GPS和捷联惯导组合导航新方法及系统误差补偿方案研究
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摘要
传统的GPS和捷联惯导组合导航技术中存在着一个基本矛盾,即高精度组合系统的可靠性和实时性较差,而实时性和可靠性好的组合系统精度较低。比如,GPS RTK定位和捷联惯导的组合导航系统精度很高,但是随着定位位置与GPS基站之间距离的增加,系统的可靠性逐渐下降,且由于需要进行整周模糊度解算而实时性较差,因此不能应用于无区域限制的实时导航中;伪距和捷联惯导的组合导航系统具有很好的可靠性和实时性,适于导航应用,但精度较差。本文的研究目的之一就是通过GPS信息的合理应用以及新的组合技术来提高GPS和捷联惯导组合导航系统的整体性能。此外,惯性传感器的随机误差和捷联惯导的初始对准误差是组合导航系统的关键误差,本文的另一个研究目的就是通过新技术实现GPS辅助的这两种误差的最优补偿。围绕上述两个研究目的,本文主要完成了以下研究工作:
1.以GPS载波相位观测量为基础,研究了载波相位时间差分观测量,并推导了其观测方程;探讨了载波相位时间差分观测量在导航与组合导航中的应用。误差分析表明载波相位时间差分兼具伪距和载波相位的优点,是一个非模糊的高精度的GPS观测量;导航试验研究表明由载波相位时间差分可以解算出毫米/秒量级的高精度速度;组合导航试验研究表明载波相位时间差分和捷联惯导的组合导航系统具有很高的短时精度,但是系统的位置误差存在着缓慢的积累效应。
2.针对含有两种观测量且两种观测量之间测量噪声差异较大的最优估计系统,提出了使用双速卡尔曼滤波器把低噪声的观测量以高频的形式、把高噪声的观测量以低频的形式融入到最优估计系统中。通过分析双速卡尔曼滤波的误差协方差传播过程,发现双速卡尔曼滤波技术可以有效地隔离来自于不同观测量的测量噪声,另外双速卡尔曼滤波技术还可用于实现非同步观测信息的融合以及提高运算效率。
3.以双速卡尔曼滤波器为数学工具,设计了基于载波相位时间差分、伪距和捷联惯导的紧组合导航系统。针对系统的实现问题,推导了双速卡尔曼滤波的系统方程(基于惯导误差方程)、高速卡尔曼滤波的测量方程(基于载波相位时间差分的观测方程)、以及低速卡尔曼滤波的测量方程(基于伪距的观测方程)。试验研究表明,提出的组合导航技术与经典组合导航技术相比,使导航的位置精度获得了改善,且明显改善了系统的速度精度、姿态精度和滑行性能。
4.有色噪声对惯性传感器的性能有重要影响,为了在组合导航过程中在线补偿有色噪声引起的惯性传感器误差,需要对有色噪声进行建模。首先,针对单独的有色噪声,提出了从其功率谱密度函数推导其随机微分方程模型的一般步骤,并推导了几种常见有色噪声的随机微分方程模型。然后,针对多种有色噪声并存的情况,提出并证明了随机微分方程的等价性定理,此定理指出在宽平稳的意义下,多个随机微分方程可以等价地使用单一随机微分方程描述,并给出了此等价随机微分方程系数参数的确定方法。此定理解决了多种有色噪声共存时的等价建模问题,为有色噪声的在线补偿奠定了数学基础。
5.设计了GPS辅助的惯性传感器随机误差在线补偿方案。在此补偿方案中,白噪声、量化噪声和有色噪声分别按照下列方法进行处理:(1)白噪声用以确定系统的过程噪声协方差矩阵;(2)通过修改惯导的误差方程,把量化噪声转化为等价的白噪声,并用以扩展系统的过程噪声协方差矩阵;(3)由等价性定理导出的多种有色噪声的等价随机微分方程模型用以扩展组合导航的系统方程。试验测试结果表明此在线补偿方案有效地补偿了惯性传感器的随机误差,明显改善了纯惯导系统的运行性能。
6.为了减小大航向误差条件下捷联惯导动基座初始对准的模型误差,提出并实现了一种大航向误差条件下的捷联惯导动基座初始对准方案。针对此对准方案的实现问题,推导了相应的粗对准误差方程和测量方程以及精对准误差方程和测量方程。试验结果验证了所提出方案的优越性,通过与经典方案的试验结果相对比,发现所提出的初始对准方案明显改善了大航向误差条件下初始对准的精度和速度。
7.为了减小捷联惯导动基座初始对准的观测量误差,设计了高精度的载波相位时间差分辅助的捷联惯导动基座初始对准方案。试验结果表明,载波相位时间差分辅助的捷联惯导动基座初始对准精度已经接近GPS PPK(Post-Processing Kinematic)定位辅助的捷联惯导动基座初始对准精度。
For the conventional GPS/SINS integration techniques, there exists a basic dilemma, namely, the high precision integrated systems generally have poor reliability and real-time performances, and on the other hand, the systems with good reliability and real-time performances generally have low precision. For example, the integration of GPS RTK/SINS can be very precise, however, its reliability will become poor with the increasing of the distance from the GPS base station and its real-time performances are not good because of the necessity for the resolution of the integer ambiguities. So, generally, GPS RTK/SINS integrated system can not be used in real-time or wide-area navigation applications. As an opposite example, the integration of GPS pseudorange/SINS is suitable for navigation applications because of its good reliability and real-time performances, however, its precision is low. So, the first goal of this research is to improve the overall performances of GPS/SINS integrated system by rearrangement of the GPS information and by using new integration techniques. Besides, the stochastic errors of the inertial sensors and the initial alignment error of the SINS are two kinds of the most crucial errors, so the second goal of this research is to develop some techniques to optimally compensate both of them with the aiding of GPS. To accomplish these two goals, the following work has been finished in this research:
1. A new GPS observable, incremental carrier-phase observable, has been derived based on GPS carrier-phase, and the corresponding observation equation for the incremental carrier-phase has also been derived. Furthermore, the applications of the incremental carrier-phase in navigation and integrated navigation have been discussed. Error analysis has shown that the incremental carrier-phase is an unambiguous and precise observable with the advantages of both pseudorange and carrier-phase. Navigation experiments have revealed that the mm/s level accuracy has been achieved in computing velocity from the incremental carrier-phase. Integrated navigation experiments have demonstrated that the integration of the incremental carrier-phase and SINS can obtain very high short-term navigation accuracy, while the position error will slowly accumulate with time.
2. For the optimal estimation systems with two kinds of observables whose measurement noises are quite different with each other, a novel optimal estimation technique, dual-rate Kalman Filtering technique, has been proposed, and the relevant theoretical analysis has been done. The dual-rate Kalman Filter fuses the low-noise observable with high rate, and the high-noise observable with low rate into the optimal estimation systems. By analyzing the propagation of the error covariance, it has been found that the proposed dual-rate Kalman Filtering can effectively isolate the noises from different error sources, and at the same time, the dual-rate Kalman Filtering can be used to fuse the asynchronous observations from different sensors and can also improve the computation efficiency.
3. By using the dual-rate Kalman Filter as the integration tool, a novel tightly coupled integration system based on the incremental carrier-phase, the pseudorang, and the SINS has been designed. To implement the above integrated system, the system equation for the dual-rate Kalman Filtering has been derived based on the SINS error equation, and the measurement equation for the high-rate Kalman Filtering as well as the measurement equation for the low-rate Kalman Filtering has also been derived based on the incremental carrier-phase and the pseudorange, respectively. Experimental tests have demonstrated that, compared with the conventional integration techniques, the proposed novel integration technique has improved the position accuracy, and dramatically improved the velocity and attitude accuracy as well as the coasting performance.
4. Colored noises have important influences to the performances of inertial sensors, and to compenstate the errors of the inertial sensors introduced by the colored noises in GPS/SINS integration, it is necessary to model the colored noises. Firstly, for a single colored noise, a general procedure has been proposed to derive its stochastic differential equation model from its power spectral density (PSD) function, and the stochastic differential equations of several common colored noises have been derived. Then, for multiple concurrently existing colored noises, an equivalence theorem relating to the stochastic differential equation has been proposed and proved. The equivalence theorem states that multiple stochastic differential equations can be equivalently expressed as a single stochastic differential equation in the wide sense stationarity, and gives the formulas to determine the coefficients of the equivalent stochastic differential equation. The equivalence theorem is the basis of the equivalent modeling and on-line compensation for multiple concurrently existing colored noises.
5. An on-line compensation scheme for the stochastic errors of the inertial sensors has been proposed with the aiding of GPS. In the compensation scheme, the white noise, the quantization noise and the colored noises are dealt with as follows: (1) the white noise is used to determine the covariance matrix of the process noise; (2) by modifiying the SINS error equation, the quantization noise is converted into white noise, and is used to augment the covariance matrix of the process noise; (3) the equivalent stochastic differential equation model for multiple colored noises, which is derived from the equivalence theorem, is used to augment the system equation of the integrated system. The results of the experimental tests have demonstrated that the proposed scheme has effectively compensated the stochastic errors of the inertial sensors, and as a result, dramatically improved the performances of the pure SINS.
6. To reduce the in-motion alignment error of SINS introduced by the modeling error under the condition of large initial heading error, a novel in-motion alignment approach has been proposed for the SINS. To implement the above approach, the system equation and the measurement equation for the coarse alignment and fine alignment have been derive respectively. Experimental tests have shown the superiority of the proposed alignment approach, and compared with the conventional approaches, the proposed approach has dramatically improved the accuracy and speed of the alignment procedure.
7. To reduce the in-motion alignment error of SINS introduced by the observable error, a novel in-motion alignment scheme has been designed with the aiding of high precision incremental carrier-phase. Experimental tests have indicated that the alignment accuracy of the SINS with the aiding of the incremental carrier-phase has almost approached the alignment accuracy with the aiding of GPS PPK (Post-Processing Kinematic) positioning.
1.以GPS载波相位观测量为基础,研究了载波相位时间差分观测量,并推导了其观测方程;探讨了载波相位时间差分观测量在导航与组合导航中的应用。误差分析表明载波相位时间差分兼具伪距和载波相位的优点,是一个非模糊的高精度的GPS观测量;导航试验研究表明由载波相位时间差分可以解算出毫米/秒量级的高精度速度;组合导航试验研究表明载波相位时间差分和捷联惯导的组合导航系统具有很高的短时精度,但是系统的位置误差存在着缓慢的积累效应。
2.针对含有两种观测量且两种观测量之间测量噪声差异较大的最优估计系统,提出了使用双速卡尔曼滤波器把低噪声的观测量以高频的形式、把高噪声的观测量以低频的形式融入到最优估计系统中。通过分析双速卡尔曼滤波的误差协方差传播过程,发现双速卡尔曼滤波技术可以有效地隔离来自于不同观测量的测量噪声,另外双速卡尔曼滤波技术还可用于实现非同步观测信息的融合以及提高运算效率。
3.以双速卡尔曼滤波器为数学工具,设计了基于载波相位时间差分、伪距和捷联惯导的紧组合导航系统。针对系统的实现问题,推导了双速卡尔曼滤波的系统方程(基于惯导误差方程)、高速卡尔曼滤波的测量方程(基于载波相位时间差分的观测方程)、以及低速卡尔曼滤波的测量方程(基于伪距的观测方程)。试验研究表明,提出的组合导航技术与经典组合导航技术相比,使导航的位置精度获得了改善,且明显改善了系统的速度精度、姿态精度和滑行性能。
4.有色噪声对惯性传感器的性能有重要影响,为了在组合导航过程中在线补偿有色噪声引起的惯性传感器误差,需要对有色噪声进行建模。首先,针对单独的有色噪声,提出了从其功率谱密度函数推导其随机微分方程模型的一般步骤,并推导了几种常见有色噪声的随机微分方程模型。然后,针对多种有色噪声并存的情况,提出并证明了随机微分方程的等价性定理,此定理指出在宽平稳的意义下,多个随机微分方程可以等价地使用单一随机微分方程描述,并给出了此等价随机微分方程系数参数的确定方法。此定理解决了多种有色噪声共存时的等价建模问题,为有色噪声的在线补偿奠定了数学基础。
5.设计了GPS辅助的惯性传感器随机误差在线补偿方案。在此补偿方案中,白噪声、量化噪声和有色噪声分别按照下列方法进行处理:(1)白噪声用以确定系统的过程噪声协方差矩阵;(2)通过修改惯导的误差方程,把量化噪声转化为等价的白噪声,并用以扩展系统的过程噪声协方差矩阵;(3)由等价性定理导出的多种有色噪声的等价随机微分方程模型用以扩展组合导航的系统方程。试验测试结果表明此在线补偿方案有效地补偿了惯性传感器的随机误差,明显改善了纯惯导系统的运行性能。
6.为了减小大航向误差条件下捷联惯导动基座初始对准的模型误差,提出并实现了一种大航向误差条件下的捷联惯导动基座初始对准方案。针对此对准方案的实现问题,推导了相应的粗对准误差方程和测量方程以及精对准误差方程和测量方程。试验结果验证了所提出方案的优越性,通过与经典方案的试验结果相对比,发现所提出的初始对准方案明显改善了大航向误差条件下初始对准的精度和速度。
7.为了减小捷联惯导动基座初始对准的观测量误差,设计了高精度的载波相位时间差分辅助的捷联惯导动基座初始对准方案。试验结果表明,载波相位时间差分辅助的捷联惯导动基座初始对准精度已经接近GPS PPK(Post-Processing Kinematic)定位辅助的捷联惯导动基座初始对准精度。
For the conventional GPS/SINS integration techniques, there exists a basic dilemma, namely, the high precision integrated systems generally have poor reliability and real-time performances, and on the other hand, the systems with good reliability and real-time performances generally have low precision. For example, the integration of GPS RTK/SINS can be very precise, however, its reliability will become poor with the increasing of the distance from the GPS base station and its real-time performances are not good because of the necessity for the resolution of the integer ambiguities. So, generally, GPS RTK/SINS integrated system can not be used in real-time or wide-area navigation applications. As an opposite example, the integration of GPS pseudorange/SINS is suitable for navigation applications because of its good reliability and real-time performances, however, its precision is low. So, the first goal of this research is to improve the overall performances of GPS/SINS integrated system by rearrangement of the GPS information and by using new integration techniques. Besides, the stochastic errors of the inertial sensors and the initial alignment error of the SINS are two kinds of the most crucial errors, so the second goal of this research is to develop some techniques to optimally compensate both of them with the aiding of GPS. To accomplish these two goals, the following work has been finished in this research:
1. A new GPS observable, incremental carrier-phase observable, has been derived based on GPS carrier-phase, and the corresponding observation equation for the incremental carrier-phase has also been derived. Furthermore, the applications of the incremental carrier-phase in navigation and integrated navigation have been discussed. Error analysis has shown that the incremental carrier-phase is an unambiguous and precise observable with the advantages of both pseudorange and carrier-phase. Navigation experiments have revealed that the mm/s level accuracy has been achieved in computing velocity from the incremental carrier-phase. Integrated navigation experiments have demonstrated that the integration of the incremental carrier-phase and SINS can obtain very high short-term navigation accuracy, while the position error will slowly accumulate with time.
2. For the optimal estimation systems with two kinds of observables whose measurement noises are quite different with each other, a novel optimal estimation technique, dual-rate Kalman Filtering technique, has been proposed, and the relevant theoretical analysis has been done. The dual-rate Kalman Filter fuses the low-noise observable with high rate, and the high-noise observable with low rate into the optimal estimation systems. By analyzing the propagation of the error covariance, it has been found that the proposed dual-rate Kalman Filtering can effectively isolate the noises from different error sources, and at the same time, the dual-rate Kalman Filtering can be used to fuse the asynchronous observations from different sensors and can also improve the computation efficiency.
3. By using the dual-rate Kalman Filter as the integration tool, a novel tightly coupled integration system based on the incremental carrier-phase, the pseudorang, and the SINS has been designed. To implement the above integrated system, the system equation for the dual-rate Kalman Filtering has been derived based on the SINS error equation, and the measurement equation for the high-rate Kalman Filtering as well as the measurement equation for the low-rate Kalman Filtering has also been derived based on the incremental carrier-phase and the pseudorange, respectively. Experimental tests have demonstrated that, compared with the conventional integration techniques, the proposed novel integration technique has improved the position accuracy, and dramatically improved the velocity and attitude accuracy as well as the coasting performance.
4. Colored noises have important influences to the performances of inertial sensors, and to compenstate the errors of the inertial sensors introduced by the colored noises in GPS/SINS integration, it is necessary to model the colored noises. Firstly, for a single colored noise, a general procedure has been proposed to derive its stochastic differential equation model from its power spectral density (PSD) function, and the stochastic differential equations of several common colored noises have been derived. Then, for multiple concurrently existing colored noises, an equivalence theorem relating to the stochastic differential equation has been proposed and proved. The equivalence theorem states that multiple stochastic differential equations can be equivalently expressed as a single stochastic differential equation in the wide sense stationarity, and gives the formulas to determine the coefficients of the equivalent stochastic differential equation. The equivalence theorem is the basis of the equivalent modeling and on-line compensation for multiple concurrently existing colored noises.
5. An on-line compensation scheme for the stochastic errors of the inertial sensors has been proposed with the aiding of GPS. In the compensation scheme, the white noise, the quantization noise and the colored noises are dealt with as follows: (1) the white noise is used to determine the covariance matrix of the process noise; (2) by modifiying the SINS error equation, the quantization noise is converted into white noise, and is used to augment the covariance matrix of the process noise; (3) the equivalent stochastic differential equation model for multiple colored noises, which is derived from the equivalence theorem, is used to augment the system equation of the integrated system. The results of the experimental tests have demonstrated that the proposed scheme has effectively compensated the stochastic errors of the inertial sensors, and as a result, dramatically improved the performances of the pure SINS.
6. To reduce the in-motion alignment error of SINS introduced by the modeling error under the condition of large initial heading error, a novel in-motion alignment approach has been proposed for the SINS. To implement the above approach, the system equation and the measurement equation for the coarse alignment and fine alignment have been derive respectively. Experimental tests have shown the superiority of the proposed alignment approach, and compared with the conventional approaches, the proposed approach has dramatically improved the accuracy and speed of the alignment procedure.
7. To reduce the in-motion alignment error of SINS introduced by the observable error, a novel in-motion alignment scheme has been designed with the aiding of high precision incremental carrier-phase. Experimental tests have indicated that the alignment accuracy of the SINS with the aiding of the incremental carrier-phase has almost approached the alignment accuracy with the aiding of GPS PPK (Post-Processing Kinematic) positioning.
引文
[1] Kaplan E D, Hegarty C. Understanding GPS Principles and Applications, 2nd ed[M]. Boston: Artech House Publishers, 2005: 1-14, 67, 87-100.
[2] Misra P, Enge P. Global Positioning System--Signals, Measurements, and Performance[M]. Lincoln: Ganga-Jamuna Press, 2001: 32, 124-130, 196-198.
[3] Hofmann-Wellenhof B, Lichtenegger H, Collins J. Global Positioning System--Theory and Practice, 4th ed[M]. New York: Springer-Verlag, 1997: 22, 184, 89-93.
[4] Kleusberg A, Teunissen P J G. GPS for Geodesy[M]. Berlin:Springer-Verlag, 1996: 141-174.
[5] GPS Joint Programme Office. Navstar GPS Space Segment/Navigation User Interfaces[Z]. 2006.
[6] Gurtner W. RINEX: The Receiver Independent Exchange Format Version 2.10[Z]. 2007.
[7] DoD Positioning Navigation and Timing Executive Committee. Global Positioning System Standard positioning Service Performance Standard[Z]. 2008.
[8] El-Rabbany A. Introduction to GPS[M]. Boston:Artech House, 2002.
[9] Bisnath S B, Beran T, Langley R B. Precise Platform Positioning with a Single GPS Receiver[J]. GPS World. 2002, 13(4): 42-49.
[10] Bisnath S, Gao Y. Precise Point Positioning--A Powerful Technique with a Promising Future[J]. GPS World. 2009, 20(4): 43-50.
[11] Zumberge J F, Heflin M B, Jefferson D C, Watkins M M. Precise Point Positioning for the Efficient and Robust Analysis of GPS Data from Large Networks[J]. Journal of Geophysical Research. 1997, 102(B3): 5005-5017.
[12] Hu C, Chen W, Wu J. Models and Algorithms Evaluation on GPS Kinematic Precise Point Positioning[C]. ION GNSS 21st. International Technical Meeting of the Satellite Division, Savannah, GA, USA, 16-19 September, 2008: 1875-1882.
[13] Laurichesse D, Mercier F. Integer Ambiguity Resolution on Undifferenced GPS Phase Measurements and its Application to PPP[C]. ION GNSS 20th International Technical Meeting of the Satellite Division, Fort Worth, TX, USA, 25-28 September, 2007: 839-848.
[14] Mervart L, Lukes Z, Rocken C, Iwabuchi T. Precise Point Positioning with Ambiguity Resolution in Real-Time[C]. ION GNSS 21st. International Technical Meeting of the Satellite Division, Savannah, GA, USA, 16-19 September, 2008.
[15] Geng J. Rapid Re-convergence in Real-Time Precise Point Positioning with Ambiguity Resolution[C]. ION GNSS 22nd. International Technical Meeting ofthe Satellite Division, Savannah, GA, USA, 22-25, September, 2009: 2437-2448.
[16] Van Bree R J P, Tiberius C C J M, Hauschild A. Real Time Satellite Clocks in Single Frequency Precise Point Positioning[C]. ION GNSS 22nd. International Technical Meeting of the Satellite Division, Savannah, GA, USA, 22-25, September, 2009: 2400-2414.
[17] Neumann J B, Manz A, Ford T J, Mulyk O. Test Results from a New 2cm Real Time Kinematic GPS Positioning System[C]. ION GPS-96, Kansas City, 17-20 September, 1996: 1-10.
[18] Langley R B. RTK GPS[J]. GPS World. 1998, 9(9): 70-76.
[19] Ueno M, Nimura T, Fujiwara T, Nonaka K. Evaluation of RTK-OTF Positioning System for Free Running Manoeubrability Test of a Model Ship[C]. IEEE Conference Oceans '97, Halifax, Nova Scotia, October, 1997: 1120-1125.
[20] Han S, Rizos C. GPS Network Design and Error Mitigation for Real-Time Continuous Array Monitoring Systems[C]. ION GPS-96, Kansas City, 17-20 September, 1996: 1827-1836.
[21] Rizos C. Network RTK Research and Implementation - A Geodetic Perspective[J]. Journal of Global Positioning Systems. 2003, 1(2): 144-150.
[22] Rizos C. Reference station network based RTK systems-concepts and progress[J]. Wuhan University Journal of Natural Sciences. 2003, 8(2): 566-574.
[23] Lim S, Rizos C. An Optimal Design for Server-Based RTK Systems[C]. ION GNSS 21st. International Technical Meeting of the Satellite Division, Savannah, GA, USA, 16-19 September, 2008: 2969-2974.
[24] Takac F, Zelzer O. The Relationship between Network RTK Solutions MAC, VRS, PRS, FKP AND i-MAX[C]. ION GNSS 21st. International Technical Meeting of the Satellite Division, Savannah, GA, USA, 16-19 September, 2008: 348-355.
[25] Heo Y, Li B, Lim S, Rizos C. Development of a Network Real-Time Kinematic Processing Platform[C]. ION GNSS 22nd. International Technical Meeting of the Satellite Division, Savannah, GA, USA, 22-25, September, 2009: 2668-2676.
[26] Zinas N. Assessment of a New Rover-Enhanced Network-Based Real Time Kinematic GNSS Data Processing Strategy[C]. ION GNSS 22nd. International Technical Meeting of the Satellite Division, Savannah, GA, USA, 22-25, September, 2009: 2692-2706.
[27] Zhang K, Wu F, Wu S, Rizos C, Roberts C. The latest development of a state-wide GNSS network-based RTK system in Australia[C]. ION GNSS 20th International Technical Meeting of the Satellite Division, Fort Worth, Texas, 25-28 September, 2007: 699-707.
[28] The Allan Consulting Group. Economic Benefits of High Resolution Positioning Services[Z]. 2008.
[29] Santos M, Nievinski F, Cove K, Kingdon R, Wells D. Range-Extended Post-Processing Kinematic (PPK) in a Marine Environment[C]. ION GNSS 18th International Technical Meeting of the Satellite Division, Long Beach, CA, USA, 13-16 September, 2005: 805-809.
[30] Defina A, Charqane K, Dominici D, Marucco G, Porporato C, De Agostino M, Manzino A M. User Terminal/Local Element System for Network Based Positioning Using RTK/EGNOS in Urban Enviroment[C]. ION GNSS 21st International Technical Meeting of the Satellite Division, Savannah, GA, USA, 16-19 September, 2008: 356-367.
[31] De Agostino M. Performance of Different Low-cost GNSS/INS Land Systems[C]. ION 22nd International Meeting of the Satellite Division, Savannan, GA, USA, 22-25 September, 2009: 3064-3074.
[32] Takasu T. RTKLIB ver. 2.2.2 Manual[Z]. Tokyo, Japan: Tokyo University of Marine Science and Technology, 2009.
[33] El-Mowafy A, Schwarz K P. Epoch-by-Epoch Ambiguity Resolution for Real-time Attitude Determination Using a GPS Multi-antenna System[J]. Navigation. 1995, 42(2): 391-408.
[34]郑冲,周伯昭,吴杰.单频GPS实时定姿系统研究[J].航天控制. 2006, 24(1): 14-18.
[35]郑伟,吴杰,赵健康. GPS实时定姿系统的设计与实现[J].空间科学学报. 2003, 23(4): 294-298.
[36]吴杰. GPS定姿系统动态检较[J].飞行器测控学报. 2002, 21(3): 87-92.
[37] Olynik M, Petovello M G, Cannon M E, Lachapelle G. Temporal Variability of GPS Error Sources and Their Effect on Relative Positioning Accuracy[C]. ION NTM 2002, San Diego, CA, 28-30 January, 2002: 877-888.
[38] Altshuler E E. Corrections for Tropospheric Range Error[R]. Air Force Cambridge Research Laboratory, 1971.
[39]金群锋.大气折射率影响因素的研究[D].杭州:浙江大学, 2006.
[40] Klobuchar J A. Ionospheric Effects on GPS[M]. Parkinson B, Spilker J, Axelrad P, et al(eds). Global Posilioning System: Theory and Applications, Washington D.C.:AIAA , 1996: 485-515.
[41] Feess W A, Stephens S G. Evaluation of GPS Ionospheric Time-Delay Model[J]. IEEE Transactions on Aerospace and Electronic Systems. 1987, 23(3): 332-338.
[42] Doherty P, Raffi E, Klobuchar J, El-Arini M B. Statistics of Time Rate of Change of Ionospheric Range Delay[C]. 7th International Technical Meeting of the Satellite Division of The Institute of Navigation, Salt Lake City, UT, USA, 20-23 September, 1994: 1589-1598.
[43] Diebel J. Representing Attitude: Euler Angles, Unit Quaternions, and RotationVectors[R]. Standford: Stanford University, 2006.
[44] Greenwood D T. Principles of Dynamics[M]. Upper Saddle River, New Jersey:Prentice Hall, 1988.
[45]武元新.对偶四元数导航算法与非线性高斯滤波研究[D].长沙:国防科学技术大学, 2005.
[46]陈哲.捷联惯导系统原理[M].北京:宇航出版社, 1986.
[47]袁信.导航系统[M].北京:航空工业出版社, 1993.
[48] Bortz J E. A New Mathematical Formulation for Strapdown Inertial Navigation[J]. IEEE Transactions on AES. 1970, 7(1): 61-66.
[49] Wiener T F. Theoretical Analysis of Gimballess Inertial Reference Equipment using Delta-Modulated Instruments[D]. Cambrage, Massachusetts: Massachusetts institute of Technology, 1962.
[50] Wilcox J C. A New Algorithm for Strapped-Down Inertial Navigation[J]. IEEE Transactions on AES. 1967, 3(5): 796-802.
[51] Jordan J W. An Accurate Strapdown Direction Cosine Algorithm[R]. Cambridge, Massachusetts: Electronics Research Center, 1969.
[52] Jordan J W. Direction Cosine Comutational Error[R]. Cambridge, Massachusetts: Electronics Research Center, 1969.
[53] Corporation U A. A Study of the Critical Computational Problems Associated with Strapdown Inertial Navigation Systems[R]. Washington D C: Electronics Research Center, 1968.
[54] Bortz J E. A New Concept in Strapdown Inertial Navigation[D]. Cambridge: Massachusetts Institute of Technology, 1969.
[55] Miller R B. A New Strapdown Attitude Algorithm[J]. Journal of Guidance. 1983, 6(4): 287-291.
[56] Lee J G, Yoon Y J. Extension of Strapdown Attitude Algorithm for High-Frquency Base Motion[J]. Journal of Guidance. 1988, 13(4).
[57] Ignagni M B. Optimal Strapdown Attitude Integration Algorithms[J]. Journal of Guidance. 1990, 13(2): 363-369.
[58] Wu Y, Hu X, Hu D, Li T, Lian J. Strapdown Inertial Navigation System Algorithms Based on Dual Quaternions[J]. IEEE Transactions on AES. 2005, 41(1): 110-132.
[59] Savage P G. Strapdown Inertial Navigation Integration Algorithm Design Part 2: Velocity and Position Algorithms[J]. Journal of Guidance, Control, and Dynamics. 1998, 21(2): 208-221.
[60] Savage P G. Strapdown Inertial Navigation Integration Algorithm Design Part 1: Attitude Algorithms[J]. Journal of Guidance, Control, and Dynamics. 1998, 21(1): 20-28.
[61]孔祥元,郭际明,刘宗泉.大地测量学基础[M].武汉:武汉大学出版社, 2001.
[62] Goshen-Meskin D, Bar-Itzhack I Y. Unified Approach to Inertial Navigation System Error Modeling[J]. Journal of Guidance, Control, and Dynamics. 1992, 15(3): 648-654.
[63]查特菲尔德(著),武凤德等(译).高精度惯性导航基础[M].北京:国防工业出版社, 2002.
[64]张树侠,孙静.捷联式惯性导航系统[M].北京:国防工业出版社, 1992.
[65] Greenspan R L. Inertial Navigation Technology from 1970-1995[J]. Navigation: Journal of The Institute of Navigation. 1995, 42(1): 165-185.
[66] Petovello M G. Real-Time Integration of a Tactical-Grade IMU and GPS for High-Accuracy Positioning and Navigation[D]. University of Calgary, 2003.
[67] Shin E. Accuracy Improvement of Low Cost INS/GPS for Land Applications[D]. University of Calgary, 2001.
[68] Savage P G. Strapdown Inertial Navigation Lecture Notes[Z]. Maple Plain, MN, USA: Strapdown Associates, 1997.
[69] Britting K R. Inertial Navigation Systems Analysis[M]. New York:John Wiley & Sons, 1971.
[70]邓正隆.惯性技术[M].哈尔滨:哈尔滨工业大学出版社, 2006.
[71]刘建业,曾庆化,赵伟,熊智.导航系统理论与应用[M].西安:西北工业大学出版社, 2010.
[72]袁保伦.四频激光陀螺旋转式惯导系统研究[D].长沙:国防科学技术大学, 2007.
[73]董绪荣,张守信,华仲春. GPS/INS组合导航定位及其应用[M].长沙:国防科技大学出版社, 1998.
[74] Gelb A. Applied optimal Estimation[M]. Cambridge:MIT Press, 1974.
[75] Grewal M S, Andrews A P. Kalman Filtering : Theory and Practice using MATLAB [M]. 2nd. ed; New York:John Wiley & Sons, 2001.
[76] Kalman R E. A New Approach to Linear Filtering and Prediction Problems[J]. Journal of Basic Engineering. 1960, 82: 35-45.
[77] Ho Y C, Lee R C K. A Bayesian Approach to Problems in Stochastic Estimation and Control[J]. IEEE Transactions on Automatic Control. 1964, 9(4): 333-339.
[78] Aggarwal P, Gu D, El-Sheimy N. Adaptive Particle Filter for INS/GPS Integration[C]. ION GNSS 19th International Technical Meeting of the Satellite Division, Fort Worth, TX, 26-29 September , 2006: 1606-1613.
[79] Gordon N J, Salmond D J, Smith A F M. Novel Approach to Nonlinear/non-Gaussian Bayesian State Estimation [C]. IEE Conference on Radar and Signal Processing, 1993: 107-113.
[80] Raol J R, Girija G. Sensor Data Fusion Algorithms Using Square-Root Information Filtering[C]. IEE Conference on Radar, Sonar and Navigation, April, 2002: 89-96.
[81] Zhang Y, Zhang H, Guanzhong D. A New Bias Partitioned Square-Root Information Filter and Smoother for Aircraft Flight State and Parameter Estimation[C]. 31st Conference on Decision and Control, Tucson, Arizona, USA, December, 1992: 741-742.
[82] Groves P D. Principles of GNSS, Inertial, and Multisensor Integrated Navigation Systems[M]. Boston:Artech House, 2008.
[83] George M, Sukkarieh S. Tightly coupled INS/GPS with bias estimation for uav applications.[C]. Australiasian Conference on Robotics and Automation , 2005.
[84] Wang W, Liu Z, Xie R. An Improved Tightly Coupled Approach for GPS/INS Integration[C]. IEEE Conference on Robotics, Automation and mechatronics, Singapore, 1-3 December, 2004: 1164-1167.
[85] Wendel J, Metzger J, Moenikes R, Maier A, Trommer G F. A Performance Comparison of Tightly Coupled GPS/INS Navigation Systems Based on Extended and Sigma Point Kalman Filters[C]. ION GNSS 18th International Technical Meeting of the Satellite Division, Long Beach, CA, USA, 13-16 September, 2005: 456-466.
[86] Zhang J, Knedlik S, Loffeld O. Performance Investigation of Real-time MEMS-IMU/GNSS Integrated System[C]. 22nd International Meeting of the Satellite Division of The Institute of Navigation, Savannah, GA, USA, 22-25 September, 2009: 978-986.
[87] Chiang K, Hou H, Niu X, El-Sheimy N. Improving the Positioning Accuracy of DGPS/MEMS IMU Integrated Systems Utilizing Cascade De-noising Algorithm[C]. ION GNSS 17th International Technical Meeting of the Satellite Division, Long Beach, CA, USA, 21-24 September, 2004: 809-818.
[88] Geng Y, Cole A, Dempster A, Rizos C, Wang J. Developing a Low-cost MEMS IMU/ DGPS Integrated System for Robust Machine Automation[C]. ION GNSS 20th International Technical Meeting of the Satellite Division, Fort Worth, TX, USA, 25-28, September, 2007: 1618-1624.
[89] Godha S, Cannon M E. Integration of DGPS with a Low Cost MEMS - Based Inertial Measurement Unit (IMU) for Land Vehicle Navigation Application[C]. ION GNSS 18th International Technical Meeting of the Satellite Division, Long Beach, CA, USA, 13-16 September, 2005: 333-345.
[90] Moore T, Hill C, Norris A, Hide C, Park D, Ward N. GNSS/INS Integration: Potential Impact on Maritime Navigation[C]. ION GNSS 20th International Technical Meeting of the Satellite Division, Fort Worth, TX, USA, 25-28 September, 2007: 1964-1976.
[91] Roesler G, Martell H. Tightly Coupled Processing of Precise Point Position (PPP) and INS Data[C]. 22nd International Meeting of the Satellite Division of the Institute of Navigation, Savannah, GA, 22-25 September, 2009: 1898-1905.
[92] Shin E, Scherzinger B. Inertially Aided Precise Point Positioning[C]. 22nd International Meeting of the Satellite Division of the Institute of Navigation, Savannah, GA, USA, 22-25, September, 2009: 1892-1897.
[93] Zhang Y, Gao Y. Integration of INS and Un-Differenced GPS Measurements for Precise Position and Attitude Determination[J]. The Journal of Navigation. 2008, 61(1): 87-97.
[94] Da R. Investigation of a Low-Cost and High-Accuracy GPWIMU System[C]. ION National Technical Meeting 1997, Santa, Monica, CA, USA, 14-16 January, 1997: 955-963.
[95] Huang Y, Chiang K, Lin Y, Lin J, Tsai J, Shih C. Performance Analysis of Low Cost INS/GPS POS Systems for Land Based MMS Utilizing LC and TC Integration[C]. 22nd International Meeting of the Satellite Division of the Institute of Navigation, Savannah, GA, USA, 22-25 September, 2009: 946-955.
[96] Kim J, Lee G, Lee J G. A Complete GPS/INS Integration Technique Using GPS Carrier Phase Measurements[C]. PLANS 1998, Palm Springs, CA, 20-23 April, 1998: 526-533.
[97] Mathur N G. Feasibility of Using a Low-Cost Inertial Measurement Unit with Centimeter Accuracy Differential Global positioning[D]. Ohio University, 1999.
[98] Van Graas F, Soloviev A. Precise Velocity Estimation Using a Stand-Alone GPS Receiver[J]. Navigation: Jouranl of the Institute of Navigation. 2004, 51(4): 283-292.
[99] Wendel J, Meister O, Monikes R, Trommer G F. Time-Differenced Carrier Phase Measurements for Tightly Coupled GPS/INS Integration[C]. PLANS 2006, 25-27 April, 2006: 54-60.
[100] Wendel J, Trommer G F. Tightly coupled GPS/INS integration for missile applications[J]. Aerospace Science and Technology. 2004, 8: 627-634.
[101]汤勇刚,练军想,吴文启,胡小平.北斗载波相位时间差分/SINS紧组合技术与实验研究[J].国防科学技术大学学报. 2007, 29(2): 19-23.
[102]汤勇刚,杨建文,吴文启,胡小平.无源北斗/捷联惯导(SINS)紧组合导航技术的应用研究[J].电光与控制. 2007, 14(2): 55-58.
[103] Akcayir Y, Ozkazanc Y. Gyroscope Drift Estimation Analysis in Land Navigation Systems[C]. IEEE conference on Control Application, 23-25 June, 2003: 1488-1491.
[104] Gao W, Nie Q, Zai G, Jia H. Gyroscope Drift Estimation in Tightly-coupled INS/GPS Navigation System[C]. IEEE Conference on Industrial Electronics andApplications, Harbin, China, 23-25 May, 2007: 391-396.
[105] Lee H, Jung S. Gyro Sensor Drift Compensation by Kalman Filter to Control a Mobile Inverted Pendulum Robot System[C]. IEEE International Conference on Industrial Technology 2009, Gippsland, VIC, Australia, 10-13 Febrary, 2009: 1-6.
[106] Han S, Wang J. Monitoring the Degree of Observability in Integrated GPS/INS Systems[C]. International Symposium on GPS/GNSS 2008, Tokyo, 11-14 November, 2008: 414-421.
[107] Niu X, El-Sheimy N. The Development of a Low-cost MEMS IMU/GPS Navigation System for Land Vehicles Using Auxiliary Velocity Updates in the Body Frame[C]. ION GPS 2005, Long Beach, CA, 13-16 September, 2005: 2003-2012.
[108] Wang J, Lee H K, Hewitson S, Lee H. Influence of Dynamics and Trajectory on Integrated GPS/INS Navigation Performance[J]. Journal of Global Positioning Systems. 2003, 2(2): 109-116.
[109] Grejner-Brzezinska D A. Direct Sensor Orientation in Airborne and Landbased mapping Applications[R]. Columbus, Ohio, USA: The Ohio State University, 2001.
[110] Schwarz K P, Wei M. INS/GPS Integration for Geomatics[R]. Calgary, Canada: The University of Calgary, 2001.
[111] Kelley R T, Katz I N, Bedoya C A. Design, development and evaluation of an Ada coded INS/GPS open loop Kalman filter[C]. IEEE Conference on Aerospace and Electronics , Dayton, OH, USA, 21-25 May, 1990: 382-388.
[112] Pham T M. Kalman Filter Mechanization for INS Airstart[C]. IEEE/AIAA 10th Digital Avionics Systems Conference, Los Angeles, CA, USA, 14-17 October, 1991: 516-525.
[113] Rogers R M. IMU In-Motion Alignment without Benefit of Attitude Initialization[J]. Navigation: Journal of the Institute of Navigation. 1997, 44(3).
[114]武汉大学测绘学院测量平差学科组.误差理论与测量平差基础[M].武汉:武汉大学出版社, 2005.
[115] Fan K K, Ding X L. Estimation of GPS Carrier Phase Multipath Signals Based on Site Environment[J]. Journal of Global Positioning Systems. 2006, 5(1-2): 22-28.
[116] Bisnath S B. Efficient, Automated Cycle-Slip Correction Of Dual-Frequency Kinematic GPS Data[C]. ION GPS 2000, Salt Lake, Utah, USA, 19-22 September, 2000: 145-154.
[117] Blewitt G. An Automatic Editing Algorithm for GPS Data[J]. Geophysical Research Letters. 1990, 17(3): 199-202.
[118] Colombo O L, Bhapkar U V, Evans A G. Inertial-Aided Cycle-SlipDetection/Correction for Precise, Long-Baseline Kinematic GPS[C]. ION GPS 1999, Nashville, TN, USA, 14-17 September, 1999: 1915-1921.
[119] Gao Y, Li Z. Cycle Slip Detection and Ambiguity Resolution Algorithms for Dual Frequency GPS Data Processing[J]. Marine Geodesy. 1999, 22(3): 169-181.
[120] Lee H K, Wang J, Rizos C, Park W Y. Carrier Phase Processing Issues for High Accuracy Integrated GPS/Pseudolite/INS Systems[C]. 11th International Association of Institutes of Navigation , Berlin, Germany, 21-24 October, 2003: 252.
[121] Dach R, Hugentobler U, Fridez P, Meindl M. Bernese GPS Software Version 5.0 Manual[Z]. Astronomical Institute, University of Bern, 2007.
[122] Fang R, Shi C, Lou Y, Zhao Q. Real-time Cycle-slip Detection of GPS Undifferenced Carrier-phase Measurements[C]. International Conference on Earth Observation Data Processing and Analysis , Wuhan, China, December, 2008: 72851U.
[123] Hewitson S, Wang J. GNSS Receiver Autonomous Integrity Monitoring (RAIM) for Multiple Outliers[J]. The European Journal of Navigation. 2006, 4(4): 47-57.
[124] Hewitson S, Wang J. GNSS Receiver Autonomous Integrity Monitoring (RAIM) with a Dynamic Model[J]. Journal of Navigation. 2007, 60(2): 247-263.
[125] Wang J, Ober P B. On the Availability of Fault Detection and Exclusion in GNSS Receiver Autonomous Integrity Monitoring [J]. Journal of Navigation. 2009, 62(2): 251-261.
[126] Titterton D H, Weston J L. Strapdown Inertial Navigation Technology[M]. 2nd. ed; Institution of Engineering and Technology , 2004.
[127] Farrell J L, Anoll R K, Mcconkey D D. IMU Coast: Not a Silver Vullet[C]. ION 55th Annual Meeting, Cambridge, MA, USA, 28-30 June, 1999: 159-168.
[128] Brown R G, Hwang P Y C. Introduction to Random Signals and Applied Kalman Filtering[M]. 3rd. ed; New York:John Wiley & Sons, 1997.
[129]张乃一.线性代数[M].天津:天津大学出版社, 2000.
[130] Benson D O. A Comparison of Two Approaches to Pure-Inertial and Doppler-Inertial Error Analysis[J]. IEEE Transactions on AES. 1975, 11(4): 447-455.
[131] Savage P. Strapdown Analytics[M]. Maple plain, Minnesota, USA:Strapdown Associates, 2000.
[132] Benson D O. Comments on "The Psi-Angle Error Equation in Strapdown Inertial Navigation Systems"[J]. IEEE Transactions on AES. 1979, 15(1): 168-170.
[133] Weinred A, Bar-Itzhack I Y. The Psi-Angle Error Equation in Strapdown Inertial Navigation Ssytems[J]. IEEE Transactions on AES. 1978, 14(3): 539-542.
[134] IEEE Aerospace And Electronic Society. IEEE Standard Specification FormatGuide and Test Procedure for Single-Axis Laser Gyros[S]. New York, USA, 2006.
[135] Ross S M. Stochastic Processes[M]. 2nd. ed; New York, USA:John Wiley & Sons, 1996.
[136] Grejner-Brzezinska D A, Wang J. Gravity Modeling for High-Accuracy GPS/INS Integration[J]. Navigation: Journal of the Institute of Navigation. 1998, 45(3): 209-220.
[137] Danik B. The Least-Square Approximation of Inertial Platform Drift[J]. IEEE Transaction on AES. 1965, 2(5): 591-594.
[138] Hammon R L. An Application of Random Process Theory to Gyro Drift Analysis[J]. IRE Transactions on Aeronautical and Navigational Electronics. 1960, September: 84-91.
[139] Hammon R L. Effects on Inertial Guidance Systems of Random Error Sources[J]. IRE Transactions on Aerospace and Navigational Electronics. 1962(December): 130-215.
[140] Dushman A. On Gyro Drift Models and Their Evaluation[J]. IRE Transactions on Aerospace and Navigational Electronics. 1962, December: 230-234.
[141] Van Dierendonck A J, Brown R G. Modeling Nonstationary Random Processes with an Application to Gyro Drift Rate[J]. IEEE Transactions on AES. 1969, 5(3): 423-428.
[142] Oravertz A S, Sandberg H J. Stationary and Nonstationary Characteristics of Gyro Drift Rate[J]. AIAA Journal. 1970(October): 1766-1772.
[143] Pandit S M, Zhang W. Modeling Random Gyro Drift Rate by Data Dependent Systems[J]. IEEE Transactions on AES. 1986, 22(4): 455-460.
[144] Jiang H, Yang W, Yang Y. State Space Modeling of Random Drift Rate in High-Precision Gyro[J]. IEEE Transactions on AES. 1996, 32(3): 1138-1143.
[145] Seong S M, Lee J G. Equivalent ARMA Model Representation for RLG Random Errors[J]. IEEE Transaction on AES. 2000, 36(1): 286-290.
[146] IEEE Aerospace And Electronic Society. IEEE Standard Specification Format Guide and Test Procedure for Single- Axis Interferometric Fiber Optic Gyros[S]. New York, USA, 1997.
[147] Yi Y. On Improving the Accuracy and Reliability of GPS/INS-Based Direct Sensor Georeferencing[D]. Ohio State University, 2007.
[148] IEEE Aerospace And Electronic Society. IEEE Recommended Practice for Inertial Sensor Test Equipment, Instrumentation, Data Acquisition, and Analysis[S]. 2005.
[149] Ng L C. On the Application of Allan Variance Method for Ring Laser Gyro Performance Characterization[R]. Lawrence Livermore National Laboratory , 1993.
[150] Ng L C. Characterization of Ring Laser Gyro Performance Using the Allan Variance Method[J]. Journal of Guidance. 1996, 20(1): 211-214.
[151] Allan D W. Statistics of Atomic Frequency Standards[J]. Proceedings of the IEEE. 1966, 54(2): 222-230.
[152] Sargent D, Wyman B O. Extraction of Stability Statistics From Integrated. Rate Data[C]. AIAA Guidance and Control Conference, Danvers, Massachusetts, USA, 1980: 88-94.
[153]高伯龙,王关根.陀螺数据的数学处理[J].国防科学技术大学学报. 1979(1): 91-106.
[154] Gao B, Zhang M, Zhang W. New Interpretation of Laser Gyro Drifts[J]. Science China Technological Sciences. 2010, 53(5): 1168-1175.
[155]张梅,张文.陀螺漂移的研究方法(一)[J].中国惯性技术学报. 2009, 17(2): 210-213.
[156]张梅,张文.激光陀螺的研究方法(二)[J].中国惯性技术学报. 2009, 17(3): 350-355.
[157] Savage P G. Analytical Modeling of Sensor Quantization in Strapdown Inertial Navigation Error Equations[J]. Journal of Guidance, Control, and Dynamics. 2002, 25(5): 833-842.
[158] Papoulis A. Probability, Random Variables, and Stochastic Processes [M]. 3rd. ed; New York:McGraw-Hill, 1991.
[159] Ogata K. Mordern Control Engineering [M]. 4th. ed; New Jersey:Prentice Hall, 2002.
[160] Yates R D, Goodman D J. Probability and Stochastic Processes[M]. New York:Jonh Wiley & Sons, 1998.
[161]房建成,万德均.惯性导航初始对准[M].南京:东南大学出版社, 1998.
[162] Bar-Itzhack I Y, Berman N. Control Theoretic Approach to Inertial Navigation Systems[J]. Journal of Guidance. 1988, 11(3): 237-245.
[163] Jiang Y F, Lin Y P. Error Estimation of INS Ground Alignment through Observability Analysis[J]. IEEE Transactions on AES. 1992, 28(1): 92-96.
[164] Goshen-Meskin D, Bar-Itzhack I Y. Observerbility Analysis of Piece-Wise Constant Systems with Application to Inertial Navigation[C]. 29th Conference on Decision and Control, Honolulu, Hawaii, USA, December, 1990: 821-826.
[165] Goshen-Meskin D, Bar-Itzhack I Y. Observability Analysis of Piece-Wise Constant Systems--Part I: Theory[J]. IEEE Transactions on AES. 1992, 28(4): 1056-1067.
[166] Goshen-Meskin D, Bar-Itzhack I Y. Observability Analysis of Piece-Wise Constant Systems--Part II: Application to Inertial Navigation In-Flight Alignment[J]. IEEE Transactions on AES. 1992, 28(4): 1068-1075.
[167] Boeing. Integrated GPS/INS User's Guide[Z]. Boeing North American, 1997.
[168]顾冬晴,秦永元.捷联惯导量化误差建模研究[J].中国惯性技术学报. 2004, 12(6): 13-17.
[169] Oppenheim A V, Willsky A S. Signals and Systems[M]. 2nd. ed; Prentice Hall, 1997.
[170] Dmitriyev S P, Stepanov O A, Shepel S V. Nonlinear Filtering Methods Applicatoin in INS Alignment[J]. IEEE Transactions on AES. 1997, 33(1): 260-272.
[171] Kong X, Nebot E M, Durrant-Whyte H. Development of a Nonlinear Psi-angle Model for Large Misalignment Errors and Its Application in INS Alignment and Calibration[C]. IEEE International Conference on Robotics and Automation , Detroit, Michigan, USA, May, 1999: 1430-1435.
[172] Jaffe R P. DQI Technical Description and Performance Capability[C]. AIAA Guidance, Navigation and Control Conference, San Diego, California, 29-31 July, 1996, Paper No: 96-3711.
[2] Misra P, Enge P. Global Positioning System--Signals, Measurements, and Performance[M]. Lincoln: Ganga-Jamuna Press, 2001: 32, 124-130, 196-198.
[3] Hofmann-Wellenhof B, Lichtenegger H, Collins J. Global Positioning System--Theory and Practice, 4th ed[M]. New York: Springer-Verlag, 1997: 22, 184, 89-93.
[4] Kleusberg A, Teunissen P J G. GPS for Geodesy[M]. Berlin:Springer-Verlag, 1996: 141-174.
[5] GPS Joint Programme Office. Navstar GPS Space Segment/Navigation User Interfaces[Z]. 2006.
[6] Gurtner W. RINEX: The Receiver Independent Exchange Format Version 2.10[Z]. 2007.
[7] DoD Positioning Navigation and Timing Executive Committee. Global Positioning System Standard positioning Service Performance Standard[Z]. 2008.
[8] El-Rabbany A. Introduction to GPS[M]. Boston:Artech House, 2002.
[9] Bisnath S B, Beran T, Langley R B. Precise Platform Positioning with a Single GPS Receiver[J]. GPS World. 2002, 13(4): 42-49.
[10] Bisnath S, Gao Y. Precise Point Positioning--A Powerful Technique with a Promising Future[J]. GPS World. 2009, 20(4): 43-50.
[11] Zumberge J F, Heflin M B, Jefferson D C, Watkins M M. Precise Point Positioning for the Efficient and Robust Analysis of GPS Data from Large Networks[J]. Journal of Geophysical Research. 1997, 102(B3): 5005-5017.
[12] Hu C, Chen W, Wu J. Models and Algorithms Evaluation on GPS Kinematic Precise Point Positioning[C]. ION GNSS 21st. International Technical Meeting of the Satellite Division, Savannah, GA, USA, 16-19 September, 2008: 1875-1882.
[13] Laurichesse D, Mercier F. Integer Ambiguity Resolution on Undifferenced GPS Phase Measurements and its Application to PPP[C]. ION GNSS 20th International Technical Meeting of the Satellite Division, Fort Worth, TX, USA, 25-28 September, 2007: 839-848.
[14] Mervart L, Lukes Z, Rocken C, Iwabuchi T. Precise Point Positioning with Ambiguity Resolution in Real-Time[C]. ION GNSS 21st. International Technical Meeting of the Satellite Division, Savannah, GA, USA, 16-19 September, 2008.
[15] Geng J. Rapid Re-convergence in Real-Time Precise Point Positioning with Ambiguity Resolution[C]. ION GNSS 22nd. International Technical Meeting ofthe Satellite Division, Savannah, GA, USA, 22-25, September, 2009: 2437-2448.
[16] Van Bree R J P, Tiberius C C J M, Hauschild A. Real Time Satellite Clocks in Single Frequency Precise Point Positioning[C]. ION GNSS 22nd. International Technical Meeting of the Satellite Division, Savannah, GA, USA, 22-25, September, 2009: 2400-2414.
[17] Neumann J B, Manz A, Ford T J, Mulyk O. Test Results from a New 2cm Real Time Kinematic GPS Positioning System[C]. ION GPS-96, Kansas City, 17-20 September, 1996: 1-10.
[18] Langley R B. RTK GPS[J]. GPS World. 1998, 9(9): 70-76.
[19] Ueno M, Nimura T, Fujiwara T, Nonaka K. Evaluation of RTK-OTF Positioning System for Free Running Manoeubrability Test of a Model Ship[C]. IEEE Conference Oceans '97, Halifax, Nova Scotia, October, 1997: 1120-1125.
[20] Han S, Rizos C. GPS Network Design and Error Mitigation for Real-Time Continuous Array Monitoring Systems[C]. ION GPS-96, Kansas City, 17-20 September, 1996: 1827-1836.
[21] Rizos C. Network RTK Research and Implementation - A Geodetic Perspective[J]. Journal of Global Positioning Systems. 2003, 1(2): 144-150.
[22] Rizos C. Reference station network based RTK systems-concepts and progress[J]. Wuhan University Journal of Natural Sciences. 2003, 8(2): 566-574.
[23] Lim S, Rizos C. An Optimal Design for Server-Based RTK Systems[C]. ION GNSS 21st. International Technical Meeting of the Satellite Division, Savannah, GA, USA, 16-19 September, 2008: 2969-2974.
[24] Takac F, Zelzer O. The Relationship between Network RTK Solutions MAC, VRS, PRS, FKP AND i-MAX[C]. ION GNSS 21st. International Technical Meeting of the Satellite Division, Savannah, GA, USA, 16-19 September, 2008: 348-355.
[25] Heo Y, Li B, Lim S, Rizos C. Development of a Network Real-Time Kinematic Processing Platform[C]. ION GNSS 22nd. International Technical Meeting of the Satellite Division, Savannah, GA, USA, 22-25, September, 2009: 2668-2676.
[26] Zinas N. Assessment of a New Rover-Enhanced Network-Based Real Time Kinematic GNSS Data Processing Strategy[C]. ION GNSS 22nd. International Technical Meeting of the Satellite Division, Savannah, GA, USA, 22-25, September, 2009: 2692-2706.
[27] Zhang K, Wu F, Wu S, Rizos C, Roberts C. The latest development of a state-wide GNSS network-based RTK system in Australia[C]. ION GNSS 20th International Technical Meeting of the Satellite Division, Fort Worth, Texas, 25-28 September, 2007: 699-707.
[28] The Allan Consulting Group. Economic Benefits of High Resolution Positioning Services[Z]. 2008.
[29] Santos M, Nievinski F, Cove K, Kingdon R, Wells D. Range-Extended Post-Processing Kinematic (PPK) in a Marine Environment[C]. ION GNSS 18th International Technical Meeting of the Satellite Division, Long Beach, CA, USA, 13-16 September, 2005: 805-809.
[30] Defina A, Charqane K, Dominici D, Marucco G, Porporato C, De Agostino M, Manzino A M. User Terminal/Local Element System for Network Based Positioning Using RTK/EGNOS in Urban Enviroment[C]. ION GNSS 21st International Technical Meeting of the Satellite Division, Savannah, GA, USA, 16-19 September, 2008: 356-367.
[31] De Agostino M. Performance of Different Low-cost GNSS/INS Land Systems[C]. ION 22nd International Meeting of the Satellite Division, Savannan, GA, USA, 22-25 September, 2009: 3064-3074.
[32] Takasu T. RTKLIB ver. 2.2.2 Manual[Z]. Tokyo, Japan: Tokyo University of Marine Science and Technology, 2009.
[33] El-Mowafy A, Schwarz K P. Epoch-by-Epoch Ambiguity Resolution for Real-time Attitude Determination Using a GPS Multi-antenna System[J]. Navigation. 1995, 42(2): 391-408.
[34]郑冲,周伯昭,吴杰.单频GPS实时定姿系统研究[J].航天控制. 2006, 24(1): 14-18.
[35]郑伟,吴杰,赵健康. GPS实时定姿系统的设计与实现[J].空间科学学报. 2003, 23(4): 294-298.
[36]吴杰. GPS定姿系统动态检较[J].飞行器测控学报. 2002, 21(3): 87-92.
[37] Olynik M, Petovello M G, Cannon M E, Lachapelle G. Temporal Variability of GPS Error Sources and Their Effect on Relative Positioning Accuracy[C]. ION NTM 2002, San Diego, CA, 28-30 January, 2002: 877-888.
[38] Altshuler E E. Corrections for Tropospheric Range Error[R]. Air Force Cambridge Research Laboratory, 1971.
[39]金群锋.大气折射率影响因素的研究[D].杭州:浙江大学, 2006.
[40] Klobuchar J A. Ionospheric Effects on GPS[M]. Parkinson B, Spilker J, Axelrad P, et al(eds). Global Posilioning System: Theory and Applications, Washington D.C.:AIAA , 1996: 485-515.
[41] Feess W A, Stephens S G. Evaluation of GPS Ionospheric Time-Delay Model[J]. IEEE Transactions on Aerospace and Electronic Systems. 1987, 23(3): 332-338.
[42] Doherty P, Raffi E, Klobuchar J, El-Arini M B. Statistics of Time Rate of Change of Ionospheric Range Delay[C]. 7th International Technical Meeting of the Satellite Division of The Institute of Navigation, Salt Lake City, UT, USA, 20-23 September, 1994: 1589-1598.
[43] Diebel J. Representing Attitude: Euler Angles, Unit Quaternions, and RotationVectors[R]. Standford: Stanford University, 2006.
[44] Greenwood D T. Principles of Dynamics[M]. Upper Saddle River, New Jersey:Prentice Hall, 1988.
[45]武元新.对偶四元数导航算法与非线性高斯滤波研究[D].长沙:国防科学技术大学, 2005.
[46]陈哲.捷联惯导系统原理[M].北京:宇航出版社, 1986.
[47]袁信.导航系统[M].北京:航空工业出版社, 1993.
[48] Bortz J E. A New Mathematical Formulation for Strapdown Inertial Navigation[J]. IEEE Transactions on AES. 1970, 7(1): 61-66.
[49] Wiener T F. Theoretical Analysis of Gimballess Inertial Reference Equipment using Delta-Modulated Instruments[D]. Cambrage, Massachusetts: Massachusetts institute of Technology, 1962.
[50] Wilcox J C. A New Algorithm for Strapped-Down Inertial Navigation[J]. IEEE Transactions on AES. 1967, 3(5): 796-802.
[51] Jordan J W. An Accurate Strapdown Direction Cosine Algorithm[R]. Cambridge, Massachusetts: Electronics Research Center, 1969.
[52] Jordan J W. Direction Cosine Comutational Error[R]. Cambridge, Massachusetts: Electronics Research Center, 1969.
[53] Corporation U A. A Study of the Critical Computational Problems Associated with Strapdown Inertial Navigation Systems[R]. Washington D C: Electronics Research Center, 1968.
[54] Bortz J E. A New Concept in Strapdown Inertial Navigation[D]. Cambridge: Massachusetts Institute of Technology, 1969.
[55] Miller R B. A New Strapdown Attitude Algorithm[J]. Journal of Guidance. 1983, 6(4): 287-291.
[56] Lee J G, Yoon Y J. Extension of Strapdown Attitude Algorithm for High-Frquency Base Motion[J]. Journal of Guidance. 1988, 13(4).
[57] Ignagni M B. Optimal Strapdown Attitude Integration Algorithms[J]. Journal of Guidance. 1990, 13(2): 363-369.
[58] Wu Y, Hu X, Hu D, Li T, Lian J. Strapdown Inertial Navigation System Algorithms Based on Dual Quaternions[J]. IEEE Transactions on AES. 2005, 41(1): 110-132.
[59] Savage P G. Strapdown Inertial Navigation Integration Algorithm Design Part 2: Velocity and Position Algorithms[J]. Journal of Guidance, Control, and Dynamics. 1998, 21(2): 208-221.
[60] Savage P G. Strapdown Inertial Navigation Integration Algorithm Design Part 1: Attitude Algorithms[J]. Journal of Guidance, Control, and Dynamics. 1998, 21(1): 20-28.
[61]孔祥元,郭际明,刘宗泉.大地测量学基础[M].武汉:武汉大学出版社, 2001.
[62] Goshen-Meskin D, Bar-Itzhack I Y. Unified Approach to Inertial Navigation System Error Modeling[J]. Journal of Guidance, Control, and Dynamics. 1992, 15(3): 648-654.
[63]查特菲尔德(著),武凤德等(译).高精度惯性导航基础[M].北京:国防工业出版社, 2002.
[64]张树侠,孙静.捷联式惯性导航系统[M].北京:国防工业出版社, 1992.
[65] Greenspan R L. Inertial Navigation Technology from 1970-1995[J]. Navigation: Journal of The Institute of Navigation. 1995, 42(1): 165-185.
[66] Petovello M G. Real-Time Integration of a Tactical-Grade IMU and GPS for High-Accuracy Positioning and Navigation[D]. University of Calgary, 2003.
[67] Shin E. Accuracy Improvement of Low Cost INS/GPS for Land Applications[D]. University of Calgary, 2001.
[68] Savage P G. Strapdown Inertial Navigation Lecture Notes[Z]. Maple Plain, MN, USA: Strapdown Associates, 1997.
[69] Britting K R. Inertial Navigation Systems Analysis[M]. New York:John Wiley & Sons, 1971.
[70]邓正隆.惯性技术[M].哈尔滨:哈尔滨工业大学出版社, 2006.
[71]刘建业,曾庆化,赵伟,熊智.导航系统理论与应用[M].西安:西北工业大学出版社, 2010.
[72]袁保伦.四频激光陀螺旋转式惯导系统研究[D].长沙:国防科学技术大学, 2007.
[73]董绪荣,张守信,华仲春. GPS/INS组合导航定位及其应用[M].长沙:国防科技大学出版社, 1998.
[74] Gelb A. Applied optimal Estimation[M]. Cambridge:MIT Press, 1974.
[75] Grewal M S, Andrews A P. Kalman Filtering : Theory and Practice using MATLAB [M]. 2nd. ed; New York:John Wiley & Sons, 2001.
[76] Kalman R E. A New Approach to Linear Filtering and Prediction Problems[J]. Journal of Basic Engineering. 1960, 82: 35-45.
[77] Ho Y C, Lee R C K. A Bayesian Approach to Problems in Stochastic Estimation and Control[J]. IEEE Transactions on Automatic Control. 1964, 9(4): 333-339.
[78] Aggarwal P, Gu D, El-Sheimy N. Adaptive Particle Filter for INS/GPS Integration[C]. ION GNSS 19th International Technical Meeting of the Satellite Division, Fort Worth, TX, 26-29 September , 2006: 1606-1613.
[79] Gordon N J, Salmond D J, Smith A F M. Novel Approach to Nonlinear/non-Gaussian Bayesian State Estimation [C]. IEE Conference on Radar and Signal Processing, 1993: 107-113.
[80] Raol J R, Girija G. Sensor Data Fusion Algorithms Using Square-Root Information Filtering[C]. IEE Conference on Radar, Sonar and Navigation, April, 2002: 89-96.
[81] Zhang Y, Zhang H, Guanzhong D. A New Bias Partitioned Square-Root Information Filter and Smoother for Aircraft Flight State and Parameter Estimation[C]. 31st Conference on Decision and Control, Tucson, Arizona, USA, December, 1992: 741-742.
[82] Groves P D. Principles of GNSS, Inertial, and Multisensor Integrated Navigation Systems[M]. Boston:Artech House, 2008.
[83] George M, Sukkarieh S. Tightly coupled INS/GPS with bias estimation for uav applications.[C]. Australiasian Conference on Robotics and Automation , 2005.
[84] Wang W, Liu Z, Xie R. An Improved Tightly Coupled Approach for GPS/INS Integration[C]. IEEE Conference on Robotics, Automation and mechatronics, Singapore, 1-3 December, 2004: 1164-1167.
[85] Wendel J, Metzger J, Moenikes R, Maier A, Trommer G F. A Performance Comparison of Tightly Coupled GPS/INS Navigation Systems Based on Extended and Sigma Point Kalman Filters[C]. ION GNSS 18th International Technical Meeting of the Satellite Division, Long Beach, CA, USA, 13-16 September, 2005: 456-466.
[86] Zhang J, Knedlik S, Loffeld O. Performance Investigation of Real-time MEMS-IMU/GNSS Integrated System[C]. 22nd International Meeting of the Satellite Division of The Institute of Navigation, Savannah, GA, USA, 22-25 September, 2009: 978-986.
[87] Chiang K, Hou H, Niu X, El-Sheimy N. Improving the Positioning Accuracy of DGPS/MEMS IMU Integrated Systems Utilizing Cascade De-noising Algorithm[C]. ION GNSS 17th International Technical Meeting of the Satellite Division, Long Beach, CA, USA, 21-24 September, 2004: 809-818.
[88] Geng Y, Cole A, Dempster A, Rizos C, Wang J. Developing a Low-cost MEMS IMU/ DGPS Integrated System for Robust Machine Automation[C]. ION GNSS 20th International Technical Meeting of the Satellite Division, Fort Worth, TX, USA, 25-28, September, 2007: 1618-1624.
[89] Godha S, Cannon M E. Integration of DGPS with a Low Cost MEMS - Based Inertial Measurement Unit (IMU) for Land Vehicle Navigation Application[C]. ION GNSS 18th International Technical Meeting of the Satellite Division, Long Beach, CA, USA, 13-16 September, 2005: 333-345.
[90] Moore T, Hill C, Norris A, Hide C, Park D, Ward N. GNSS/INS Integration: Potential Impact on Maritime Navigation[C]. ION GNSS 20th International Technical Meeting of the Satellite Division, Fort Worth, TX, USA, 25-28 September, 2007: 1964-1976.
[91] Roesler G, Martell H. Tightly Coupled Processing of Precise Point Position (PPP) and INS Data[C]. 22nd International Meeting of the Satellite Division of the Institute of Navigation, Savannah, GA, 22-25 September, 2009: 1898-1905.
[92] Shin E, Scherzinger B. Inertially Aided Precise Point Positioning[C]. 22nd International Meeting of the Satellite Division of the Institute of Navigation, Savannah, GA, USA, 22-25, September, 2009: 1892-1897.
[93] Zhang Y, Gao Y. Integration of INS and Un-Differenced GPS Measurements for Precise Position and Attitude Determination[J]. The Journal of Navigation. 2008, 61(1): 87-97.
[94] Da R. Investigation of a Low-Cost and High-Accuracy GPWIMU System[C]. ION National Technical Meeting 1997, Santa, Monica, CA, USA, 14-16 January, 1997: 955-963.
[95] Huang Y, Chiang K, Lin Y, Lin J, Tsai J, Shih C. Performance Analysis of Low Cost INS/GPS POS Systems for Land Based MMS Utilizing LC and TC Integration[C]. 22nd International Meeting of the Satellite Division of the Institute of Navigation, Savannah, GA, USA, 22-25 September, 2009: 946-955.
[96] Kim J, Lee G, Lee J G. A Complete GPS/INS Integration Technique Using GPS Carrier Phase Measurements[C]. PLANS 1998, Palm Springs, CA, 20-23 April, 1998: 526-533.
[97] Mathur N G. Feasibility of Using a Low-Cost Inertial Measurement Unit with Centimeter Accuracy Differential Global positioning[D]. Ohio University, 1999.
[98] Van Graas F, Soloviev A. Precise Velocity Estimation Using a Stand-Alone GPS Receiver[J]. Navigation: Jouranl of the Institute of Navigation. 2004, 51(4): 283-292.
[99] Wendel J, Meister O, Monikes R, Trommer G F. Time-Differenced Carrier Phase Measurements for Tightly Coupled GPS/INS Integration[C]. PLANS 2006, 25-27 April, 2006: 54-60.
[100] Wendel J, Trommer G F. Tightly coupled GPS/INS integration for missile applications[J]. Aerospace Science and Technology. 2004, 8: 627-634.
[101]汤勇刚,练军想,吴文启,胡小平.北斗载波相位时间差分/SINS紧组合技术与实验研究[J].国防科学技术大学学报. 2007, 29(2): 19-23.
[102]汤勇刚,杨建文,吴文启,胡小平.无源北斗/捷联惯导(SINS)紧组合导航技术的应用研究[J].电光与控制. 2007, 14(2): 55-58.
[103] Akcayir Y, Ozkazanc Y. Gyroscope Drift Estimation Analysis in Land Navigation Systems[C]. IEEE conference on Control Application, 23-25 June, 2003: 1488-1491.
[104] Gao W, Nie Q, Zai G, Jia H. Gyroscope Drift Estimation in Tightly-coupled INS/GPS Navigation System[C]. IEEE Conference on Industrial Electronics andApplications, Harbin, China, 23-25 May, 2007: 391-396.
[105] Lee H, Jung S. Gyro Sensor Drift Compensation by Kalman Filter to Control a Mobile Inverted Pendulum Robot System[C]. IEEE International Conference on Industrial Technology 2009, Gippsland, VIC, Australia, 10-13 Febrary, 2009: 1-6.
[106] Han S, Wang J. Monitoring the Degree of Observability in Integrated GPS/INS Systems[C]. International Symposium on GPS/GNSS 2008, Tokyo, 11-14 November, 2008: 414-421.
[107] Niu X, El-Sheimy N. The Development of a Low-cost MEMS IMU/GPS Navigation System for Land Vehicles Using Auxiliary Velocity Updates in the Body Frame[C]. ION GPS 2005, Long Beach, CA, 13-16 September, 2005: 2003-2012.
[108] Wang J, Lee H K, Hewitson S, Lee H. Influence of Dynamics and Trajectory on Integrated GPS/INS Navigation Performance[J]. Journal of Global Positioning Systems. 2003, 2(2): 109-116.
[109] Grejner-Brzezinska D A. Direct Sensor Orientation in Airborne and Landbased mapping Applications[R]. Columbus, Ohio, USA: The Ohio State University, 2001.
[110] Schwarz K P, Wei M. INS/GPS Integration for Geomatics[R]. Calgary, Canada: The University of Calgary, 2001.
[111] Kelley R T, Katz I N, Bedoya C A. Design, development and evaluation of an Ada coded INS/GPS open loop Kalman filter[C]. IEEE Conference on Aerospace and Electronics , Dayton, OH, USA, 21-25 May, 1990: 382-388.
[112] Pham T M. Kalman Filter Mechanization for INS Airstart[C]. IEEE/AIAA 10th Digital Avionics Systems Conference, Los Angeles, CA, USA, 14-17 October, 1991: 516-525.
[113] Rogers R M. IMU In-Motion Alignment without Benefit of Attitude Initialization[J]. Navigation: Journal of the Institute of Navigation. 1997, 44(3).
[114]武汉大学测绘学院测量平差学科组.误差理论与测量平差基础[M].武汉:武汉大学出版社, 2005.
[115] Fan K K, Ding X L. Estimation of GPS Carrier Phase Multipath Signals Based on Site Environment[J]. Journal of Global Positioning Systems. 2006, 5(1-2): 22-28.
[116] Bisnath S B. Efficient, Automated Cycle-Slip Correction Of Dual-Frequency Kinematic GPS Data[C]. ION GPS 2000, Salt Lake, Utah, USA, 19-22 September, 2000: 145-154.
[117] Blewitt G. An Automatic Editing Algorithm for GPS Data[J]. Geophysical Research Letters. 1990, 17(3): 199-202.
[118] Colombo O L, Bhapkar U V, Evans A G. Inertial-Aided Cycle-SlipDetection/Correction for Precise, Long-Baseline Kinematic GPS[C]. ION GPS 1999, Nashville, TN, USA, 14-17 September, 1999: 1915-1921.
[119] Gao Y, Li Z. Cycle Slip Detection and Ambiguity Resolution Algorithms for Dual Frequency GPS Data Processing[J]. Marine Geodesy. 1999, 22(3): 169-181.
[120] Lee H K, Wang J, Rizos C, Park W Y. Carrier Phase Processing Issues for High Accuracy Integrated GPS/Pseudolite/INS Systems[C]. 11th International Association of Institutes of Navigation , Berlin, Germany, 21-24 October, 2003: 252.
[121] Dach R, Hugentobler U, Fridez P, Meindl M. Bernese GPS Software Version 5.0 Manual[Z]. Astronomical Institute, University of Bern, 2007.
[122] Fang R, Shi C, Lou Y, Zhao Q. Real-time Cycle-slip Detection of GPS Undifferenced Carrier-phase Measurements[C]. International Conference on Earth Observation Data Processing and Analysis , Wuhan, China, December, 2008: 72851U.
[123] Hewitson S, Wang J. GNSS Receiver Autonomous Integrity Monitoring (RAIM) for Multiple Outliers[J]. The European Journal of Navigation. 2006, 4(4): 47-57.
[124] Hewitson S, Wang J. GNSS Receiver Autonomous Integrity Monitoring (RAIM) with a Dynamic Model[J]. Journal of Navigation. 2007, 60(2): 247-263.
[125] Wang J, Ober P B. On the Availability of Fault Detection and Exclusion in GNSS Receiver Autonomous Integrity Monitoring [J]. Journal of Navigation. 2009, 62(2): 251-261.
[126] Titterton D H, Weston J L. Strapdown Inertial Navigation Technology[M]. 2nd. ed; Institution of Engineering and Technology , 2004.
[127] Farrell J L, Anoll R K, Mcconkey D D. IMU Coast: Not a Silver Vullet[C]. ION 55th Annual Meeting, Cambridge, MA, USA, 28-30 June, 1999: 159-168.
[128] Brown R G, Hwang P Y C. Introduction to Random Signals and Applied Kalman Filtering[M]. 3rd. ed; New York:John Wiley & Sons, 1997.
[129]张乃一.线性代数[M].天津:天津大学出版社, 2000.
[130] Benson D O. A Comparison of Two Approaches to Pure-Inertial and Doppler-Inertial Error Analysis[J]. IEEE Transactions on AES. 1975, 11(4): 447-455.
[131] Savage P. Strapdown Analytics[M]. Maple plain, Minnesota, USA:Strapdown Associates, 2000.
[132] Benson D O. Comments on "The Psi-Angle Error Equation in Strapdown Inertial Navigation Systems"[J]. IEEE Transactions on AES. 1979, 15(1): 168-170.
[133] Weinred A, Bar-Itzhack I Y. The Psi-Angle Error Equation in Strapdown Inertial Navigation Ssytems[J]. IEEE Transactions on AES. 1978, 14(3): 539-542.
[134] IEEE Aerospace And Electronic Society. IEEE Standard Specification FormatGuide and Test Procedure for Single-Axis Laser Gyros[S]. New York, USA, 2006.
[135] Ross S M. Stochastic Processes[M]. 2nd. ed; New York, USA:John Wiley & Sons, 1996.
[136] Grejner-Brzezinska D A, Wang J. Gravity Modeling for High-Accuracy GPS/INS Integration[J]. Navigation: Journal of the Institute of Navigation. 1998, 45(3): 209-220.
[137] Danik B. The Least-Square Approximation of Inertial Platform Drift[J]. IEEE Transaction on AES. 1965, 2(5): 591-594.
[138] Hammon R L. An Application of Random Process Theory to Gyro Drift Analysis[J]. IRE Transactions on Aeronautical and Navigational Electronics. 1960, September: 84-91.
[139] Hammon R L. Effects on Inertial Guidance Systems of Random Error Sources[J]. IRE Transactions on Aerospace and Navigational Electronics. 1962(December): 130-215.
[140] Dushman A. On Gyro Drift Models and Their Evaluation[J]. IRE Transactions on Aerospace and Navigational Electronics. 1962, December: 230-234.
[141] Van Dierendonck A J, Brown R G. Modeling Nonstationary Random Processes with an Application to Gyro Drift Rate[J]. IEEE Transactions on AES. 1969, 5(3): 423-428.
[142] Oravertz A S, Sandberg H J. Stationary and Nonstationary Characteristics of Gyro Drift Rate[J]. AIAA Journal. 1970(October): 1766-1772.
[143] Pandit S M, Zhang W. Modeling Random Gyro Drift Rate by Data Dependent Systems[J]. IEEE Transactions on AES. 1986, 22(4): 455-460.
[144] Jiang H, Yang W, Yang Y. State Space Modeling of Random Drift Rate in High-Precision Gyro[J]. IEEE Transactions on AES. 1996, 32(3): 1138-1143.
[145] Seong S M, Lee J G. Equivalent ARMA Model Representation for RLG Random Errors[J]. IEEE Transaction on AES. 2000, 36(1): 286-290.
[146] IEEE Aerospace And Electronic Society. IEEE Standard Specification Format Guide and Test Procedure for Single- Axis Interferometric Fiber Optic Gyros[S]. New York, USA, 1997.
[147] Yi Y. On Improving the Accuracy and Reliability of GPS/INS-Based Direct Sensor Georeferencing[D]. Ohio State University, 2007.
[148] IEEE Aerospace And Electronic Society. IEEE Recommended Practice for Inertial Sensor Test Equipment, Instrumentation, Data Acquisition, and Analysis[S]. 2005.
[149] Ng L C. On the Application of Allan Variance Method for Ring Laser Gyro Performance Characterization[R]. Lawrence Livermore National Laboratory , 1993.
[150] Ng L C. Characterization of Ring Laser Gyro Performance Using the Allan Variance Method[J]. Journal of Guidance. 1996, 20(1): 211-214.
[151] Allan D W. Statistics of Atomic Frequency Standards[J]. Proceedings of the IEEE. 1966, 54(2): 222-230.
[152] Sargent D, Wyman B O. Extraction of Stability Statistics From Integrated. Rate Data[C]. AIAA Guidance and Control Conference, Danvers, Massachusetts, USA, 1980: 88-94.
[153]高伯龙,王关根.陀螺数据的数学处理[J].国防科学技术大学学报. 1979(1): 91-106.
[154] Gao B, Zhang M, Zhang W. New Interpretation of Laser Gyro Drifts[J]. Science China Technological Sciences. 2010, 53(5): 1168-1175.
[155]张梅,张文.陀螺漂移的研究方法(一)[J].中国惯性技术学报. 2009, 17(2): 210-213.
[156]张梅,张文.激光陀螺的研究方法(二)[J].中国惯性技术学报. 2009, 17(3): 350-355.
[157] Savage P G. Analytical Modeling of Sensor Quantization in Strapdown Inertial Navigation Error Equations[J]. Journal of Guidance, Control, and Dynamics. 2002, 25(5): 833-842.
[158] Papoulis A. Probability, Random Variables, and Stochastic Processes [M]. 3rd. ed; New York:McGraw-Hill, 1991.
[159] Ogata K. Mordern Control Engineering [M]. 4th. ed; New Jersey:Prentice Hall, 2002.
[160] Yates R D, Goodman D J. Probability and Stochastic Processes[M]. New York:Jonh Wiley & Sons, 1998.
[161]房建成,万德均.惯性导航初始对准[M].南京:东南大学出版社, 1998.
[162] Bar-Itzhack I Y, Berman N. Control Theoretic Approach to Inertial Navigation Systems[J]. Journal of Guidance. 1988, 11(3): 237-245.
[163] Jiang Y F, Lin Y P. Error Estimation of INS Ground Alignment through Observability Analysis[J]. IEEE Transactions on AES. 1992, 28(1): 92-96.
[164] Goshen-Meskin D, Bar-Itzhack I Y. Observerbility Analysis of Piece-Wise Constant Systems with Application to Inertial Navigation[C]. 29th Conference on Decision and Control, Honolulu, Hawaii, USA, December, 1990: 821-826.
[165] Goshen-Meskin D, Bar-Itzhack I Y. Observability Analysis of Piece-Wise Constant Systems--Part I: Theory[J]. IEEE Transactions on AES. 1992, 28(4): 1056-1067.
[166] Goshen-Meskin D, Bar-Itzhack I Y. Observability Analysis of Piece-Wise Constant Systems--Part II: Application to Inertial Navigation In-Flight Alignment[J]. IEEE Transactions on AES. 1992, 28(4): 1068-1075.
[167] Boeing. Integrated GPS/INS User's Guide[Z]. Boeing North American, 1997.
[168]顾冬晴,秦永元.捷联惯导量化误差建模研究[J].中国惯性技术学报. 2004, 12(6): 13-17.
[169] Oppenheim A V, Willsky A S. Signals and Systems[M]. 2nd. ed; Prentice Hall, 1997.
[170] Dmitriyev S P, Stepanov O A, Shepel S V. Nonlinear Filtering Methods Applicatoin in INS Alignment[J]. IEEE Transactions on AES. 1997, 33(1): 260-272.
[171] Kong X, Nebot E M, Durrant-Whyte H. Development of a Nonlinear Psi-angle Model for Large Misalignment Errors and Its Application in INS Alignment and Calibration[C]. IEEE International Conference on Robotics and Automation , Detroit, Michigan, USA, May, 1999: 1430-1435.
[172] Jaffe R P. DQI Technical Description and Performance Capability[C]. AIAA Guidance, Navigation and Control Conference, San Diego, California, 29-31 July, 1996, Paper No: 96-3711.