 1118-2004.
[3]肖业伦,张晓敏.编队飞行卫星群的轨道动力学特性与构型设计[J].宇航学报, 2001, 22(4):7-12.
[4] Luu K, Martin M, Stallard M. University Nanosatellite Distributed Satellite Capabilities to Support TechSat 21[C]. 13th AIAA/USU Conference on Small Satellites, 1999:1-9.
[5]王飞行.基于AOS建议的GPS自主定位数据传输[J].飞行器测控学报,2004, (3):119-120.
[6]徐仁新.天体物理导论[M].北京:北京大学出版社, 2006:3-4.
[7] Graven, P., Collins,J., Sheikh, S.,Hanson, J., Ray, P., Wood, K. XNAV for Deep Space Navigation[C]. Proceedings of 31st AnnualAAS Guidance and Control Conference, 2008:1-16.
[8]帅平,陈绍龙,吴一帆,张春青,李明. X-射线脉冲星导航原理[J].宇航学报. 2008, 28(6):1538-1541.
[9] Graven P, Collins J, Sheikh S and Hanson J E. XNAV beyond the Moon[C]. Institute of Navigation 63rd Annual Meeting, Cambridge, MA, April 23-25, 2007:423-431.
[10] Taylor J H. Millisecond pulsars: Nature’s most stable clocks[J]. Proceeding of IEEE, 1991, 79:1054-1062.
[11] Mallat S. Theory for multiresolution signal decomposition: The wavelet representation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1989, 11(7): 674 - 693.
[12] Taylor J H. Pulsar Timing and Relativistic Gravity[J]. Philosophical Transactions of the Royal Society of London, 1992,341: 117-134.
[13]朱晓明,廖褔成,唐远炎.基于小波分析的脉冲星信号消噪处理[J].天文学报, 2006, 47(3):328-335.
[14]阎迪,许录平,谢振华,脉冲星信号的模糊阈值小波降噪算法[J].西安交通大学学报, 2007, 49(10):1193-1197.
[15]李建勋,柯熙政.基于小波模极大值相关信息的脉冲星标准脉冲轮廓累积方法[J].天文学报, 2008, 49(4):394-402.
[16]李建勋,柯熙政,汪丽.基于高阶统计量自适应滤波的毫秒脉冲星信号处理[J].西安理工大学学报, 2009, 25(1):76-79.
[17]谢振华,许录平,倪广仁.基于双谱的脉冲星累积脉冲轮廓时间延迟测量[J].物理学报, 2008, 57(10):6683-6689
[18]苏哲,许录平,王光耀,谢振华,刘劼.基于离散方波变换的脉冲星微弱信号周期性检测[J].宇航学报, 2009, 30(6):2242-2247.
[19]边肇祺,张学工.模式识别.北京:清华大学出版社, 2000: 2-3.
[20] Zhang J, Zhou X, Wang H, Suffredini A; Lin Zhang, Huang Y, Wong S. Bayesian Peptide Peak Detection for High Resolution TOF Mass Spectrometry[J]. IEEE Transactions on Signal Processing, 2010, 58(11): 5883-5894.
[21]林杰.脉冲星识别算法及其矢量测量技术研究[D].哈尔滨工业大学学位论文. 2010, 9:34-56.
[22]赵智云.γ射线脉冲星的代参数和能谱分析[J].天文研究与技术, 2009, 6(4):259-263.
[23] Taylor J H, Stinebring D R. Recent Progress in the Understanding of Pulsars[J]. Annual Review of Astronomy and Astrophysics. 1986, 24(1):285-327.
[24] Lyne A G, Smith F G. Pulsar Astronomy[M], Cambridge University Press, Cambridge UK, 1998:128-136.
[25] Manchester R N, Taylor J H. Pulsars[M]. W. H. Freeman and Company, San Francisco CA. 1977:13-25.
[26]李宗云,丁月蓉.脉冲星的分类[J].中国科学A辑, 1991, 7:752-761.
[27]谢振华,许录平,倪广仁等.基于一维选择线谱的脉冲星辐射脉冲信号辨识[J].红外与毫米波学报, 2007, 26(3): 187-195.
[28]刘劲,马杰,田金文.基于小波和双谱的脉冲星信号识别[J].信息控制, 2009, 38(2):249-252.
[29]刘蓉,段福庆,刘三阳,吴福朝.基于小波特征的星系光谱分类[J].电子学报, 2005, 33(11):2059-2062.
[30]王首勇,朱光喜,唐远炎.应用最优小波包变换的特征提取方法[J].电子学报, 2003, 31(7):6300-6303.
[31]陈志新,徐金梧,杨德斌,章立军.基于经验模态分解的混沌噪声背景下弱信号检测与信号提取[J].机械科学与技术. 2006, 25(2):220-224.
[32]姚鹏,叶学义,庄镇泉,吴亮,李斌.基于局部频率特征和局部方向特征的虹膜识别算法[J].电子学报. 2007, 35(4):663-667.
[33]张静,王国宏,杨智勇.基于局部特征核主成分分析的SAR图像识别方法[J].宇航学报, 2008, 29(3):698-705.
[34]田进,李言俊,张科,郭俊锋.基于高斯chirplet时频原子参数自适应时频分布图的不变矩特征提取方法研究.宇航学报, 2008, 29(5):1656-1661
[35] Virmajoki O. Pairwise Nearest Neighbor Method Revisited[D]. University of Joensuu, 2004:3-4.
[36] Baumes J, Goldberg M, Krishnamoorthy M, et al. Finding Communities By Clustering A Graph Into Overlapping Subgraphs[C]. IADIS International Conference on Applied Computing 2005:97-105.
[37]周辉仁,郑丕谔,牛犇,宗蕴.基于递阶遗传算法和BP网络的模式分类方法[J].系统仿真学报, 2009, 21(8):2243-2247.
[38] Billings S A, Zheng G L. Radial basis function network configuration using genetic algorithms[J]. Neural Network. 1995, 8(6):877-890.
[39]蒋宗礼.人工神经网络导论[M].北京:高等教育出版社. 2001:8.
[40] Chen S, Wu Y, LUK B L. Combined genetic optimization and regulation orthogonal least squares learning for radial basis function networks[J]. Neural Networks, 1999, 10(5):1239-1243.
[41] F. Leung. Tuning of the structure and parameters of a neural network using an improved genetic algorithm[J]. IEEE Transactions on Neural Networks, 2003, 14(1): 79-81.
[42]李伟超,宋大猛,陈斌.基于遗传算法的人工神经网络[J].计算机工程与设计, 2006, 27(2): 316-318.
[43]郑丕谔,马艳华. RBF神经网络的递阶遗传训练新方法[J].控制与决策, 2000, 15(2): 165-168.
[44] Hewish A, Bell S J, Pilkington J D, et al. Observation of a Rapidly Pulsating Radio Source[J]. Nature, 1968, 217: 709-713.
[45] Kraushaar W L, Clark G W, Garmire G P, et al. High-energy cosmicgamma-ray observations from the OSO-3 satellite[J]. Astrophysical Journal, 1966, 177: 341-363.
[46] S. Singer. The Vela satellite Program for Detection of High-altitute Detonations[J]. Proceedings of IEEE, 1965, 53(12):1935-1951.
[47] Giacconi R, Kellogg E, Gorenstein P, Gursky H, Tananbaum H. Mission Overview[J]. Astronomy physic Journal, 1971,165:27.
[48] Allen, Jahoda, Whitlock. HEAO-1 and the A2 Experiment[J]. Legacy, 1994, 5:13-20.
[49] Petre R. ROSAT: The Roentgen Satellite. 2004, March[OL] http://heasarc.gsfc.nasa.gov/docs/rosat/rosat.html.
[50] Gruber D E, Blanco P R, Heindl W A, Pelling M R, et al. The high energy X-ray timing experiment on XTE[J]. Astronomy Astrophysics, 1996, 120:641.
[51] Weisskopf M C. The Chandra X-Ray Observatory: An overview[J]. Advances in Space Research, 2003,32(10): 2005-2011.
[52] Blanchard A, Vauclair S C, SadatNew R. XMM observations of high redshift X-ray clusters and cosmological interpretation[J]. Astronomy Reviews, 2005,49:69-73.
[53] Storey J W V, Ashley M C, Burton B. An Automated Astrophysical Observatory for Antarctica[J]. Publications of the Astronomical Society of Australia, 1996, 13(1):35-38.
[54] Kijak J, Gil J. Radio emission regions in pulsars. Monthly[J]. Notation Research of Astronomy Society, 1998, 299:855-861.
[55] Manchester R N, Hobbs G B, Teoh A, et al. The Australia Telescope National Facility Pulsar Catalogue[J]. The Astronomical Journal, 2008, 129:1993-2006.
[56]康连生.在乌鲁木齐天文站25m天线上进行的脉冲星观测[J].天文学进展, 1997, 15(2):169-172.
[57] Downs G S. Interplanetary Navigation Using Pulsating Radio Sources[R]. JPL-TR-32-1594, Technical Report.1974:10-15.
[58] Chester T J, Butman S A. Navigation using X-ray pulsars[R]. TDA Progress Report March and April 1981: 42-63.
[59] Wood K S. Navigation Studies Utilizing the NRL-801 Experiment and the ARGOS Satellite.Small Satellite Technology and Applications III[J]. SPIE Proceedings, 1993,1940:105-116.
[60] Hanson J. Principles of X-ray navigation[D]. Dept. Aeronautics andastronautics Stanford Univ Standford. 1996:1-50.
[61] Wood K S. The HEAO-1 X-ray Source Catalog[J] The Astrophysical Journal Supplement Series. 1984, 56:507-649.
[62] Sheikh S I. The Use of Variable Celestialx-Ray Sources For Spacecraft Navigation[D]. Doctor Thesis of Maryland University. 2005:221-229.
[63] Taylor J H, Weisberg J M. Further Experimental Tests of Relativistic Gravity Using the Binary Pulsar PSR 1913+16[J]. Astrophysical Journal. 1989, 345:434-450.
[64]仲崇霞.综合脉冲星时算法及脉冲星时应用[D].中国科学院学位论文, 2007:55-70.
[65]熊凯,魏春岭,刘良栋.基于脉冲星的空间飞行器自主导航技术研究[J].航天控制, 2007, 25(4):36-39.
[66]谢振华,许录平,倪广仁.基于最大似然的X射线脉冲星空间定位研究[J].宇航学报, 2007, 28(6):1605-1609.
[67]孙景荣,许录平,梁逸升,谢振华,倪广仁.中心差分Kalman滤波方法在X射线脉冲星导航中的应用[J].宇航学报, 2008, 29(11):1829-1833.
[68] Sheikh S I, Pines D J, Ray P S, et al. The Use of X-ray Pulsars for Spacecraft Navigation[J]. Advances in the Astronautical Sciences. 2005, 119:105-119.
[69] Sheikh S I, Pines D J, Ray P S, et al. Spacecraft navigation using X-ray Pulsars[J]. Journal of Guidance Control and Dynamics, 2006, 29(1):49-63.
[70] Sheikh S I, Ronald W, Hellings R, et al High-Order Pulsar Timing For Navigation[C]. Institute of Navigation 63rd Annual Meeting. 2007, Cambridge, Massachusetts:433-443.
[71] Ramkumar P S, Deshpande A A. Real-Time Signal Processor for Pulsar Studies[J].Astrophys and Astronomy, 2001, 22:321-342.
[72] Riba J, Sala J, Vazquez G. Conditional Maximum Likelihood Timing Recovery: Estimators and Bounds[J]. IEEE Transactions on Signal Processing, 2001, 49(4):835-851.
[73] Ray P S, Wood K S, Sheikh S I. Deep-Space Navigation Using Celestial X-ray Sources[C]. ION New Technology Meeting 2008, San Diego, CA, 2008:101-109.
[74] Golshan A R, Sheikh S I. On Pulse Phase Estimation and Tracking of Variable Celestial X-Ray Sources[C]. Institute of Navigation 63rd Annual Meeting, Cambridge, MA, 2007:413-423.
[75] Ashby N, Golshan A R. Minimum Uncertainties in Position and Velocity Determination using X-ray Photons from Millisecond Pulsars[C]. ION New Technology Meeting, San Diego, CA, 2008: 110-116.
[76] Ashby N, Howe D A. Relativity and timing in X-ray Pulsar navigation[C] Proceedings of the IEEE International Frequency Control Symposium and Exposition, 2006:767-770.
[77]朱振才,杨根庆,余金培等.微小卫星组网与编队技术的发展[J].上海航天, 2004, 6: 46-49.
[78]马涛,郝云彩,马骏,周胜利.编队飞行卫星的星间跟踪与测量技术综述[J].航天控制. 2005, 23(3):91-97.
[79] Bauer F, Bristow J, Folta D, Hartman K, et al. Satellite Formation Flying Using an Innovative Autonomous Control System Environment[C]. AIAA/AAS Astrodynamics Specialists Conference, 1997:657-666.
[80] Adams C, Robertson A, Zimmerman K, et al. Technologies for Spacecraft Formation Flying[C]. Proceedings of the ION GPS-96 Conference, 1996: 1321-1330.
[81] Long A, Kelbel D, Lee T, et al., Relative Navigation of Formation-Flying Satellites[C]. International Symposium on Formation Flying Missions & Technologies. Toulouse, France, 2002:1-8.
[82] Stadter P A, Heins R J, Chacos A A, et al. Enabling Distributed Spacecraft Systems with the Crosslink Transceiver[C]. AIAA Space 2001 Conference and Exposition, Albuquerque, 2001 August:28-30,.
[83] Purcell G, Kuang D, Lichten S, et al. Autonomous Formation Flyer (AFF) Sensor Technology Development[C]. 21st Annual AAS Guidance and Control Conference, Breckenridge, Colorado, 1998: 98-062.
[84] Kawano I, Wakabayashi Y. In-Orbit Demonstration Concept for the Space Platform in NASDA-Rendezvous Docking System[C]. IAF 1989, Malaga, 1989: 1-5.
[85] Tietz J C, Kelly J H. Development of an Autonomous Video Rendezvous and Docking System[R]. Martin Marietta Aerospace Report, Martin Marietta Aerospace: Denver Aerospace, Denver, CO, 1982: 1-15.
[86] Ho C C J, McClamroch N H. Automatica Spacecraft Docking Using Computer Vision Based Guidance and Control Techniques[J]. Journal of Guidance, Control, and Dynamics.1993, 16(2): 281-288.
[87] Goddard J S, Jatko W B, Ferrel R K, et al. Roubust Determination for Autonomous Docking[C]. 6th Topical Meeting on Robotics and Remote Systems, Monterey, CA, 1995:1-5.
[88]陈世平.空间相机设计与实验[M].北京:宇航出版社, 2003: 121-125.
[89] Clarke T A, Fryer J F, Wang X. The Principal Point and CCD Cameras[J]. Photogrammetric Record, 1998, 16(92): 293-312.
[90]闫野.利用星间测距实现卫星网自主定位[J].空间科学学报, 2000, 20(1):33-37.
[91] Guinot B. Pulsar timing[J]. Astronomy & Astrophysics, 1988, 256:192-370.
[92] Kapsi V M, Taylor J H, Ryba M F. High-Precision Timing of Millisecond Pulsars. III. Long-Term Monitoring of PSRs B1855+09 and B1937+21[J]. Astrophysics Journal, 428:713-728.
[93]倪广仁,杨廷高,赵当丽.毫秒脉冲星计时-脉冲星观测与研究[M].乌鲁木齐:新疆人民出版社. 2000:197-198.
[94] Emadazahea A A, Speyer J L, Hadaegh F Y. A Parametric Study of Relative Navigation using Pulsars[C]. Institute of Navigation 63rd Annual Meeting, 2007, Cambridge:454-459.
[95] Emadazahea A A, Speyer J L. A Study of Pulsar Signals Modeling and Time Delay Estimation for Relative Navigation of Spacecrafts[C]. ION New Technology Meeting, 2008, San Diego, CA:333-336.
[96]张承民,吴鑫基,贺龙松.脉冲星辐射机制[J].河北工学院学报. 1994, 23(4):77-81.
[97] Rakin M J. Toward an empirical theory of pulsar emission[J]. Astronomy Physics Journal. 1983, 274:359.
[98]吴鑫基,康连生,金声震等.四颗脉冲星在327MHZ观测结果[J].天体物理学报, 1997, (1):7-42.
[99] Morii M, Ktamoto S, Shibazaki N, et al. Suzaku Observation of the Anomalous X-Ray Pulsar[J]. Publications of The Astronomical Society of Japan, 2010,62(5): 1249-1259.
[100] Maron O, Kijak J, Kramer M, et al. Pulsar spectra of radio emission[J]. Astronomy and Astrophysics(Suppl), 2007,147:195-203.
[101] Charles P A, Seward F D. Exploring the X-ray Universe[M],Cambridge University Press, Cambridge UK, 1995:225-227.
[102]周概容.概率论与数理统计基础[M].上海:复旦大学出版社,2004:35-45.
[103] Hanson J, Sheikh S I, Graven P, et al. Noise analysis for X-ray navigation systems[C]. 2008 IEEE/ION Position, Location and Navigation Symposium, USA: IEEE, 2008, Monterey:704-713.
[104] White N E, Nagase F, Parmar A N. The Properties of X-ray Binaries, X-ray Binaries[M]. Cambridge University Press, Cambridge UK, 1995:1-57.
[105]苏哲,王勇,许录平,罗楠.一种新的脉冲星累积脉冲轮廓辨识算法[J].宇航学报, 2010, 31(6):1563-1568.
[106] Ramkumar P S, Deshpande A A. Real-Time Signal Processor for Pulsar Studies[J] J. Astrophys. Astr, 2001, 22:321–342.
[107] Sheikh S I, Ray P, Weiner K, et al. Relative Navigation of Spacecraft Utilizing Bright, Aperiodic Celestrial Sources[C]. ION 63rd Annual Meeting, 2007, Cambridge:201-208.
[108] Shark L K, Yu C. Denoising by optimal fuzzy thresholding in wavelet domain[J]. Electronics Letters, 2000, 36(6):581-582.
[109]杨建军,刘鸿福.基于经验模态分解的探地雷达信号去噪处理[J].计算机应用. 2008,9:29-30.
[110] Huang N E, Long S R, Zhen S. A new view of nonlinear water waves: the hilbert spectrum[J]. Annual Rev Fluid Mechanics, 1999, 31: 417-457.
[111] Huang N E,.The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J], Proceeding of Royal. Socociety, 1998, 454: 903-995.
[112] Boudraa A O, Cexus J C, Saidi Z.EMD-based signal noise reduction[C]. Proceeding of World Academy of Science, Engineering and Technology, 2004, 2: 122-125.
[113]孙伟峰,彭玉华,许建华.基于EMD的激光超声信号去噪方法[J].山东大学学报工学版, 2008, 38(5): 1-6.
[114]陈凤林.一种新的基于EMD模态相关的信号去噪方法[J].西华大学学报, 2009, 8(6): 20-24.
[115]刘劲,马杰,田金文,基于EMD的脉冲星信号消噪算法[J].计算机工程与应用, 2008, 44(20): 212-215.
[116]周建刚,陈印椿.统计物理中熵的定义[J].大连大学学报, 1992, 1(4): 59-63.
[117] Pincus S M. Approximate entropy as a measure of system complexity[C].Proceeding of National academy Sciety, 1991, 88: 2297-2301.
[118] Mallat S G. A theory for Multiresolution signal decomposition: The wavelet Represtation[J]. IEEE trasactions on Pattern analysis and machine intelligence. 1989, 11(7):674-693.
[119] Gardner W. Introduction to Random Processes with Aplications to Signals and Systems[M]. McGraw-Hill. 1990:221-222
[120]邓丽华.基于人工神经网络的手写体数字识别[J].三峡大学学报(自然科学学报), 2005, 27(3): 254-256.
[121] Gardner W A. Stationarizable random processes[J]. IEEE Trans. Information Theory, 1978, 24: 8-22.
[122]郑君里.信号与系统[M].高等教育出版社. 2000: 146-147.
[123] Gardner W A. Measurement of Spectral Correlation[J]. IEEE Trans.On Acoustic, Speech, and Signal Processing. 1986,34:1111-1123.
[124]梁应敞,王树勋.高阶累积量在谱估计中的应用[J].电子学报, 1992, 20(4): 93-96.
[125]田景文,高美娟.人工神经网络算法研究及应用[M].北京:北京理工大学出版社, 2006:26-27.
[126]李关防,惠俊英.基于经验模态分解的模态域MVDR方法研究[J].电子学报, 2009,37(5):942-947.
[127] Wood K S, Fritz G, Hertz P, et al. The USA X-ray Timing Experiment American Physical Society, April Meeting, April 20 - 23, 2002 Albuquerque Convention Center Albuquerque, New Mexico:1-10.
[128]张辉,钟建勇,袁家虎,刘恩海,电路噪声对星敏感器星点定位精度的影响[J].光学精密工程. 2006,10(4):1052-1056.
[129]刘一武,陈义庆,星敏感器测量模型及其在卫星姿态确定系统中的应用[J].宇航学报, 2003, 24(2)162-168.
[130] LIEBE C C. Accuracy performance of star trackers-a tutorial[J]. IEEE Trans. on Aerospace and Electronics Systems. 2002, 38 (2):587-599.
[131] Matsakis D N, Taylor J H, Eubanks T M. A Statistic for Describing Pulsar and Clock Stabilities[J]. Astronomy and Astrophysics, 1997, 326: 924-928.
[132]杨华波,张士峰,蔡洪.无陀螺仪惯性系统构型中安装误差分析与标定[J].中国惯性技术学报, 2007,15(1):39-46.
[133] Roy R, Kailath T. ESPRIT-Estimation of Signal Parameters via RotationalInvariance Techniques[J]. IEEE transactions on acoustics, speech, and signal processing. 1989(37):984-996.
[134] Rao B D, Hari K V S. Performance analysis of Esprit and TAM in determining the direction of estimation of arrival of plane waves in noise[J]. IEEE Transaction on Acoustic Speech Signal Processing, 1989(40):1990-1995.
[135] Kaveh M, Barabell A J. The statistical performance of MUSIC and the minimum norm algorithms in resolving plane waves in noise[J]. IEEE Transaction on Acoustic Speech Signal Processing, 1986(34): 331-340.
[136] Pines D. J. X-ray Source-based Navigation for Autonomous Position Determination[R]. Program. DARPA/ TTO , USA , 2004,571:218-4339.
[137] Nrgaard M. Advances in Derivative free State Estimation for Nonlinear Systems[D]. Technical University of Denmark , 2000, 49:1-33. .
[2] Fu Huiqing, Ling Mo, et al. Calibration specification for global positioning system (GPS Receiver)[J]. State Administration for Quality Inspection and Quarantine, 2004: 1118-2004.
[3]肖业伦,张晓敏.编队飞行卫星群的轨道动力学特性与构型设计[J].宇航学报, 2001, 22(4):7-12.
[4] Luu K, Martin M, Stallard M. University Nanosatellite Distributed Satellite Capabilities to Support TechSat 21[C]. 13th AIAA/USU Conference on Small Satellites, 1999:1-9.
[5]王飞行.基于AOS建议的GPS自主定位数据传输[J].飞行器测控学报,2004, (3):119-120.
[6]徐仁新.天体物理导论[M].北京:北京大学出版社, 2006:3-4.
[7] Graven, P., Collins,J., Sheikh, S.,Hanson, J., Ray, P., Wood, K. XNAV for Deep Space Navigation[C]. Proceedings of 31st AnnualAAS Guidance and Control Conference, 2008:1-16.
[8]帅平,陈绍龙,吴一帆,张春青,李明. X-射线脉冲星导航原理[J].宇航学报. 2008, 28(6):1538-1541.
[9] Graven P, Collins J, Sheikh S and Hanson J E. XNAV beyond the Moon[C]. Institute of Navigation 63rd Annual Meeting, Cambridge, MA, April 23-25, 2007:423-431.
[10] Taylor J H. Millisecond pulsars: Nature’s most stable clocks[J]. Proceeding of IEEE, 1991, 79:1054-1062.
[11] Mallat S. Theory for multiresolution signal decomposition: The wavelet representation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1989, 11(7): 674 - 693.
[12] Taylor J H. Pulsar Timing and Relativistic Gravity[J]. Philosophical Transactions of the Royal Society of London, 1992,341: 117-134.
[13]朱晓明,廖褔成,唐远炎.基于小波分析的脉冲星信号消噪处理[J].天文学报, 2006, 47(3):328-335.
[14]阎迪,许录平,谢振华,脉冲星信号的模糊阈值小波降噪算法[J].西安交通大学学报, 2007, 49(10):1193-1197.
[15]李建勋,柯熙政.基于小波模极大值相关信息的脉冲星标准脉冲轮廓累积方法[J].天文学报, 2008, 49(4):394-402.
[16]李建勋,柯熙政,汪丽.基于高阶统计量自适应滤波的毫秒脉冲星信号处理[J].西安理工大学学报, 2009, 25(1):76-79.
[17]谢振华,许录平,倪广仁.基于双谱的脉冲星累积脉冲轮廓时间延迟测量[J].物理学报, 2008, 57(10):6683-6689
[18]苏哲,许录平,王光耀,谢振华,刘劼.基于离散方波变换的脉冲星微弱信号周期性检测[J].宇航学报, 2009, 30(6):2242-2247.
[19]边肇祺,张学工.模式识别.北京:清华大学出版社, 2000: 2-3.
[20] Zhang J, Zhou X, Wang H, Suffredini A; Lin Zhang, Huang Y, Wong S. Bayesian Peptide Peak Detection for High Resolution TOF Mass Spectrometry[J]. IEEE Transactions on Signal Processing, 2010, 58(11): 5883-5894.
[21]林杰.脉冲星识别算法及其矢量测量技术研究[D].哈尔滨工业大学学位论文. 2010, 9:34-56.
[22]赵智云.γ射线脉冲星的代参数和能谱分析[J].天文研究与技术, 2009, 6(4):259-263.
[23] Taylor J H, Stinebring D R. Recent Progress in the Understanding of Pulsars[J]. Annual Review of Astronomy and Astrophysics. 1986, 24(1):285-327.
[24] Lyne A G, Smith F G. Pulsar Astronomy[M], Cambridge University Press, Cambridge UK, 1998:128-136.
[25] Manchester R N, Taylor J H. Pulsars[M]. W. H. Freeman and Company, San Francisco CA. 1977:13-25.
[26]李宗云,丁月蓉.脉冲星的分类[J].中国科学A辑, 1991, 7:752-761.
[27]谢振华,许录平,倪广仁等.基于一维选择线谱的脉冲星辐射脉冲信号辨识[J].红外与毫米波学报, 2007, 26(3): 187-195.
[28]刘劲,马杰,田金文.基于小波和双谱的脉冲星信号识别[J].信息控制, 2009, 38(2):249-252.
[29]刘蓉,段福庆,刘三阳,吴福朝.基于小波特征的星系光谱分类[J].电子学报, 2005, 33(11):2059-2062.
[30]王首勇,朱光喜,唐远炎.应用最优小波包变换的特征提取方法[J].电子学报, 2003, 31(7):6300-6303.
[31]陈志新,徐金梧,杨德斌,章立军.基于经验模态分解的混沌噪声背景下弱信号检测与信号提取[J].机械科学与技术. 2006, 25(2):220-224.
[32]姚鹏,叶学义,庄镇泉,吴亮,李斌.基于局部频率特征和局部方向特征的虹膜识别算法[J].电子学报. 2007, 35(4):663-667.
[33]张静,王国宏,杨智勇.基于局部特征核主成分分析的SAR图像识别方法[J].宇航学报, 2008, 29(3):698-705.
[34]田进,李言俊,张科,郭俊锋.基于高斯chirplet时频原子参数自适应时频分布图的不变矩特征提取方法研究.宇航学报, 2008, 29(5):1656-1661
[35] Virmajoki O. Pairwise Nearest Neighbor Method Revisited[D]. University of Joensuu, 2004:3-4.
[36] Baumes J, Goldberg M, Krishnamoorthy M, et al. Finding Communities By Clustering A Graph Into Overlapping Subgraphs[C]. IADIS International Conference on Applied Computing 2005:97-105.
[37]周辉仁,郑丕谔,牛犇,宗蕴.基于递阶遗传算法和BP网络的模式分类方法[J].系统仿真学报, 2009, 21(8):2243-2247.
[38] Billings S A, Zheng G L. Radial basis function network configuration using genetic algorithms[J]. Neural Network. 1995, 8(6):877-890.
[39]蒋宗礼.人工神经网络导论[M].北京:高等教育出版社. 2001:8.
[40] Chen S, Wu Y, LUK B L. Combined genetic optimization and regulation orthogonal least squares learning for radial basis function networks[J]. Neural Networks, 1999, 10(5):1239-1243.
[41] F. Leung. Tuning of the structure and parameters of a neural network using an improved genetic algorithm[J]. IEEE Transactions on Neural Networks, 2003, 14(1): 79-81.
[42]李伟超,宋大猛,陈斌.基于遗传算法的人工神经网络[J].计算机工程与设计, 2006, 27(2): 316-318.
[43]郑丕谔,马艳华. RBF神经网络的递阶遗传训练新方法[J].控制与决策, 2000, 15(2): 165-168.
[44] Hewish A, Bell S J, Pilkington J D, et al. Observation of a Rapidly Pulsating Radio Source[J]. Nature, 1968, 217: 709-713.
[45] Kraushaar W L, Clark G W, Garmire G P, et al. High-energy cosmicgamma-ray observations from the OSO-3 satellite[J]. Astrophysical Journal, 1966, 177: 341-363.
[46] S. Singer. The Vela satellite Program for Detection of High-altitute Detonations[J]. Proceedings of IEEE, 1965, 53(12):1935-1951.
[47] Giacconi R, Kellogg E, Gorenstein P, Gursky H, Tananbaum H. Mission Overview[J]. Astronomy physic Journal, 1971,165:27.
[48] Allen, Jahoda, Whitlock. HEAO-1 and the A2 Experiment[J]. Legacy, 1994, 5:13-20.
[49] Petre R. ROSAT: The Roentgen Satellite. 2004, March[OL] http://heasarc.gsfc.nasa.gov/docs/rosat/rosat.html.
[50] Gruber D E, Blanco P R, Heindl W A, Pelling M R, et al. The high energy X-ray timing experiment on XTE[J]. Astronomy Astrophysics, 1996, 120:641.
[51] Weisskopf M C. The Chandra X-Ray Observatory: An overview[J]. Advances in Space Research, 2003,32(10): 2005-2011.
[52] Blanchard A, Vauclair S C, SadatNew R. XMM observations of high redshift X-ray clusters and cosmological interpretation[J]. Astronomy Reviews, 2005,49:69-73.
[53] Storey J W V, Ashley M C, Burton B. An Automated Astrophysical Observatory for Antarctica[J]. Publications of the Astronomical Society of Australia, 1996, 13(1):35-38.
[54] Kijak J, Gil J. Radio emission regions in pulsars. Monthly[J]. Notation Research of Astronomy Society, 1998, 299:855-861.
[55] Manchester R N, Hobbs G B, Teoh A, et al. The Australia Telescope National Facility Pulsar Catalogue[J]. The Astronomical Journal, 2008, 129:1993-2006.
[56]康连生.在乌鲁木齐天文站25m天线上进行的脉冲星观测[J].天文学进展, 1997, 15(2):169-172.
[57] Downs G S. Interplanetary Navigation Using Pulsating Radio Sources[R]. JPL-TR-32-1594, Technical Report.1974:10-15.
[58] Chester T J, Butman S A. Navigation using X-ray pulsars[R]. TDA Progress Report March and April 1981: 42-63.
[59] Wood K S. Navigation Studies Utilizing the NRL-801 Experiment and the ARGOS Satellite.Small Satellite Technology and Applications III[J]. SPIE Proceedings, 1993,1940:105-116.
[60] Hanson J. Principles of X-ray navigation[D]. Dept. Aeronautics andastronautics Stanford Univ Standford. 1996:1-50.
[61] Wood K S. The HEAO-1 X-ray Source Catalog[J] The Astrophysical Journal Supplement Series. 1984, 56:507-649.
[62] Sheikh S I. The Use of Variable Celestialx-Ray Sources For Spacecraft Navigation[D]. Doctor Thesis of Maryland University. 2005:221-229.
[63] Taylor J H, Weisberg J M. Further Experimental Tests of Relativistic Gravity Using the Binary Pulsar PSR 1913+16[J]. Astrophysical Journal. 1989, 345:434-450.
[64]仲崇霞.综合脉冲星时算法及脉冲星时应用[D].中国科学院学位论文, 2007:55-70.
[65]熊凯,魏春岭,刘良栋.基于脉冲星的空间飞行器自主导航技术研究[J].航天控制, 2007, 25(4):36-39.
[66]谢振华,许录平,倪广仁.基于最大似然的X射线脉冲星空间定位研究[J].宇航学报, 2007, 28(6):1605-1609.
[67]孙景荣,许录平,梁逸升,谢振华,倪广仁.中心差分Kalman滤波方法在X射线脉冲星导航中的应用[J].宇航学报, 2008, 29(11):1829-1833.
[68] Sheikh S I, Pines D J, Ray P S, et al. The Use of X-ray Pulsars for Spacecraft Navigation[J]. Advances in the Astronautical Sciences. 2005, 119:105-119.
[69] Sheikh S I, Pines D J, Ray P S, et al. Spacecraft navigation using X-ray Pulsars[J]. Journal of Guidance Control and Dynamics, 2006, 29(1):49-63.
[70] Sheikh S I, Ronald W, Hellings R, et al High-Order Pulsar Timing For Navigation[C]. Institute of Navigation 63rd Annual Meeting. 2007, Cambridge, Massachusetts:433-443.
[71] Ramkumar P S, Deshpande A A. Real-Time Signal Processor for Pulsar Studies[J].Astrophys and Astronomy, 2001, 22:321-342.
[72] Riba J, Sala J, Vazquez G. Conditional Maximum Likelihood Timing Recovery: Estimators and Bounds[J]. IEEE Transactions on Signal Processing, 2001, 49(4):835-851.
[73] Ray P S, Wood K S, Sheikh S I. Deep-Space Navigation Using Celestial X-ray Sources[C]. ION New Technology Meeting 2008, San Diego, CA, 2008:101-109.
[74] Golshan A R, Sheikh S I. On Pulse Phase Estimation and Tracking of Variable Celestial X-Ray Sources[C]. Institute of Navigation 63rd Annual Meeting, Cambridge, MA, 2007:413-423.
[75] Ashby N, Golshan A R. Minimum Uncertainties in Position and Velocity Determination using X-ray Photons from Millisecond Pulsars[C]. ION New Technology Meeting, San Diego, CA, 2008: 110-116.
[76] Ashby N, Howe D A. Relativity and timing in X-ray Pulsar navigation[C] Proceedings of the IEEE International Frequency Control Symposium and Exposition, 2006:767-770.
[77]朱振才,杨根庆,余金培等.微小卫星组网与编队技术的发展[J].上海航天, 2004, 6: 46-49.
[78]马涛,郝云彩,马骏,周胜利.编队飞行卫星的星间跟踪与测量技术综述[J].航天控制. 2005, 23(3):91-97.
[79] Bauer F, Bristow J, Folta D, Hartman K, et al. Satellite Formation Flying Using an Innovative Autonomous Control System Environment[C]. AIAA/AAS Astrodynamics Specialists Conference, 1997:657-666.
[80] Adams C, Robertson A, Zimmerman K, et al. Technologies for Spacecraft Formation Flying[C]. Proceedings of the ION GPS-96 Conference, 1996: 1321-1330.
[81] Long A, Kelbel D, Lee T, et al., Relative Navigation of Formation-Flying Satellites[C]. International Symposium on Formation Flying Missions & Technologies. Toulouse, France, 2002:1-8.
[82] Stadter P A, Heins R J, Chacos A A, et al. Enabling Distributed Spacecraft Systems with the Crosslink Transceiver[C]. AIAA Space 2001 Conference and Exposition, Albuquerque, 2001 August:28-30,.
[83] Purcell G, Kuang D, Lichten S, et al. Autonomous Formation Flyer (AFF) Sensor Technology Development[C]. 21st Annual AAS Guidance and Control Conference, Breckenridge, Colorado, 1998: 98-062.
[84] Kawano I, Wakabayashi Y. In-Orbit Demonstration Concept for the Space Platform in NASDA-Rendezvous Docking System[C]. IAF 1989, Malaga, 1989: 1-5.
[85] Tietz J C, Kelly J H. Development of an Autonomous Video Rendezvous and Docking System[R]. Martin Marietta Aerospace Report, Martin Marietta Aerospace: Denver Aerospace, Denver, CO, 1982: 1-15.
[86] Ho C C J, McClamroch N H. Automatica Spacecraft Docking Using Computer Vision Based Guidance and Control Techniques[J]. Journal of Guidance, Control, and Dynamics.1993, 16(2): 281-288.
[87] Goddard J S, Jatko W B, Ferrel R K, et al. Roubust Determination for Autonomous Docking[C]. 6th Topical Meeting on Robotics and Remote Systems, Monterey, CA, 1995:1-5.
[88]陈世平.空间相机设计与实验[M].北京:宇航出版社, 2003: 121-125.
[89] Clarke T A, Fryer J F, Wang X. The Principal Point and CCD Cameras[J]. Photogrammetric Record, 1998, 16(92): 293-312.
[90]闫野.利用星间测距实现卫星网自主定位[J].空间科学学报, 2000, 20(1):33-37.
[91] Guinot B. Pulsar timing[J]. Astronomy & Astrophysics, 1988, 256:192-370.
[92] Kapsi V M, Taylor J H, Ryba M F. High-Precision Timing of Millisecond Pulsars. III. Long-Term Monitoring of PSRs B1855+09 and B1937+21[J]. Astrophysics Journal, 428:713-728.
[93]倪广仁,杨廷高,赵当丽.毫秒脉冲星计时-脉冲星观测与研究[M].乌鲁木齐:新疆人民出版社. 2000:197-198.
[94] Emadazahea A A, Speyer J L, Hadaegh F Y. A Parametric Study of Relative Navigation using Pulsars[C]. Institute of Navigation 63rd Annual Meeting, 2007, Cambridge:454-459.
[95] Emadazahea A A, Speyer J L. A Study of Pulsar Signals Modeling and Time Delay Estimation for Relative Navigation of Spacecrafts[C]. ION New Technology Meeting, 2008, San Diego, CA:333-336.
[96]张承民,吴鑫基,贺龙松.脉冲星辐射机制[J].河北工学院学报. 1994, 23(4):77-81.
[97] Rakin M J. Toward an empirical theory of pulsar emission[J]. Astronomy Physics Journal. 1983, 274:359.
[98]吴鑫基,康连生,金声震等.四颗脉冲星在327MHZ观测结果[J].天体物理学报, 1997, (1):7-42.
[99] Morii M, Ktamoto S, Shibazaki N, et al. Suzaku Observation of the Anomalous X-Ray Pulsar[J]. Publications of The Astronomical Society of Japan, 2010,62(5): 1249-1259.
[100] Maron O, Kijak J, Kramer M, et al. Pulsar spectra of radio emission[J]. Astronomy and Astrophysics(Suppl), 2007,147:195-203.
[101] Charles P A, Seward F D. Exploring the X-ray Universe[M],Cambridge University Press, Cambridge UK, 1995:225-227.
[102]周概容.概率论与数理统计基础[M].上海:复旦大学出版社,2004:35-45.
[103] Hanson J, Sheikh S I, Graven P, et al. Noise analysis for X-ray navigation systems[C]. 2008 IEEE/ION Position, Location and Navigation Symposium, USA: IEEE, 2008, Monterey:704-713.
[104] White N E, Nagase F, Parmar A N. The Properties of X-ray Binaries, X-ray Binaries[M]. Cambridge University Press, Cambridge UK, 1995:1-57.
[105]苏哲,王勇,许录平,罗楠.一种新的脉冲星累积脉冲轮廓辨识算法[J].宇航学报, 2010, 31(6):1563-1568.
[106] Ramkumar P S, Deshpande A A. Real-Time Signal Processor for Pulsar Studies[J] J. Astrophys. Astr, 2001, 22:321–342.
[107] Sheikh S I, Ray P, Weiner K, et al. Relative Navigation of Spacecraft Utilizing Bright, Aperiodic Celestrial Sources[C]. ION 63rd Annual Meeting, 2007, Cambridge:201-208.
[108] Shark L K, Yu C. Denoising by optimal fuzzy thresholding in wavelet domain[J]. Electronics Letters, 2000, 36(6):581-582.
[109]杨建军,刘鸿福.基于经验模态分解的探地雷达信号去噪处理[J].计算机应用. 2008,9:29-30.
[110] Huang N E, Long S R, Zhen S. A new view of nonlinear water waves: the hilbert spectrum[J]. Annual Rev Fluid Mechanics, 1999, 31: 417-457.
[111] Huang N E,.The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J], Proceeding of Royal. Socociety, 1998, 454: 903-995.
[112] Boudraa A O, Cexus J C, Saidi Z.EMD-based signal noise reduction[C]. Proceeding of World Academy of Science, Engineering and Technology, 2004, 2: 122-125.
[113]孙伟峰,彭玉华,许建华.基于EMD的激光超声信号去噪方法[J].山东大学学报工学版, 2008, 38(5): 1-6.
[114]陈凤林.一种新的基于EMD模态相关的信号去噪方法[J].西华大学学报, 2009, 8(6): 20-24.
[115]刘劲,马杰,田金文,基于EMD的脉冲星信号消噪算法[J].计算机工程与应用, 2008, 44(20): 212-215.
[116]周建刚,陈印椿.统计物理中熵的定义[J].大连大学学报, 1992, 1(4): 59-63.
[117] Pincus S M. Approximate entropy as a measure of system complexity[C].Proceeding of National academy Sciety, 1991, 88: 2297-2301.
[118] Mallat S G. A theory for Multiresolution signal decomposition: The wavelet Represtation[J]. IEEE trasactions on Pattern analysis and machine intelligence. 1989, 11(7):674-693.
[119] Gardner W. Introduction to Random Processes with Aplications to Signals and Systems[M]. McGraw-Hill. 1990:221-222
[120]邓丽华.基于人工神经网络的手写体数字识别[J].三峡大学学报(自然科学学报), 2005, 27(3): 254-256.
[121] Gardner W A. Stationarizable random processes[J]. IEEE Trans. Information Theory, 1978, 24: 8-22.
[122]郑君里.信号与系统[M].高等教育出版社. 2000: 146-147.
[123] Gardner W A. Measurement of Spectral Correlation[J]. IEEE Trans.On Acoustic, Speech, and Signal Processing. 1986,34:1111-1123.
[124]梁应敞,王树勋.高阶累积量在谱估计中的应用[J].电子学报, 1992, 20(4): 93-96.
[125]田景文,高美娟.人工神经网络算法研究及应用[M].北京:北京理工大学出版社, 2006:26-27.
[126]李关防,惠俊英.基于经验模态分解的模态域MVDR方法研究[J].电子学报, 2009,37(5):942-947.
[127] Wood K S, Fritz G, Hertz P, et al. The USA X-ray Timing Experiment American Physical Society, April Meeting, April 20 - 23, 2002 Albuquerque Convention Center Albuquerque, New Mexico:1-10.
[128]张辉,钟建勇,袁家虎,刘恩海,电路噪声对星敏感器星点定位精度的影响[J].光学精密工程. 2006,10(4):1052-1056.
[129]刘一武,陈义庆,星敏感器测量模型及其在卫星姿态确定系统中的应用[J].宇航学报, 2003, 24(2)162-168.
[130] LIEBE C C. Accuracy performance of star trackers-a tutorial[J]. IEEE Trans. on Aerospace and Electronics Systems. 2002, 38 (2):587-599.
[131] Matsakis D N, Taylor J H, Eubanks T M. A Statistic for Describing Pulsar and Clock Stabilities[J]. Astronomy and Astrophysics, 1997, 326: 924-928.
[132]杨华波,张士峰,蔡洪.无陀螺仪惯性系统构型中安装误差分析与标定[J].中国惯性技术学报, 2007,15(1):39-46.
[133] Roy R, Kailath T. ESPRIT-Estimation of Signal Parameters via RotationalInvariance Techniques[J]. IEEE transactions on acoustics, speech, and signal processing. 1989(37):984-996.
[134] Rao B D, Hari K V S. Performance analysis of Esprit and TAM in determining the direction of estimation of arrival of plane waves in noise[J]. IEEE Transaction on Acoustic Speech Signal Processing, 1989(40):1990-1995.
[135] Kaveh M, Barabell A J. The statistical performance of MUSIC and the minimum norm algorithms in resolving plane waves in noise[J]. IEEE Transaction on Acoustic Speech Signal Processing, 1986(34): 331-340.
[136] Pines D. J. X-ray Source-based Navigation for Autonomous Position Determination[R]. Program. DARPA/ TTO , USA , 2004,571:218-4339.
[137] Nrgaard M. Advances in Derivative free State Estimation for Nonlinear Systems[D]. Technical University of Denmark , 2000, 49:1-33. .