用户名: 密码: 验证码:
光纤陀螺的动态性能研究
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
光纤陀螺广泛应用于捷联惯性导航系统中,它的工作性能在很大程度上决定着整个惯性系统的精度。目前国内外对处于静止或匀速运动状态下的光纤陀螺性能即光纤陀螺的静态性能进行了大量的研究报道,而对处于角加速运动状态的光纤陀螺性能即光纤陀螺的动态性能则研究的较少。本文系统研究了光纤陀螺动态条件下的误差理论、测试方法、测试结果的分析方法和性能的改进方法。
     捷联系统直接与运动载体固连,在实际运动中经常处于角加速运动状态。因此,角加速运动下光纤陀螺性能的优劣决定着捷联惯导系统的导航精度。在分析光纤陀螺系统模型和角加速运动响应特性的基础上,建立了光纤陀螺动态条件下的误差模型。详细剖析了光纤陀螺的稳定性条件,结构参数、信号处理周期以及外界环境对光纤陀螺动态性能的影响。从理论上阐述了光源平均波长和反馈通道增益的变化作用于结构参数的机理,台阶高度信号和输出信号的滤波作用于信号处理周期的机理。仿真结果证明所建立的光纤陀螺动态条件下的误差模型准确可靠。
     为了对光纤陀螺的动态性能进行合理评价,采用三轴惯导测试转台来模拟光纤陀螺的角加速运动状态,给光纤陀螺施加瞬时变化的角速度输入,对其进行动态测试。对测试原理和测试步骤进行详细阐述。采用位置差商法、分周期离散理论曲线法和公式变换法确定动态测试中的基准值。分析结果表明分周期离散理论曲线法和公式变换法较适合。
     三轴转台的精度是制约光纤陀螺测试结果精确性的瓶颈因素。根据转台在摇摆状态下输出信号的特点,采用皮萨伦科谱分解法对其进行辨识。由此得到转台信号的幅度失真、频率失真以及夹杂在其中的分量谐波的幅度和频率。并通过比较辨识前后转台误差的标准差,证明了辨识结果的可靠性。同时,分析了不同转台框在相同摇摆条件下的失真规律和同一转台框在不同摇摆条件下的失真规律。实验结果表明,皮萨伦科谱分解法应用于转台正弦信号的失真辨识中是非常适用的。
     为了避免转台摇摆运动轨迹中夹杂的噪声传递到动态测试的基准信号中,结合小波多分辨分析和空间局部化的性质,选用db5小波对转台的运动轨迹进行降噪。结果表明,小波滤波法的噪声滤除效果理想,提高了对光纤陀螺动态测试结果评定的准确性。
     采用时延估计理论分析和补偿动态测试中基准信号与实际信号之间的时间延迟。利用测试中信号与噪声、噪声与噪声互不相关的特点,对两个信号进行相关运算,估计出两信号之间的时间延迟,并进一步对其补偿。结果表明,时间延迟对测试结果有较大影响,经过补偿后的动态误差更符合实际情况。
     为了更好的分析光纤陀螺的动态性能,采用动态Allan方差法对光纤陀螺的动态误差进行分析。根据动态Allan方差法中窗函数的原理,讨论了不同窗口长度对动态误差分析结果的影响。并且,提供了单一摇摆运动和两种复合摇摆运动的分析结果。从分析图中方差的起伏变化可以看出,动态Allan方差法可以准确地反映动态误差里的突变和周期性变化等非稳定性因素,能够清晰地辨识出隐藏在动态误差里的不同摇摆状态。由理论分析和实验结果可知,动态Allan方差法对光纤陀螺的动态性能分析是非常适用的。
     动态Allan方差法是一种分析非平稳性信号的有效工具,但在辨识噪声时存在功率泄漏和定量表示单一的缺陷。为此,提出窗函数组合法和噪声量值的二维表示法对其改进,并将其用于分析和定量描述光纤陀螺动态误差中的各种噪声项。窗函数组合法在光纤陀螺动态误差分解的基础上采用矩形窗和汉宁窗对其中的低频噪声和高频噪声分别进行分析。噪声量值的二维表示法根据动态Allan方差法原理得到噪声量值随采样点数目增加的变化规律。实验结果表明窗函数组合法可以满足不同频段噪声的辨识要求,减小功率泄漏;噪声量值的二维表示法可以准确地反映出动态误差中噪声项的变化特征。
     为了改善光纤陀螺的动态性能,将普通PID控制器的设计思想应用到光纤陀螺的动态误差控制器中,并进一步基于光纤陀螺动态条件下的误差特性设计出一种新型的动态误差控制器结构。前者主要通过普通PID控制器的设计思想与光纤陀螺的控制方式相结合,即基于光纤陀螺内部控制方式实现。而后者将微分环节设置在输出信号之前,使输出信号和反馈信号同时具有提前预测功能,并在微分环节后面加一个低通滤波器以抑制微分环节带来的高频干扰。这一新控制器结构既可以使控制量减小,各个时刻的控制误差不累积,还可以使输出跟踪输入,反映输入的变化。两种动态误差控制器均通过在光纤陀螺数字信号处理芯片FPGA的各模块中编写VHDL语言实现。实验结果表明两种动态误差控制器都可以明显地改善光纤陀螺的动态性能,且基于光纤陀螺动态条件下误差特性的动态误差控制器具有更优的控制效果。
Fiber optic gyroscope (FOG) is widely applied in strapdown inertial navigation system (SINS), and its performance largely determines the precision of SINS. At home and abroad, lots of researches on the performance of FOG are reported in the state of rest or uniform motion, i.e., the static properties of FOG, however, the study on the performance of FOG in the state of angular acceleration motion is less, i.e., the dynamic performance of FOG. In this paper, study the error theory of FOG under the dynamic conditions, test methods, analysis of test results and the improvement methods of performance systematically.
     SINS fix directly with the carrier, which are always under angular acceleration state in the actual movement. Therefore, the performance of FOG under angular acceleration state determines the accuracy of SINS.The error model of FOG under the dynamic condition is established, basing on the analysis of FOG system model and response characteristics under angular acceleration motion. The influence of FOG stability conditions, structural parameters, signal processing cycle as well as the external environment on the dynamic performance of FOG are discussed. In theory, the affect mechanism of light average wavelength and feedback channel gain on the structural parameters are analyzed; the influence mechanism of the step height signal and the output signal filtering on the signal processing cycle are discussed. Simulation results indicate that the error model of FOG under the dynamic conditions is accurate and reliable.
     To evaluate the dynamic performance of FOG reasonably, the three-axis inertial test turntable is chosen to test the dynamic performance of FOG. The input angular velocity signal of FOG changes according to sine law. The test principle and procedures are presented. In this paper, three methods are presented to determine the reference value in dynamic test, which are location divided difference, separated period discretization theory curve and transform formula method. Separated period discretization theory curve and transform formula method are suitable among these.
     The accuracy of three-axis turntable is one of the key factors that constrain the precision of FOG test results. Based on the characteristics of output signals under the sway states, use of the Pisarenko spectrum decomposition method is preferred for identifying the output signals of turntable, which include the amplitude distortion, frequency distortion and the component harmonics. In this paper, the standard deviations of turntable errors are compared and analyzed to identify the credibility. Moreover, the distortion laws are analyzed under two conditions:different turntable frames the same sway conditions and identical turntable frame the different sway conditions. The results indicate that the Pisarenko spectrum decomposition method is applicable to identify the sinusoidal signal distortion of turntable.
     Based on the wavelet natures of multiresolution analysis and spatial localization, db5wavelet is choosed to fiter the noise of turntable trajectory for avoiding it to pass in the reference signal of dynamic test. The results indicate that the filtering effect of wavelet is satisfactory and it improves the accuracy of the dynamic test results of FOG.
     The time delay between the reference signal and the actual signal in dynamic test is analyzed and compensated using time delay estimation theory. Related operation is done to estimate and further compensate the time delay between the two signals, based on signals and noises, noises and noises are irrelevant in the test. The results indicate that time delay has a greater impact on test results and the dynamic error after compensation is in accordance with the actual situation.
     In order to study the dynamic performance of FOG better, it is proposed that the dynamic error which is obtained by test of FOG is analyzed by dynamic Allan variance. According to the principle of window function of dynamic Allan variance method, the analysis results of dynamic error are discussed under the different window length conditions. Furthermore, a kind of single sway movement and two kinds of composite sway movement are analyzed by dynamic Allan variance method and their results are provided. There is fluctuating variation of variance in analysis figures, by which the various non-stationary factors in the dynamic error such as mutation and periodic variation are accurately reflected and the different sway states hidded in the dynamic errors are clearly identified. Both the theoretical analysis and experimental results indicate that the dynamic Allan variance method is very applicable to analyze the dynamic performance of FOG.
     The dynamic Allan variance is an effective method for analyzing non-stationary signal. However, it has defects in noise identification:power leakage and single quantification. Therefore, window function combination method is introduced for their improvements as well as two-dimensional expression of noise value. They are used for analysis and quantitative measurement of various noise terms in the FOG dynamic error. Based on the dynamic error resolution of FOG, rectangular window is applied to analyze low&intermediate frequency noise, while hanning window does high-frequency noise. According to the principle of DAVAR, the noise variation laws with the numbers of sampling point are obtained, namely, two-dimensional expression of noise value. The experimental results indicate that window function combination method satisfies the identification requirements of noise in different frequency ranges and reduces power leakage; moreover, the change characteristics of every noise item in the dynamic error are accurately reflected by the two-dimensional expression of noise value.
     The design idea of normal PID controller is applied in the dynamic error controller of FOG to improve its dynamic performance; moreover, a novel dynamic controller structure is designed basing on the error characteristics of FOG under dynamic state. The former is implemented by the combination of design idea of normal PID with the control idea of FOG, i.e. implemented by the inner control model of FOG. For the later (the novel one), the differential link is set before the output signal, which make the output signal and feedback signal to predict in advance; meanwhile, a low-pass filter is set after the differential link to suppress the high frequency interference brought by the differential link. The novel control structure can not only decrease the control amount and avoid the calculation of control error, but also allows the output to track the input and reflects the input change. Both the controllers are realized through writing VHDL language in the digital signal processing chip FPGA of FOG. The test results indicate that both the dynamic error controllers can significantly improve the FOG dynamic performance, furthermore, the novel dynamic error controller, i.e. the dynamic error controller basing on the error characteristic of FOG under dynamic condition, has better error control performance.
引文
[1]张桂才.光纤陀螺原理与技术.北京:国防工业出版社.2008
    [2]郑梓祯,刘德耀,蔡迎波,等.船用惯性导航系统海上试验.北京:国防工业出版社.2006
    [3]李绪友,张娜.基于动态Allan方差的光纤陀螺动态特性分析.哈尔滨工程大学学报.2011,32(2):183-187页
    [4]李茂春,姚晓天,江俊峰,等.光纤陀螺全方位性能自动评价系统.红外与激光工程.2006,35(S5):238-242页
    [5]韩剑辉,陈桂红,杨功流.光纤陀螺测试系统设计.航空精密制造技术.2003,39(3):37-39页
    [6]Barhour N, Schmidt G. Inertial Sensor Technology Trends. IEEE Sensors Journal.2001, 1(4):332-339P
    [7]Curey R K, Ash M E, Thielman L O, et al. Proposed IEEE Inertial Systems Terminology Standard and Other Inertial Sensor Standards. IEEE Position Location and Navigation Symposium. Montery. CA:IEEE,2004:83-90P
    [8]许江宁.陀螺原理及应用.北京:国防工业出版社.2009
    [9]Ohno A, Kurokawa A, Kumagai T, et al. Applications and Technical Progress of Fiber Optic Gyros in Japan. Optical Fiber Sensors/Optical Society of America.2006:MA4P
    [10]Emge S, Monte T, Brunner J, et al. Advances in Open-Loop FOG Sensors. Optical Fiber Sensors/Optical Society of America.2006:MC3P
    [11]Culshaw B. Optical Fiber Sensor Technologies:Opportunities and-Perhaps-Pitfalls. Journal of Lightwave Technology.2004,22(1):39-50P
    [12]Grewal M, Andrews A. How Good Is Your Gyro? IEEE Control Systems.2010,30(1): 12-14P
    [13]Lefevre H C. Ultimate-Performance Fiber-Optic Gyroscope:A Reality. The 16th Opto-Electronics and Communications Conference.2011:75-78P
    [14]Edu IR, Obreja R, Grigorie T L. Current Technologies and Trends in the Development of Gyros Used in Navigation Applications-A Review. Recent Researches in Communications and IT.2011:63-68P
    [15]Peshekhonov V G Gyroscopic Navigation Systems:Current Status and Prospects. Gyroscopy and Navigation.2011,2(3):111-118P
    [16]Erler T. The Fiber Optic Gyroscope -A Sagnac Interferometer for Inertial Sensor Applications. Contributing International Traveling Summer School.2007:1-35P
    [17]http://honeywell.com/Pages/Home.aspx
    [18]Friebele E J, Askins C G, Miller G A, et al. Optical Fiber Sensors for Spacecraft: Applications and Challenges. Photonics for Space Environments IX.2004:120-131P
    [19]Sanders S J, Strandjord L K, Mead D. Fiber Optic Gyro Technology Trends-A Honeywell Perspective. Optical Fiber Sensors Conference Technical Digest.2002:5-8P
    [20]徐宇新.光纤陀螺技术趋势-Honeywell公司展望.导航控制.2003,2(4):30-32页
    [21]Divakaruni S P, Sanders S J. Fiber Optic Gyros-A Compelling Choice for High Precision Applications. Optical Fiber Sensors/Optical Society of America.2006:MC2P
    [22]Tanaka R, Kurokawa A, Sato Y. Signal Processing for FOG. Fiber Optic and Laser Sensors XII.1994:192-202P
    [23]Hayakawa Y, Kurokawa A. Outlook of Fiber Optic Gyroscope. International Conference on Optical Fibre Sensors.1991:353-358P
    [24]Byoungho L. Review of the Present Status of Optical Fiber Sensors. Optical Fiber Technology.2003,9(2):57-79P
    [25]Patterson R A, Goldner E L, Cordova A, et al. Test Results Over Extended Environments for Litton's Inertial Navigation Grade Interferometric Fiber Optic Gyro. Position Location and Navigation Symposium.1994:176-181P
    [26]Volk C, Lincoln J, Tazartes D. Northrop Grumman's Family of Fiber-Optic Based Inertial Navigation Systems. Position Location and Navigation Symposium.2006: 382-389P
    [27]Tazartes D A. Inertial Navigation:From Gimbaled Platforms to Strapdown Sensors. Transactions on Aerospace and Electronic Systems.2011,47(3):2292-2298P
    [28]Nayak J. Fiber-Optic Gyroscopes:From Design to Production. Optical Society of America.2011,50(25):E152-E161P
    [29]Culshaw B, Kersey A. Fiber-Optic Sensing:A Historical Perspective. Journal of Lightwave Technology.2008,26(9):1064-1078P
    [30]Culshaw B. The Optical Fibre Sagnac Interferometer:An Overview of Its Principles and Applications. Measurement Science and Technology.2006,17(1):R1-R16P
    [31]Barbour N, Schmidt G. Inertial Sensor Technology Trends. IEEE Sensors Journal,2001, 1(4):332-339P
    [32]http://www.northropgrumman.litef.de
    [33]Pavlath G A. Fiber Optic Gyros:The Vision Realized. Optical Fiber Sensors/Optical Society of America.2006:MA3P
    [34]Lobanov V S, Tarasenko N V, Shulga D N. Fiber-Optic Gyros & Quartz Accelerometers for Motion Control. Aerospace and Electronic Systems Magazine.2007, 22(4):23-29P
    [35]Culshaw B. Phase Measurement and Interferometry in Fibre Optic Sensor Systems. American Institute of Physics.2010,1236(24):24-28P
    [36]Barbour N M. Inertial Navigation Sensors. RTO-EN-SET-116.2011:2-1-2-28P
    [37]Bogue R. Fibre Optic Sensors:A Review of Today's Applications. Sensor Review.2011, 31(4):304-309P
    [38]伊小素译.从研发样机到以惯导级光纤陀螺为基础的惯性导航系统:Photonetics-Ixsea公司的经验.导航与控制译文集.2004,4(1):1-4页
    [39]Gaiffe T. From R&D Brassboards to Navigation Grade FOG-Based INS:The Experience of Photoneticsllxsea IXSEA. Optical Fiber Sensors Conference Technical Digest.2002:1-4P
    [40]Gaiffe T. From High Technology to Solutions:The Experience of IXSEA. Web-Based Article. http://www.ixsea.com/pdf/2006-oceans-singapore.pdf
    [41]http://www.ixsea.com/en/
    [42]Rzhavin Y I. Fiber-Optic Sensors:Technical and Market Trends. Measurement Techniques.2003,46(10):949-953P
    [43]Hotate K. Fiber Sensor Technology Today. Japanese Journal of Applied Physics.2006, 45(8B):6616-6625P
    [44]Ruffin P B. Progress in the Development of Gyroscopes for Use in Tactical Weapon Systems. Proceedings of SPIE.2000:2-12P
    [45]Kumar K K, Madhav V G. Review on Developments in Fiber Optical Sensors and Applications. Proceedings of SPIE.2010:76770R-1-76770R-12P
    [46]http://www.cannews.com.cn/zghkb/html/2011-05/19/content_18973.htm
    [47]http://news.cntv.cn/military/20110412/103738.shtml
    [48]陈北鸥,孙文胜,张桂宏,等.捷联组合(设备无定向)六位置测试标定.导弹与航天运载技术.2001,251(3):23-27页
    [49]刘百奇,房建成.光纤陀螺IMU的六位置旋转现场标定新方法.光电工程.2008,35(1):60-65页
    [50]曹华,刘建业,祝燕华,等.光纤陀螺组件误差标定ARLS算法.光电工程.2008,35(6):48-53页
    [51]李建利,房建成,盛蔚,等.微小型捷联惯性测量单元标定及补偿方法.宇航学报.2008,29(3):947-951页
    [52]严恭敏,秦永元.激光捷联惯组的双轴位置转台标定仿真.中国惯性技术学报. 2007,15(1):123-127页
    [53]熊智,刘建业,林雪原,等.激光陀螺捷联惯性导航系统中惯性器件误差补偿技术.上海交通大学学报.2003,37(11):1795-1799页
    [54]Rogers R M. Applied Mathematics in Integrated Navigation Systems. American Institute of Aeronautics and Astronautics, Inc.2007
    [55]林玉荣,邓正隆.激光陀螺捷惯导系统中惯性器件误差的系统级标定.哈尔滨工业大学学报.2001,33(1):112-115页
    [56]周章华,邱宏波,李延,等.用低精度双轴转台对捷联惯导进行系统级标定的方法.中国惯性技术学报.2010,18(4):503-507页
    [57]吴赛成,秦石乔,王省书,等.激光陀螺惯性测量单位系统级标定方法.中国惯性技术学报.2011,19(2):185-189页
    [58]白亮,秦永元,吴枫.捷联惯性组合在舰标定技术研究.西北工业大学学报.2010,28(3):369-374页
    [59]牟玉涛,周振威,方海涛.SINS外场系统级标定方法的优化——最佳六位置.北京航空航天大学学报.2011,37(7):855-860页
    [60]戚红向,王世会,司文杰,等.一种新型的光学陀螺捷联惯组系统级标定方法.航天控制.2011,29(1):7-9页
    [61]张天光,王秀萍,王丽霞,等译.捷联惯性导航技术(第二版).北京:国防工业出版社.2007
    [62]王妍,张春熹.数字闭环光纤陀螺动态特性测试研究.北京航空航天大学学报.2004,30(9):818-821页
    [63]张维叙.光纤陀螺及其应用.北京:国防工业出版社.2008
    [64]孟照魁,崔佳涛,章博,等.高精度光纤陀螺温度实验研究.宇航学报.2007,28(3):580-583页
    [65]李金涛,房建成.高精度光纤IMU的磁屏蔽方法及实验研究.航空学报.2011,32(6):1-10页
    [66]王夏霄,宋凝芳,张春熹,等.光纤陀螺磁敏感性的试验研究.北京航空航天大学学报.2005,31(10):1117-1120页
    [67]王硕邦,王巍,魏丽萍.闭环保偏光纤陀螺力学环境适应性研究.惯导与仪表.2001,(4):40-47页
    [68]李春枝,陈颖,田光明,等.基于光纤陀螺技术的三轴振动转角测试.传感器与微系统.2010,29(8):123-125页
    [69]Sanghadasa M, Ashley P R, Lindsay G A, et al. Backscatter Compensation in IFOG Based Inertial Measurement Units with Polymer Phase Modulators. Journal of Lightwave Technology.2009,27(6):806-813P
    [70]Seo M S, Kim T J, Yun S C, et al. Polarisation-Scrambled Er-Doped Superfluorescent Fibre Source with Improved Mean-Wavelength Stability. Electronics Letters.2006, 42(11):621-623P
    [71]Korkishko Y N, Fedorov V A, Kostritskii S M, et al. LiNbO3 Integrated Optical Chip for Fiber Optical Gyroscope Fabricated by High Temperature Proton Exchange. Laser and Fiber-Optical Networks Modeling.2003:275-277P
    [72]Ip E M, Kahn J M. Fiber Impairment Compensation Using Coherent Detection and Digital Signal Processing. Journal of Lightwave Technology.2010,28(4):502-519P
    [73]刘颖,李言,姬忠校,等.光纤陀螺用Y波导半波电压稳定性的研究.仪器仪表学报.2010,31(2):449-453页
    [74]宫兆涛,舒晓武,牟旭东,等.光纤陀螺用SLD光源全数字控制系统.仪器仪表学报.2005,26(7):689-691页
    [75]赵晶晶,马静,李安琪,等.SLD光源老化筛选监测系统的设计与实现.电子测量与仪器学报.2009,23(2):112-116页
    [76]李广华,刘军,殷建玲.高适应SLD光源控制方法研究.电子测量技术.2010,33(6):23-26页
    [77]徐宏杰,刘海锋,张春熹,等.基于光纤Sagnac干涉仪的高精度宽谱光源平均波长测量技术.仪器仪表学报.2010,31(1):127-131页
    [78]Bian X Q, Wang Y H, Zhang X Y, et al. Research on Simulation of Course Control for Large Ship with Wave Disturbances in Different Sea Conditions. Oceans 2009 MTS/IEEE Biloxi,2009:1-5P
    [79]Danilytchev M V, Kutuza B G. Characteristics of Emission and Scattering of Rough Sea Surface at Long Millimeter Waves. MSMW'04 Symposium Proceeding.2004: 199-201P
    [80]Seidel C, Trommer G F. Modeling of Bias Errors in Fibre-Optic Gyroscopes with Advanced Simulation Tool. Electronics Letters.2004,40(3):166-167P
    [81]Han J L, Ge S M, Shen Y, et al. Modeling and Simulation of Digital Closed-Loop Fiber Optic Gyroscope. Proceedings of the 6th World Congress on Intelligent Control and Automation.2006:1659-1663P
    [82]GJB 150.23A-2009.军用装备实验室环境试验方法——第23部分:倾斜和摇摆试验.2009
    [83]李绪友.高精度数字闭环光纤陀螺的研究.哈尔滨:哈尔滨工程大学博士学位论文.2002
    [84]余慧.光纤陀螺动态特性的测试与分析.哈尔滨:哈尔滨工程大学硕士学位论文.2009
    [85]何绪龙,冯伟利,郑应强,等.角位置定位误差检测及其补偿技术.宇航计测技术.2008,28(2):11-13页
    [86]王国民.一种测量转台位置精度的方法及误差分析.机械传动.2008,32(4):54-56页
    [87]邓志红,刘亚辰,王清哲,等.转台角位置基准误差对激光捷联惯导标定的影响分析.中国惯性技术学报.2009,17(4):498-504页
    [88]Liu Z G, Wang J Z, Zhao J B. Friction Compensation Using Dual Observer for 3-Axis Turntable Servo System. Proceedings of the IEEE International Conference on Automation and Logistics.2009:658-663P
    [89]刘钦彦,李勇,周兆英,等.计算机控制小型三轴飞行模拟转台.仪器仪表学报.2001,22(3):171-172页
    [90]何丕雁.现代测试技术中的采样非均匀性问题理论研究与分析.成都:电子科技大学硕士学位论文.2001
    [91]梁志国,孟晓风.采样抖动研究进展述评.测试技术学报.2009,23(3):253-259页
    [92]Hideaki S. Statistical Analysis of Pisarenko's Method for Sinusoidal Frequency Estimation. IEEE Signal Processing Society.1984,32(1):95-101P
    [93]王宏禹,邱天爽,陈喆.非平稳随机信号分析与处理(第二版).北京:国防工业出版社.2008
    [94]Piet M T, Broersen S W. Finite Sample Properties of ARMA Order Selection. IEEE Instrumentation and Measurement Society.2004,53(3):645-651P
    [95]周毅.时间序列模型辨识方法及其仿真研究.无锡:江南大学硕士学位论文.2008
    [96]Fattah S A, Zhu W P, Ahmad M O. An Algorithm for ARMA Model Parameter Estimation from Noisy Observations. IEEE International Symposium on Circuits and Systems.2008:3202-3205P
    [97]何燕春,行鸿彦.时延估计在超声血流速度测量中的应用.中国组织工程研究与临床康复.2009,13(13):2515-2518页
    [98]苗锦,刘志强,张跟鹏.基于互相关的时延估计方法及其精度分析.舰船此案自工程.2008,6(28):98-100页
    [99]秦一帆.干涉式光纤陀螺的噪声分析及实验研究.天津:天津大学硕士学位论文.2007
    [100]李志宏.基于光纤陀螺方位测量方法研究.长春:长春理工大学硕士学位论文.2008
    [101]Galleani L,.Tavella P. The Characterization of Clock Behavior with the Dynamic Allan Variance. Proc. IEEE FCS-EFTF.2003:239-244P
    [102]Galleani L, Tavella P. Tracking Nonstationarities in Clock Noises Using the Dynamic Allan Variance. Proc. Joint FCS-PTTI Meeting.2005:392-396P
    [103]Galleani L, Tavella P. Interpretation of the Dynamic Allan Variance of Nonstationary Clock Data. Proc. IEEE FCS-EFTF.2007:992-997P
    [104]Galleani L, Tavella P. The Dynamic Allan Variance. IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control.2009,56(3); 450-464P
    [105]Galleani L, Tavella P. Fast Computation of the Dynamic Allan Variance. Proc. IEEE FCS-EFTF.2009:685-687P
    [106]Galleani L. The Dynamic Allan Variance II:A Fast Computational Algorithm. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control.2010,57(1): 182-188P
    [107]Sesia I, Galleani L, Tavella P. Application of the Dynamic Allan Variance for the Characterization of Space Clock Behavior. IEEE Transactions on Aerospace and Electronic Systems.2011,47(2):884-895P
    [108]李迪,孙尧,李绪友,等.船用光纤陀螺随机漂移分析与研究.中国航海.2005,62(1):35-37页
    [109]李颖,陈兴林,宋申民.光纤陀螺漂移误差动态Allan方差分析.光电子·激光.2008,19(2):183-186页
    [110]魏国,龙兴武.基于动态Allan方差的机抖激光陀螺随机误差研究.中国激光.2010,37(12):2975-2979页
    [111]韩军良.光纤陀螺的误差分析、建模及滤波研究.哈尔滨:哈尔滨工业大学博士学位论文.2008
    [112]党淑雯.光纤陀螺的信号分析及滤波技术研究.上海:上海交通大学博士学位论文.2010
    [113]李银伢.满意PID控制器设计理论.南京:南京理工大学博士学位论文.2006
    [114]朱业鹏.PID控制器的参数整定及其稳定域研究.南京:南京理工大学硕士学位论文.2007

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700