小型AUV水下导航系统关键技术研究
摘要
本文研究了小型AUV水下组合导航系统所涉及的几个关键技术：导航器件误差参数的辨识与滤波、航姿参考系统的姿态解算以及组合导航系统的信息融合策略。
小型AUV的组合导航系统由于受到艇体体积和成本的限制,往往选用体积小、成本低、功耗小的MEMS惯性器件,以及体积和功耗均较小的Doppler测速仪。这些导航器件虽然能够满足小型AUV的机械与电气特性要求,但是往往测量精度低。采用上述导航器件构成的组合导航系统不但定位精度低,甚至会影响AUV的制导与控制系统的稳定性。论文的前半部分主要就是针对小型AUV采用的导航器件上述问题展开研究。
首先在对MEMS惯性器件的确定性误差进行标定后,根据经典Allan方差技术,分别根据直接采样和交叠采样技术推导了递推Allan方差辨识算法,使得MEMS惯性器件随机误差参数的在线辨识成为可能。
然后运用时间序列分析技术建立了组合导航系统中相控阵Doppler测速仪的噪声模型,并借鉴S面控制算法提出了适用于小型AUV的Doppler测速仪的Kalman滤波器。
最后针对小型AUV采用的航姿参考系统中电子罗盘子系统需要进行自差校正的问题,提出了一种基于UT变换的强跟踪UKF算法,随之又改进了算法中渐消因子矩阵的计算方法,并又将噪声参数在线估计技术引入到该算法中,使得该算法不但自适应性好而且鲁棒性强,解决了小型AUV在海面进行自差校正时遇到的海浪干扰问题,提高了UKF算法对自差参数的辨识能力。
在随后的章节中,运用频域内连续信号的分解与重构技术,基于FFT算法提出了角速率输入下的频域姿态解算方案,并在Matlab仿真环境下实现了频域姿态解算方案,通过与四元数微分方程的四阶龙格-库塔求解方法相比,该算法能够有效减小载体做圆锥运动时姿态解算存在的圆锥误差,提高系统的姿态解算精度。
组合导航系统中电子罗盘子系统虽然精度较高,但在小型AUV运动过程中,往往会受到非重力加速度的干扰,导致其输出的航姿信息产生较大的跳变误差。而基于MEMS陀螺组件解算得到的航姿信息虽然不易受非重力加速度的干扰,却存在较大的积累误差。基于上述特点,采用自适应加权算法,将电子罗盘输出的航姿信息与基于MEMS陀螺组件解算得出的航姿信息相融合,平滑了电子罗盘输出的水平姿态角和航向角,提高了整个航姿系统的动态性能。
最后针对小型AUV的水下组合导航系统在海流干扰下存在模型误差的问题,提出了一种带模型误差的自适应UKF算法,该算法基于虚拟噪声的思想,利用次优MAP估值器对虚拟噪声的统计量进行实时估计,提高了小型AUV导航系统的定位精度和滤波能力。
The dissertation has investigated several key technologies of underwater integrated navigation system of small AUV (Autonomous Underwater Vehicles). They were devices error parameters identification technique and their noise filtering technique, attitude determination of AHRS (Attitude and Heading Reference System), and the fusion strategy of integrated navigation system.
Owing to restrictions on hull size and cost of small AUV, its integrated navigation system always adopts MEMS inertial devices, which have small volume, low cost and low power consumption, besides small, low power consumption Doppler velocity log. These navigation devices can meet the requirements of mechanical and electrical characteristics of small AUV, although they often have low accuracy. The integrated navigation system consists of these devices has poor performance, and even affects the small AUV's guidance and control system stability. The first half of dissertation focused on the above problems of the navigation equipment used by small AUV.
First of all, after calibrating deterministic error of MEMS inertial devices, Allan variance recursive identification algorithm was derived using overlapping and direct sampling technique respectively, founded on classic Allan variance identification technique, which made it possible to identify the parameters of random noise online for each MEMS navigation devices.
Then the noise model of phased-array Doppler velocity log adopted by small AUV's navigation system was built by time series analysis technique. Referencing the S plane control algorithm, the Kalman filter to Doppler velocity log was designed, suitable for the small AUV.
At last, strong tracking UKF algorithm based on unscented transformation was designed, using in the small AUV's compass calibration process. The strong tracking algorithm was introduced into UKF completely based on UT technique, and the algorithm of its fading factor matrix was improved, meanwhile estimator of noise parameters was also introduced into this algorithm, so that made the algorithm have good adaptability and robustness. The algorithm solved the wave interference problem, and improved the recognition ability of error parameters of UKF algorithm, when small AUV's compass calibrating on the sea surface.
In the following chapters, angular rate input attitude determination solution was designed based on FFT (Fast Fourier Transformation) algorithm, using continuous signal decomposition and reconstruction technique in frequency domain. The algorithm was programmed in Matlab and compared with the quaternion attitude determination solved by fourth order Runge-Kutta algorithm in time domain. The comparison showed that frequency domain algorithm can reduce the coning error effectively, and improve the accuracy of attitude determination.
Although the accuracy of electronic compass in integrated navigation system is higher, it is easily interfered by non-gravitational acceleration, causing jump error in output attitude signal. Meanwhile, the heading and attitude information solved by MEMS gyro unit is not easily spoiled by non-gravitational acceleration, but its accumulation error is large. Based on the above characteristics, the attitude information respectively solved by electronic compass and MEMS gyro unit was fused by adaptive weighted algorithm, so that the attitude and heading information by electronic compass was smoothed, and the dynamic performance of the whole AHRS was improved as well.
In the last part of this thesis, an adaptive UKF algorithm with model error was designed to reduce the navigation system model error caused by ocean current disturbance. Based on the idea of virtual noise, this algorithm used suboptimal MAP estimator to calculate statistics of virtual noise real time, which helped to improve the accuracy of navigation system and to enhance the ability of filtering.
小型AUV的组合导航系统由于受到艇体体积和成本的限制,往往选用体积小、成本低、功耗小的MEMS惯性器件,以及体积和功耗均较小的Doppler测速仪。这些导航器件虽然能够满足小型AUV的机械与电气特性要求,但是往往测量精度低。采用上述导航器件构成的组合导航系统不但定位精度低,甚至会影响AUV的制导与控制系统的稳定性。论文的前半部分主要就是针对小型AUV采用的导航器件上述问题展开研究。
首先在对MEMS惯性器件的确定性误差进行标定后,根据经典Allan方差技术,分别根据直接采样和交叠采样技术推导了递推Allan方差辨识算法,使得MEMS惯性器件随机误差参数的在线辨识成为可能。
然后运用时间序列分析技术建立了组合导航系统中相控阵Doppler测速仪的噪声模型,并借鉴S面控制算法提出了适用于小型AUV的Doppler测速仪的Kalman滤波器。
最后针对小型AUV采用的航姿参考系统中电子罗盘子系统需要进行自差校正的问题,提出了一种基于UT变换的强跟踪UKF算法,随之又改进了算法中渐消因子矩阵的计算方法,并又将噪声参数在线估计技术引入到该算法中,使得该算法不但自适应性好而且鲁棒性强,解决了小型AUV在海面进行自差校正时遇到的海浪干扰问题,提高了UKF算法对自差参数的辨识能力。
在随后的章节中,运用频域内连续信号的分解与重构技术,基于FFT算法提出了角速率输入下的频域姿态解算方案,并在Matlab仿真环境下实现了频域姿态解算方案,通过与四元数微分方程的四阶龙格-库塔求解方法相比,该算法能够有效减小载体做圆锥运动时姿态解算存在的圆锥误差,提高系统的姿态解算精度。
组合导航系统中电子罗盘子系统虽然精度较高,但在小型AUV运动过程中,往往会受到非重力加速度的干扰,导致其输出的航姿信息产生较大的跳变误差。而基于MEMS陀螺组件解算得到的航姿信息虽然不易受非重力加速度的干扰,却存在较大的积累误差。基于上述特点,采用自适应加权算法,将电子罗盘输出的航姿信息与基于MEMS陀螺组件解算得出的航姿信息相融合,平滑了电子罗盘输出的水平姿态角和航向角,提高了整个航姿系统的动态性能。
最后针对小型AUV的水下组合导航系统在海流干扰下存在模型误差的问题,提出了一种带模型误差的自适应UKF算法,该算法基于虚拟噪声的思想,利用次优MAP估值器对虚拟噪声的统计量进行实时估计,提高了小型AUV导航系统的定位精度和滤波能力。
The dissertation has investigated several key technologies of underwater integrated navigation system of small AUV (Autonomous Underwater Vehicles). They were devices error parameters identification technique and their noise filtering technique, attitude determination of AHRS (Attitude and Heading Reference System), and the fusion strategy of integrated navigation system.
Owing to restrictions on hull size and cost of small AUV, its integrated navigation system always adopts MEMS inertial devices, which have small volume, low cost and low power consumption, besides small, low power consumption Doppler velocity log. These navigation devices can meet the requirements of mechanical and electrical characteristics of small AUV, although they often have low accuracy. The integrated navigation system consists of these devices has poor performance, and even affects the small AUV's guidance and control system stability. The first half of dissertation focused on the above problems of the navigation equipment used by small AUV.
First of all, after calibrating deterministic error of MEMS inertial devices, Allan variance recursive identification algorithm was derived using overlapping and direct sampling technique respectively, founded on classic Allan variance identification technique, which made it possible to identify the parameters of random noise online for each MEMS navigation devices.
Then the noise model of phased-array Doppler velocity log adopted by small AUV's navigation system was built by time series analysis technique. Referencing the S plane control algorithm, the Kalman filter to Doppler velocity log was designed, suitable for the small AUV.
At last, strong tracking UKF algorithm based on unscented transformation was designed, using in the small AUV's compass calibration process. The strong tracking algorithm was introduced into UKF completely based on UT technique, and the algorithm of its fading factor matrix was improved, meanwhile estimator of noise parameters was also introduced into this algorithm, so that made the algorithm have good adaptability and robustness. The algorithm solved the wave interference problem, and improved the recognition ability of error parameters of UKF algorithm, when small AUV's compass calibrating on the sea surface.
In the following chapters, angular rate input attitude determination solution was designed based on FFT (Fast Fourier Transformation) algorithm, using continuous signal decomposition and reconstruction technique in frequency domain. The algorithm was programmed in Matlab and compared with the quaternion attitude determination solved by fourth order Runge-Kutta algorithm in time domain. The comparison showed that frequency domain algorithm can reduce the coning error effectively, and improve the accuracy of attitude determination.
Although the accuracy of electronic compass in integrated navigation system is higher, it is easily interfered by non-gravitational acceleration, causing jump error in output attitude signal. Meanwhile, the heading and attitude information solved by MEMS gyro unit is not easily spoiled by non-gravitational acceleration, but its accumulation error is large. Based on the above characteristics, the attitude information respectively solved by electronic compass and MEMS gyro unit was fused by adaptive weighted algorithm, so that the attitude and heading information by electronic compass was smoothed, and the dynamic performance of the whole AHRS was improved as well.
In the last part of this thesis, an adaptive UKF algorithm with model error was designed to reduce the navigation system model error caused by ocean current disturbance. Based on the idea of virtual noise, this algorithm used suboptimal MAP estimator to calculate statistics of virtual noise real time, which helped to improve the accuracy of navigation system and to enhance the ability of filtering.
引文
[1]封锡盛.从有缆遥控水下机器人到自治水下机器人[J].中国工程科学,2000,2(12)：29-33.
[2]李一平.水下机器人——过去、现在和未来[J].自动化博览,2002,19(3)：56-58.
[3]桑恩方,庞永杰,卞红雨.水下机器人技术[J].机器人技术与应用.2003,3：8-13.
[4]von Alt, C. REMUS 100 transportable mine countermeasure package[C]. Proceedings of OCEANS 2003 MTS/IEEE Conference and Exhibition,2003,1925-1930.
[5]Wright J, Scott K, Tien-Hsin Chao, Lau B, Lathrop J, Mc-Cormick J. Multi-sensor data fusion for seafloor mapping and ordnance location[C]. Proceedingds of the 1996 Symposium on Autonomous Underwater Vehicle Technology,1996,167-175.
[6]Asakawa K, Kojima J, Kato Y, Matsumoto S, Kato N. Autonomous underwater vehicle AQUA EXPLORER 2 for inspection of underwater cables[C]. Proceedingds of the 2000 International Symposium on Underwater Technology,2000,242-247.
[7]Goodman L, Wang Z. Turbulence observations in the northern bight of Monterey Bay from a small AUV[J]. Journal of Marine Systems,2009,77(4):441-458.
[8]Williams S B, Pizarro O, How M, Mercer D, Powell G, Marshall J, Hanlon R. Surveying noctural cuttlesh camouage behaviour using an AUV[C]. Proceedingds of 2009 IEEE International Conference on Robotics and Automation,2009,214-219.
[9]Camilli R, Bingham B S, Jakuba M V, Duryea A N, Lebouvier R, Dock M. AUV sensors for real-time detection, localization, characterization, and monitoring of underwater munitions[J]. Marine Technology Society Journal,2009,43(4):76-84.
[10]Vaganay J, Elkins M, Esposito D, O'Halloran W, HoverF, Kokko M. Ship hull inspection with the HAUV:US navy and NATO demonstrations results[C]. Proceedings of OCEAN 2007 MTS/IEEE Conference and Exhibition,2007,761-766.
[11]Desa E, Madhan R, Maurya P, Navelkar G, Mascarenhas A, Prabhudesai S, et al. The detection of annual hypoxia in a low latitude freshwater reservoir in Kerala, India, using the small AUV Maya[J]. Marine Technology Society Journal,2009,43(3):60-70.
[12]徐玉如,苏玉民.关于发展智能水下机器人技术的思考[J].舰船科学技术,2008,30(4)：17-21.
[13]马伟锋,胡震.AUV的研究现状与发展趋势[J].火力与指挥控制,2008,33(6)：10-13.
[14]佟盛.AUV导航系统及技术发展[C].中国造船工程学会2006年船舶通讯导航学术会议,2006.241-244.
[15]李俊,徐德民,宋保维,严卫生.自主式水下机器人导航技术发展现状与展望[J].中国造船,2004,25(3)：70-77.
[16]Edgar An. A Comparison of AUV Navigation Performance:A System Approach[C]. Proceedings of OCEANS 2003 MTS/IEEE Conference and Exhibition,2003.654-662.
[17]Crowell, J. Small AUV for Hydrographic Applications[C]. Proceedings of OCEANS 2006 MTS/IEEE Conference and Exhibition,2006.1-6.
[18]Earle, M.D., Borgman, L.E., Mettlach, T.R.. Ocean surface wave measurements using a small autonomous underwater vehicle[C]. Proceedings of OCEANS 2002 MTS/IEEE Conference and Exhibition,2002.272-276.
[19]Crimmins, D., Deacutis, C., Hinchey, E., Chintala, M., Cicchetti, G., Blidberg, D.. Use of a long endurance solar powered autonomous underwater vehicle (SAUV Ⅱ) to measure dissolved oxygen concentrations in Greenwich Bay[C]. Proceedings of OCEANS 2005 MTS/IEEE Conference and Exhibition,2005.896-901.
[20]Tetlow, S., Allwood, R.L.. Develop and applications of a novel underwater laser illumination system[J]. Underwater Technology:The International Journal of the Society for Underwater,1995,21(2):13-20.
[21]Dalgleish, F.R.. Applications of laser-assisted vision to autonomous underwater vehicle navigation[D].2004, Cranfield University, Cranfield, UK.
[22]Loebis, D., Dalgleish, F.R., R. Sutton, S. Tetlow, J. Chudley, R. Allwood. An integrated approach in the design of navigation system for an AUV[C]. Proceedings of MCMC 2003 Conference,2003.329-334.
[23]Larsen, M.B.. High performance doppler-inertial navigation-experimental results[C]. Proceedings of OCEANS 2000 MTS/IEEE Conference and Exhibition,2000. 1559-1456.
[24]Ura, T., Kumagai, M., Sakskibara, T., Kimura, Y., Okumura, T., Shibasawa, K., Sasaki, M., Matsushima, M. Construction and Operation of Four Autonomous Underwater Vehicles for Lake Survey[C]. Proceedings of UT02/IEEE,2002.24-29.
[25]Maki, T., Kondo, H., Ura, T., Sakamaki, T.. Positioning method for an AUV using a profiling sonar and passive acoustic landmarks for close-range observation of seafloors[C]. Proceedings of OCEANS 2007 MTS/IEEE Conference and Exhibition, 2007.1-6.
[26]Hayato Kondo, Toshihiro Maki, Tamaki Ura, Takashi Sakamaki. AUV Navigation Based on Multi-Sensor Fusion for Breakwater Observation[C]. Proceedings of the 23rd ISARC, 2006.72-77.
[27]梁建宏,邹丹,王松,王野.SP-Ⅱ机器鱼平台及其自主航行实验[J].北京航空航天大学学报,2005,31(7)：709-713.
[28]吴宝举,李硕,李一平,王晓辉.小型自治水下机器人运动控制系统研究[J].机械设计与制造,2010,6：158-160.
[29]苏玉民,万磊,李哗,庞永杰,秦再白.舵桨联合操纵微小型水下机器人的开发[J].机器人,2007,29(2)：51-154.
[30]Hayato Kondo, Tamaki Ura. Navigation of an AUV for investigation of underwater structures[J]. Control Engineering Practice,2004,12(12):1551-1559.
[31]Yanrui Geng, Martins, R., Sousa, J.. Accuracy Analysis of DVL/IMU/Magnetometer Integrated Navigation System using Different IMUs in AUV[C]. Proceedings of the 2010 8th IEEE International Conference on Control and Automation (ICCA),2010.516-521.
[32]顾颖玲,许江宁,卞鸿威.陀螺随机漂移误差模型建模方法研究[J].海军工程大学学报,2000(1)：80-82.
[33]张研顺,房建成.小型动调陀螺随机误差建模与滤波方法研究[J].仪器仪表学报,2007(7)：1286-1289.
[34]吉训生,王寿荣MEMS陀螺仪随机漂移误差研究[J].宇航学报.2006,27(4)：640-642.
[35]D. W. Allan. Statistics of atomic frequency standards[C]. Proceedings of IEEE.1966, 54(2):221-230.
[36]IEEE STD 952-1997. IEEE standard specification format guide and test procedure for single-axis interferometric fiber optic gyros[S]. IEEE Sandard Board.1997.
[37]李迪,孙尧,李绪友等.船用光纤陀螺随机漂移分析与研究[J].中国航海.2005(1)：35-37.
[38]李晓莹,胡敏,张鹏等.交叠式Allan方差在微机械陀螺随机误差辨识中的应用[J].西北工业大学学报.2007,25(2)：225-229.
[39]Savage P G. Strap-down inertial navigation integration algorithm design part 1:attitude algorithms[J]. Journal of Guidance,Control, and Dynamics.1998,21(1):19-28.
[40]Savage, P. G.. A New Second-Order Solution for Strapped-Down Attitude Computation[C]. Proceedings of AIAA/JACC Guidance and Control Conference,1966.
[41]J. W. Jordan, An accurate strapdown direction cosine algorithm[R], NASA TN-D-5384, 1969.
[42]J. E. Bortz, A new mathematical formulation for strapdown inertial navigation[J]. IEEE Transactions on Aerospace and Electronic Systems.1971,7(1):61-66.
[43]R. Miller, Anew strapdown attitude algorithm[J]. Journal of Guidance, Control, and Dynamics.1983,6(4):287-291.
[44]V. Z. Gusinsky, V. M. Lesyuchevsky, Y. A. Litmanovich, H. Musoff, G. T. Schmidt. New procedure for deriving optimized strapdown attitude algorithm[J]. Journal of Guidance, Control, and Dynamics.1997,44(2):163-170.
[45]J. G. Lee, Y. J. Yoon, M. J. G, D. A. Tazartes. Extension of strapdown attitude algorithm for high frequency bade motion[J]. Journal of Guidance, Control, and Dynamics,1990, 13(4):738-743.
[46]M. B. Ignagni. Optimal strapdown attitude integration algorithms[J]. Journal of Guidance, Control, and Dynamics.1990,13(2):363-369.
[47]Y. F. Jiang, Y. P. Lin, Improved strapdown coning algorithms [J]. IEEE Transactions on Aerospace and Electronic Systems,1992,28:484-489.
[48]J. G. Mark, D. A. Tazartes. On sculling algorithms[C]. Proceedings of the 3rd St. Petersburg International Conference on Integrated Navigation Systems, Central Scientific and Research Institute "Elektropribor",1996.
[49]A. Solovev. Investigation into performance enhancement of integrated global positioning/inertial navigation systems by frequency domain implementation of inertial computational procedures[D]. Ohio University,2002.
[50]武元新.对偶四元数导航算法与非线性高斯滤波研究[D].国防科学技术大学博士研究生学位论文.2005.
[51]R. E. Kalman, A new approach to linear filtering and prediction problems[J]. Transactions of the ASME-Journal of Basic Engineering,1960,82(D):35-45.
[52]H. Tanizaki, R. S. Mariano, Nonlinear filters based on Taylor series expansion. Commu. Statist[J]. Theory and Methods,1996,25(6):1261-1282.
[53]S. J. Julier, J. Uhlmann. A new extension of the Kalman filter to nonlinear system[C]. Signal Processing, Sensor Fusion, and Target Recognition IT, vol.3068, Proceedings of the Society of Photo-Optical Instrumentation Engineers(SPIE),1997,182-193.
[54]M. S. Arulampalam, S. Maskell, N. Gordon, T. Clapp, A tutorial on paricle filters for online nonlinear/non-Gaussian Bayesian tracking[J]. IEEE Transactions on Signal Processing,2002,50(2):174-188.
[55]B. F. L. Scala, R. R. Bitmead, M. R. James. Conditions for stability of the extended Kalman filter and their application to the frequency tracking problem[J]. Mathematics of Control, Signals, and Systems,1995,8:1-26.
[56]K. Reif, S. Gunther, E. Yaz, R. Unbehauen. Stochastic stability of the discrete-time extended Kalman filter[J]. IEEE Transactions on Automatic Control,1999,44(4): 714-728.
[57]K. Reif, S. Gunther, E. Yaz, R. Unbehauen. Stochastic stability of the continuous-time extended Kalman filter[C]. IEE Proceeding Control Theory Application,2000,147(1): 45-52.
[58]S. J. Julier, J. Uhlmann. Unscented filtering and nonlinear estimation[C]. Proceedings of the IEEE,2004,92(3):401-422.
[59]M. Norgaard, N. K. Poulsen, O. Ravn. New developments in state estimation for nonlinear systems[J]. Automatica,2000,36(11):1627-1638.
[60]K. Ito, K. Q. Xiong. Gaussian filters for nonlinear filtering problems[J]. IEEE Transactions on Automatic Control,2000,45(5):910-927.
[61]S. Julier, J. Uhlmann, H. F. K Durrant-Whyte. A new method for the nonlinear transformation of means and covariances in filters and estimators[J]. IEEE Transactions on Automatic Control,2000,45(3):477-482.
[62]R. van der Merwe, Wan E. The Efficient derivative-free Kalman filters for online learning[C]. Proceedings of the European Symposium on Artificial Neural Networks Bruges (Belgium),2001.205-210.
[63]R van der Merwe. Sigma-point Kalman filters for probabilistic inference in dynamic state-space models[D]. Oregon Health Science University,2004.
[64]Arasaratnam I, Haykin S, Elliott R J, Discrete-time nonlinear filtering algorithm using Gauss-Hermite quadrature[C]. Proceedings of the IEEE,2007,95(3):953-977.
[65]A. J. Haug. A Tutorial on Bayesian Estimation and Tracking Techniques Applicable to Nonlinear and Non-Gaussian Processes[R]. the MITRE Corporation, USA, Technique report 2005.
[66]A. F. M. Smith, A. E. Gelfand. Bayesian statistics without tears:a sampling-resampling perspective[J]. The American Statistician,1992,46(2):84-88.
[67]Carpenter, J., Clifford, P., Fearnhead, P.. Improved particle filter for nonlinear problems[C]. Proceedings of the IEE Proceedings Radar, Sonar and Navigation,1999, 146(1):2-7.
[68]Y. C. Ho, R. C. K. Lee. A Bayesian approach to problems in stochastic estimation and control[J]. IEEE Transactions on Automatic Control,1964, AC(9):333-339.
[69]Merwe R. V. D., Wan E. A.. Sigma-Point Kalman Filters for Integrated Navigation[C]. Proceedings of the 60th Annual Meeting of the Institute of Navigation (ION),2004: 641-654.
[70]J.L. Crassidis. Sigma-Point Kalman Filtering for Integrated GPS and Inertial Navigation[J]. IEEE Transactions on Aerospace and Electronic Systems,2005,42(2): 750-756.
[71]Rezaie J, Moshiri, B, Araabi B N, Asadian A. GPS/INS integration using nonlinear blending filters[C]. Proceedings of the 2007 Annual Conference,2007:1674-1680.
[72]R. Karlsson, Particle Filtering for Positioning and Tracking Applications[D]. Linkoping University,2005.
[73]A. Doucet, S. Godsill, and C. Andrieu. On sequential Monte Carlo sampling methods for Bayesian filtering[J]. Statistics and Computing,2000,10(3):197-208.
[74]陈哲著.捷联惯导系统原理[M].北京：宇航出版社,1986.
[75]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.导航与航天运载技术[J].2001,3：23-27.
[76]Richard R. Harman, Itzhack Y. Bar-Itzhack. Implicit and Explicit Spacecraft Gyro Calibration[C]. Proceedings of the AIAA Guidance, Navigation and Control Conference and Exhibit.,2004, vol.5343.
[77]宋丽君,秦永元.微机电加速度计的六位置标定[J].传感技术学报.2009,22(11)：1557-1561.
[78]宋丽君,秦永元MEMS加速度计的六位置测试法[J].测控技术.2009,28(7)：11-17.
[79]David A. Howe, Dnald B. Percival. Wavelet variance, Allan variance, and leakage[J]. IEEE Trans. on Instrumentation and Measurement.1995,44(2):94-97.
[80]史锦顺.方差的新概念——兼论阿仑方差[J].电光系统.2001,16(1)：1-10.
[81]史锦顺.测量精度的新概念[J].电光系统.2003,18(3)：3-7.
[82]Hanspeter Schaub, John L. Junkins. Stereographic orientation parameters for attitude dynamics:a generalization of the Rodrigues parameters[J]. Journal of the Astronautical Sciences.1996,44(1):1-19.
[83]李战,冀邦杰,国琳娜.光纤陀螺漂移信号的Allan方差分析[J].光电子·激光.2008,19(2)：183-186.
[84]徐怀明,王建,帅必晖等.利用分段回归拟合激光陀螺仪零偏测试的Allan方差[J].光学技术.2007,33(6)：867-869.
[85]Hou H, El-Sheimy N.. Inertial Sensors Errors Modeling Using Allan Variance[C]. Proceedings of the 16th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GPS/GNSS 2003),2003:2860-2867.
[86]Quang M. Lam, Nick Stamatakos, Craig Woodruff et al. Gyro modeling and estimation of its random noise sources[C]. Proceedings of the 16th AIAA Guidance Navigation and Control Conference and Exhibit.2003, vol.8.
[87]H. Hou, N. El-Sheimy. Inertial Sensors Errors Modeling Using Allan Variance[C]. Proceedings of the 16th International Technical Meeting of the Satellite Division of the Institute of Navigation ION GPS/GNSS.2003:2860-2867.
[88]倪静静,王俊璞,卫炎等.三轴一体化光纤陀螺的Allan方差分析[J].光学仪器.2007,29(1)：57-61.
[89]刘付强.基于MEMS器件的捷联姿态测量系统技术研究[D].哈尔滨工程大学博士研究生学位论文.2007.
[90]Ferre-Pikal E. S., Vig J. R., Camparo J. C., Draft Revision of IEEE Std 1139-1988 Standard Definitions of Physical Quantities for Fundamental Frequency and Time Metrology-Random Instabilities[C]. Proceedings of the IEEE Frequency Control Symposium,1997:338-357.
[91]IEEE Std 1139-1988, IEEE Standard Definitions of Physical Quantities for Fundamental Frequency and Time Metrology[S].
[92]IEEE Std 1293-1998 IEEE Standard Specification Format Guide and Test Procedure for Linear, Single-Axis, Non-gyroscopic Accelerometers[S].
[93]H. Hou, Modeling Inertial Sensors Errors Using Allan Variance[D]. University of Calgary,2004.
[94]卢逢春,张殿伦,田坦.相控阵多普勒计程仪的相控波束接收方案[J].应用声学.2002,21(4)：6-9.
[95]张殿伦,卢逢春,田坦等.相控阵多普勒计程仪声基阵输出信号模型[J].应用声学.2003,22(5)：21-24页.
[96]田坦,张殿伦,卢逢春等.相控阵多普勒测速技术研究.哈尔滨工程大学学报.2002,23(1)：80-85.
[97]陈刚,高贤志,赵汪洋.基于小波变换的多普勒声纳数据处理研究[J].传感器与微系统,2006,25(12)：9-11.
[98]Cardarelli, D.. An integrated MEMS inertial measurement unit[C]. Proceedings of the IEEE Position Location and Navigation Symposium.2002,314-319.
[99]吉训生,王寿荣,许宜申.自适应Kalman滤波在MEMS陀螺仪信号处理中的应用. 传感器与微系统[J].2006,25(9)：330-334.
[100]Zhang Hua, Ke Xizheng, Jiao Rong. Experimental Research on Feedback Kalman Model of MEMS Gyroscope[C]. Proceedings of the Eighth International Conference on Electronic Measurement and Instruments,2007.253-256P.
[101]刘学敏,徐玉如.水下机器人运动的S面控制方法[J].海洋工程.2001,19(3)：81-84.
[102]刘建成,于华男,徐玉如.水下机器人改进的S面控制方法[J].哈尔滨工程大学学报.2002,23(1)：33-36.
[103]Berg R.. Estimation and prediction for maneuvering target trajectories[J]. IEEE Transactions on Automatic Control.1983,28(3):294-304.
[104]Platil A., Kubik J., Vopalensky M., et al. Precise AMR Magnetometer for Compass[C]. Proceedings of IEEE Sensors,2003.461-472P.
[105]安振昌.区域和全球地磁场模型[J].地球物理学进展.1995,3：63-72.
[106]安振昌.地磁场模型的计算和评述[J].地球科学进展.1993,4：45-48.
[107]熊剑,刘建业,孙永荣等.数字磁罗盘的研制[J].传感器技术.2004,23(8)：46-51.
[108]Shibin Liu, Jiaming Yan, Xiren Sun. Magnetic deviation compensation for UAV's heading measurement[J]. Acta Aeronautica et Astronautic Sinica.2000,21(1):78-80.
[109]Pengfei Guo, Zhang Ren, Haitao Qiu, Xinchun Ding. Twelve-position calibrating method without north reference for magnetic compass[J]. Journal of Chinese Inertial Technology.2007,15(5):598-601.
[110]Jing Zhang, Zhihua Jin, Weifeng Tian. Deviation calibrating for digital magnetic compass without heading reference[J]. Journal of Shanghai Jiaotong University.2004, 38(10):1757-1760.
[111]K. L. Lai, J. L. Crassidis, R. R. Harman. Real-time-attitude-independent three-axis magnetometer calibration[J]. Journal of Guidance, Control and Dynamics.2005,28(1): 115-120.
[112]王小旭,赵琳,夏全喜等.基于Unscented变换的强跟踪滤波器[J].控制与决策.2010,25(7)：1063-1068.
[113]葛哲学,杨拥民,温熙森.强跟踪UKF方法及其在故障辨识中的应用[J].仪器仪表学报.2008,29(8)：1670-1674.
[114]陆海勇,赵伟,熊剑等.强跟踪UKF滤波在SINS/GPS组合导航中的应用研究[J].航空电子技术.2008,39(4)：5-10.
[115]范利涛.自动转移飞行器自主导航方法研究[D].国防科学技术大学博士研究生学位论文.2009.
[116]周东华,席裕庚,张钟俊.一种带多重次优渐消因子的扩展卡尔曼滤波器[J].自动化学报.1991,17(6)：689-695页.
[117]周东华,席裕庚,张钟俊.非线性系统的带次优渐消因子的扩展卡尔曼滤波[J],控制与决策.1990,5(5)：1-6页.
[118]周东华.一类非线性系统故障检测与诊断的滤波器方法[D].上海交通大学博士研究生学位论文.1990.
[119]J. Eyre J. Bier. The Eolution of DSP Processors[J]. IEEE Signal Processing Magazine. 2000(17):43-51.
[120]牛海燕.基于DSP的捷联惯导系统设计[J].仪器仪表学报.2004,25(4)：214-216.
[121]孙志坚,刘学海,王玉辉.浮点DSP+FPGA在组合惯导系统中的应用[J].弹箭与制导学报.2005,25(3)：119-121.
[122]曾鸣,冯建鑫,于志伟.基于角速度频域重构的旋转矢量解算[J].中国惯性技术学报.2008,16(2)：144-147.
[123]朱威,张明,吴文启.捷联惯性导航频域算法的仿真研究[J].系统仿真技术及其应用.2006,9：75-77.
[124]岳达,吴第旻,王正志.基于离散傅里叶变换的姿态算法研究[J].计算机仿真.2010,7：21-24.
[125]高清维,程蒲,张道信.基于对称延拓的DFT频谱泄露抑制方法[J].安徽大学学报(自然科学版).2000,24(2)：30-35.
[126]钟佑明,秦树人,汤宝平.关于DFT中的延拓原理及计算结果物理意义的一些讨论[J].震动与冲击.2001,20(4)：1-3.
[127]纪跃波,秦树人,柏林等.有限区间信号边界效应问题的研究[J].震动与冲击.2002,21(4)：108-112.
[128]钟佑明,汤宝平,秦树人.离散傅里叶变换(DFT)计算中一些问题的论证[J].重庆大学学报(自然科学版).2001,24(3)：1-4.
[129]杨金显.微惯性测量系统关键技术研究[D].哈尔滨工程大学博士研究生学位论文.2008.
[130]黄昊,邓正隆.角速率输入下的航姿算法研究[J].中国惯性技术学报.2000,8(2)：21-26.
[131]A. Gadre, D. Stilwell. Toward underwater navigation based on range measurements from a single location[C]. Proceedings of the IEEE International Conference on Robotics and Automation,2004,4472-4477.
[132]D. Loebis, R. Sutton, J. Chudley. Adaptive tuning of a Kalman filter via fuzzy logic for an intelligent AUV navigation system[J]. Control Engineering Practice.2004,12: 1531-1539.
[133]Lefebvre T., Bruyninckx H., J. De Schutter. Comment on A new method for the nonlinear transformation of mean and covariances in filters and estimation [J]. IEEE Trans. Automat. Contr..2002,47(8):1406-1408.
[134]Tenne D, Singh T. The higher order unscented filter[C]. Control Conference,2003, 2441-2446.
[135]Loebis D., Naeem W., Sutton R.etc.. Navigation, guidance and control of the Hammerhead autonomous vehicle[J]. Advances in unmanned marine vehicles, IEE Control Series, IEE Press,2005.
[136]Demoz Gebre-Egziabher, Roger C. Hayward, J. David Powell. Design of Multi-Sensor Attitude Determination Systems[J]. IEEE Trans. on aerospace and electronic systems. 200440(2):627-649.
[137]Gao Zhong-yu, Niu Xiao-ji, Guo Mei-feng. Quaternion-Based Kalman Filter for Micro-machined Strapdown Attitude Heading Reference System[J]. CHINESE JOURNAL OF AERONAUTICS.2002,15(3):171-175.
[138]邓自立,王建国.非线性系统的自适应推广的Kalman滤波[J].自动化学报,1987,13(5)：375-379.
[2]李一平.水下机器人——过去、现在和未来[J].自动化博览,2002,19(3)：56-58.
[3]桑恩方,庞永杰,卞红雨.水下机器人技术[J].机器人技术与应用.2003,3：8-13.
[4]von Alt, C. REMUS 100 transportable mine countermeasure package[C]. Proceedings of OCEANS 2003 MTS/IEEE Conference and Exhibition,2003,1925-1930.
[5]Wright J, Scott K, Tien-Hsin Chao, Lau B, Lathrop J, Mc-Cormick J. Multi-sensor data fusion for seafloor mapping and ordnance location[C]. Proceedingds of the 1996 Symposium on Autonomous Underwater Vehicle Technology,1996,167-175.
[6]Asakawa K, Kojima J, Kato Y, Matsumoto S, Kato N. Autonomous underwater vehicle AQUA EXPLORER 2 for inspection of underwater cables[C]. Proceedingds of the 2000 International Symposium on Underwater Technology,2000,242-247.
[7]Goodman L, Wang Z. Turbulence observations in the northern bight of Monterey Bay from a small AUV[J]. Journal of Marine Systems,2009,77(4):441-458.
[8]Williams S B, Pizarro O, How M, Mercer D, Powell G, Marshall J, Hanlon R. Surveying noctural cuttlesh camouage behaviour using an AUV[C]. Proceedingds of 2009 IEEE International Conference on Robotics and Automation,2009,214-219.
[9]Camilli R, Bingham B S, Jakuba M V, Duryea A N, Lebouvier R, Dock M. AUV sensors for real-time detection, localization, characterization, and monitoring of underwater munitions[J]. Marine Technology Society Journal,2009,43(4):76-84.
[10]Vaganay J, Elkins M, Esposito D, O'Halloran W, HoverF, Kokko M. Ship hull inspection with the HAUV:US navy and NATO demonstrations results[C]. Proceedings of OCEAN 2007 MTS/IEEE Conference and Exhibition,2007,761-766.
[11]Desa E, Madhan R, Maurya P, Navelkar G, Mascarenhas A, Prabhudesai S, et al. The detection of annual hypoxia in a low latitude freshwater reservoir in Kerala, India, using the small AUV Maya[J]. Marine Technology Society Journal,2009,43(3):60-70.
[12]徐玉如,苏玉民.关于发展智能水下机器人技术的思考[J].舰船科学技术,2008,30(4)：17-21.
[13]马伟锋,胡震.AUV的研究现状与发展趋势[J].火力与指挥控制,2008,33(6)：10-13.
[14]佟盛.AUV导航系统及技术发展[C].中国造船工程学会2006年船舶通讯导航学术会议,2006.241-244.
[15]李俊,徐德民,宋保维,严卫生.自主式水下机器人导航技术发展现状与展望[J].中国造船,2004,25(3)：70-77.
[16]Edgar An. A Comparison of AUV Navigation Performance:A System Approach[C]. Proceedings of OCEANS 2003 MTS/IEEE Conference and Exhibition,2003.654-662.
[17]Crowell, J. Small AUV for Hydrographic Applications[C]. Proceedings of OCEANS 2006 MTS/IEEE Conference and Exhibition,2006.1-6.
[18]Earle, M.D., Borgman, L.E., Mettlach, T.R.. Ocean surface wave measurements using a small autonomous underwater vehicle[C]. Proceedings of OCEANS 2002 MTS/IEEE Conference and Exhibition,2002.272-276.
[19]Crimmins, D., Deacutis, C., Hinchey, E., Chintala, M., Cicchetti, G., Blidberg, D.. Use of a long endurance solar powered autonomous underwater vehicle (SAUV Ⅱ) to measure dissolved oxygen concentrations in Greenwich Bay[C]. Proceedings of OCEANS 2005 MTS/IEEE Conference and Exhibition,2005.896-901.
[20]Tetlow, S., Allwood, R.L.. Develop and applications of a novel underwater laser illumination system[J]. Underwater Technology:The International Journal of the Society for Underwater,1995,21(2):13-20.
[21]Dalgleish, F.R.. Applications of laser-assisted vision to autonomous underwater vehicle navigation[D].2004, Cranfield University, Cranfield, UK.
[22]Loebis, D., Dalgleish, F.R., R. Sutton, S. Tetlow, J. Chudley, R. Allwood. An integrated approach in the design of navigation system for an AUV[C]. Proceedings of MCMC 2003 Conference,2003.329-334.
[23]Larsen, M.B.. High performance doppler-inertial navigation-experimental results[C]. Proceedings of OCEANS 2000 MTS/IEEE Conference and Exhibition,2000. 1559-1456.
[24]Ura, T., Kumagai, M., Sakskibara, T., Kimura, Y., Okumura, T., Shibasawa, K., Sasaki, M., Matsushima, M. Construction and Operation of Four Autonomous Underwater Vehicles for Lake Survey[C]. Proceedings of UT02/IEEE,2002.24-29.
[25]Maki, T., Kondo, H., Ura, T., Sakamaki, T.. Positioning method for an AUV using a profiling sonar and passive acoustic landmarks for close-range observation of seafloors[C]. Proceedings of OCEANS 2007 MTS/IEEE Conference and Exhibition, 2007.1-6.
[26]Hayato Kondo, Toshihiro Maki, Tamaki Ura, Takashi Sakamaki. AUV Navigation Based on Multi-Sensor Fusion for Breakwater Observation[C]. Proceedings of the 23rd ISARC, 2006.72-77.
[27]梁建宏,邹丹,王松,王野.SP-Ⅱ机器鱼平台及其自主航行实验[J].北京航空航天大学学报,2005,31(7)：709-713.
[28]吴宝举,李硕,李一平,王晓辉.小型自治水下机器人运动控制系统研究[J].机械设计与制造,2010,6：158-160.
[29]苏玉民,万磊,李哗,庞永杰,秦再白.舵桨联合操纵微小型水下机器人的开发[J].机器人,2007,29(2)：51-154.
[30]Hayato Kondo, Tamaki Ura. Navigation of an AUV for investigation of underwater structures[J]. Control Engineering Practice,2004,12(12):1551-1559.
[31]Yanrui Geng, Martins, R., Sousa, J.. Accuracy Analysis of DVL/IMU/Magnetometer Integrated Navigation System using Different IMUs in AUV[C]. Proceedings of the 2010 8th IEEE International Conference on Control and Automation (ICCA),2010.516-521.
[32]顾颖玲,许江宁,卞鸿威.陀螺随机漂移误差模型建模方法研究[J].海军工程大学学报,2000(1)：80-82.
[33]张研顺,房建成.小型动调陀螺随机误差建模与滤波方法研究[J].仪器仪表学报,2007(7)：1286-1289.
[34]吉训生,王寿荣MEMS陀螺仪随机漂移误差研究[J].宇航学报.2006,27(4)：640-642.
[35]D. W. Allan. Statistics of atomic frequency standards[C]. Proceedings of IEEE.1966, 54(2):221-230.
[36]IEEE STD 952-1997. IEEE standard specification format guide and test procedure for single-axis interferometric fiber optic gyros[S]. IEEE Sandard Board.1997.
[37]李迪,孙尧,李绪友等.船用光纤陀螺随机漂移分析与研究[J].中国航海.2005(1)：35-37.
[38]李晓莹,胡敏,张鹏等.交叠式Allan方差在微机械陀螺随机误差辨识中的应用[J].西北工业大学学报.2007,25(2)：225-229.
[39]Savage P G. Strap-down inertial navigation integration algorithm design part 1:attitude algorithms[J]. Journal of Guidance,Control, and Dynamics.1998,21(1):19-28.
[40]Savage, P. G.. A New Second-Order Solution for Strapped-Down Attitude Computation[C]. Proceedings of AIAA/JACC Guidance and Control Conference,1966.
[41]J. W. Jordan, An accurate strapdown direction cosine algorithm[R], NASA TN-D-5384, 1969.
[42]J. E. Bortz, A new mathematical formulation for strapdown inertial navigation[J]. IEEE Transactions on Aerospace and Electronic Systems.1971,7(1):61-66.
[43]R. Miller, Anew strapdown attitude algorithm[J]. Journal of Guidance, Control, and Dynamics.1983,6(4):287-291.
[44]V. Z. Gusinsky, V. M. Lesyuchevsky, Y. A. Litmanovich, H. Musoff, G. T. Schmidt. New procedure for deriving optimized strapdown attitude algorithm[J]. Journal of Guidance, Control, and Dynamics.1997,44(2):163-170.
[45]J. G. Lee, Y. J. Yoon, M. J. G, D. A. Tazartes. Extension of strapdown attitude algorithm for high frequency bade motion[J]. Journal of Guidance, Control, and Dynamics,1990, 13(4):738-743.
[46]M. B. Ignagni. Optimal strapdown attitude integration algorithms[J]. Journal of Guidance, Control, and Dynamics.1990,13(2):363-369.
[47]Y. F. Jiang, Y. P. Lin, Improved strapdown coning algorithms [J]. IEEE Transactions on Aerospace and Electronic Systems,1992,28:484-489.
[48]J. G. Mark, D. A. Tazartes. On sculling algorithms[C]. Proceedings of the 3rd St. Petersburg International Conference on Integrated Navigation Systems, Central Scientific and Research Institute "Elektropribor",1996.
[49]A. Solovev. Investigation into performance enhancement of integrated global positioning/inertial navigation systems by frequency domain implementation of inertial computational procedures[D]. Ohio University,2002.
[50]武元新.对偶四元数导航算法与非线性高斯滤波研究[D].国防科学技术大学博士研究生学位论文.2005.
[51]R. E. Kalman, A new approach to linear filtering and prediction problems[J]. Transactions of the ASME-Journal of Basic Engineering,1960,82(D):35-45.
[52]H. Tanizaki, R. S. Mariano, Nonlinear filters based on Taylor series expansion. Commu. Statist[J]. Theory and Methods,1996,25(6):1261-1282.
[53]S. J. Julier, J. Uhlmann. A new extension of the Kalman filter to nonlinear system[C]. Signal Processing, Sensor Fusion, and Target Recognition IT, vol.3068, Proceedings of the Society of Photo-Optical Instrumentation Engineers(SPIE),1997,182-193.
[54]M. S. Arulampalam, S. Maskell, N. Gordon, T. Clapp, A tutorial on paricle filters for online nonlinear/non-Gaussian Bayesian tracking[J]. IEEE Transactions on Signal Processing,2002,50(2):174-188.
[55]B. F. L. Scala, R. R. Bitmead, M. R. James. Conditions for stability of the extended Kalman filter and their application to the frequency tracking problem[J]. Mathematics of Control, Signals, and Systems,1995,8:1-26.
[56]K. Reif, S. Gunther, E. Yaz, R. Unbehauen. Stochastic stability of the discrete-time extended Kalman filter[J]. IEEE Transactions on Automatic Control,1999,44(4): 714-728.
[57]K. Reif, S. Gunther, E. Yaz, R. Unbehauen. Stochastic stability of the continuous-time extended Kalman filter[C]. IEE Proceeding Control Theory Application,2000,147(1): 45-52.
[58]S. J. Julier, J. Uhlmann. Unscented filtering and nonlinear estimation[C]. Proceedings of the IEEE,2004,92(3):401-422.
[59]M. Norgaard, N. K. Poulsen, O. Ravn. New developments in state estimation for nonlinear systems[J]. Automatica,2000,36(11):1627-1638.
[60]K. Ito, K. Q. Xiong. Gaussian filters for nonlinear filtering problems[J]. IEEE Transactions on Automatic Control,2000,45(5):910-927.
[61]S. Julier, J. Uhlmann, H. F. K Durrant-Whyte. A new method for the nonlinear transformation of means and covariances in filters and estimators[J]. IEEE Transactions on Automatic Control,2000,45(3):477-482.
[62]R. van der Merwe, Wan E. The Efficient derivative-free Kalman filters for online learning[C]. Proceedings of the European Symposium on Artificial Neural Networks Bruges (Belgium),2001.205-210.
[63]R van der Merwe. Sigma-point Kalman filters for probabilistic inference in dynamic state-space models[D]. Oregon Health Science University,2004.
[64]Arasaratnam I, Haykin S, Elliott R J, Discrete-time nonlinear filtering algorithm using Gauss-Hermite quadrature[C]. Proceedings of the IEEE,2007,95(3):953-977.
[65]A. J. Haug. A Tutorial on Bayesian Estimation and Tracking Techniques Applicable to Nonlinear and Non-Gaussian Processes[R]. the MITRE Corporation, USA, Technique report 2005.
[66]A. F. M. Smith, A. E. Gelfand. Bayesian statistics without tears:a sampling-resampling perspective[J]. The American Statistician,1992,46(2):84-88.
[67]Carpenter, J., Clifford, P., Fearnhead, P.. Improved particle filter for nonlinear problems[C]. Proceedings of the IEE Proceedings Radar, Sonar and Navigation,1999, 146(1):2-7.
[68]Y. C. Ho, R. C. K. Lee. A Bayesian approach to problems in stochastic estimation and control[J]. IEEE Transactions on Automatic Control,1964, AC(9):333-339.
[69]Merwe R. V. D., Wan E. A.. Sigma-Point Kalman Filters for Integrated Navigation[C]. Proceedings of the 60th Annual Meeting of the Institute of Navigation (ION),2004: 641-654.
[70]J.L. Crassidis. Sigma-Point Kalman Filtering for Integrated GPS and Inertial Navigation[J]. IEEE Transactions on Aerospace and Electronic Systems,2005,42(2): 750-756.
[71]Rezaie J, Moshiri, B, Araabi B N, Asadian A. GPS/INS integration using nonlinear blending filters[C]. Proceedings of the 2007 Annual Conference,2007:1674-1680.
[72]R. Karlsson, Particle Filtering for Positioning and Tracking Applications[D]. Linkoping University,2005.
[73]A. Doucet, S. Godsill, and C. Andrieu. On sequential Monte Carlo sampling methods for Bayesian filtering[J]. Statistics and Computing,2000,10(3):197-208.
[74]陈哲著.捷联惯导系统原理[M].北京：宇航出版社,1986.
[75]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.导航与航天运载技术[J].2001,3：23-27.
[76]Richard R. Harman, Itzhack Y. Bar-Itzhack. Implicit and Explicit Spacecraft Gyro Calibration[C]. Proceedings of the AIAA Guidance, Navigation and Control Conference and Exhibit.,2004, vol.5343.
[77]宋丽君,秦永元.微机电加速度计的六位置标定[J].传感技术学报.2009,22(11)：1557-1561.
[78]宋丽君,秦永元MEMS加速度计的六位置测试法[J].测控技术.2009,28(7)：11-17.
[79]David A. Howe, Dnald B. Percival. Wavelet variance, Allan variance, and leakage[J]. IEEE Trans. on Instrumentation and Measurement.1995,44(2):94-97.
[80]史锦顺.方差的新概念——兼论阿仑方差[J].电光系统.2001,16(1)：1-10.
[81]史锦顺.测量精度的新概念[J].电光系统.2003,18(3)：3-7.
[82]Hanspeter Schaub, John L. Junkins. Stereographic orientation parameters for attitude dynamics:a generalization of the Rodrigues parameters[J]. Journal of the Astronautical Sciences.1996,44(1):1-19.
[83]李战,冀邦杰,国琳娜.光纤陀螺漂移信号的Allan方差分析[J].光电子·激光.2008,19(2)：183-186.
[84]徐怀明,王建,帅必晖等.利用分段回归拟合激光陀螺仪零偏测试的Allan方差[J].光学技术.2007,33(6)：867-869.
[85]Hou H, El-Sheimy N.. Inertial Sensors Errors Modeling Using Allan Variance[C]. Proceedings of the 16th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GPS/GNSS 2003),2003:2860-2867.
[86]Quang M. Lam, Nick Stamatakos, Craig Woodruff et al. Gyro modeling and estimation of its random noise sources[C]. Proceedings of the 16th AIAA Guidance Navigation and Control Conference and Exhibit.2003, vol.8.
[87]H. Hou, N. El-Sheimy. Inertial Sensors Errors Modeling Using Allan Variance[C]. Proceedings of the 16th International Technical Meeting of the Satellite Division of the Institute of Navigation ION GPS/GNSS.2003:2860-2867.
[88]倪静静,王俊璞,卫炎等.三轴一体化光纤陀螺的Allan方差分析[J].光学仪器.2007,29(1)：57-61.
[89]刘付强.基于MEMS器件的捷联姿态测量系统技术研究[D].哈尔滨工程大学博士研究生学位论文.2007.
[90]Ferre-Pikal E. S., Vig J. R., Camparo J. C., Draft Revision of IEEE Std 1139-1988 Standard Definitions of Physical Quantities for Fundamental Frequency and Time Metrology-Random Instabilities[C]. Proceedings of the IEEE Frequency Control Symposium,1997:338-357.
[91]IEEE Std 1139-1988, IEEE Standard Definitions of Physical Quantities for Fundamental Frequency and Time Metrology[S].
[92]IEEE Std 1293-1998 IEEE Standard Specification Format Guide and Test Procedure for Linear, Single-Axis, Non-gyroscopic Accelerometers[S].
[93]H. Hou, Modeling Inertial Sensors Errors Using Allan Variance[D]. University of Calgary,2004.
[94]卢逢春,张殿伦,田坦.相控阵多普勒计程仪的相控波束接收方案[J].应用声学.2002,21(4)：6-9.
[95]张殿伦,卢逢春,田坦等.相控阵多普勒计程仪声基阵输出信号模型[J].应用声学.2003,22(5)：21-24页.
[96]田坦,张殿伦,卢逢春等.相控阵多普勒测速技术研究.哈尔滨工程大学学报.2002,23(1)：80-85.
[97]陈刚,高贤志,赵汪洋.基于小波变换的多普勒声纳数据处理研究[J].传感器与微系统,2006,25(12)：9-11.
[98]Cardarelli, D.. An integrated MEMS inertial measurement unit[C]. Proceedings of the IEEE Position Location and Navigation Symposium.2002,314-319.
[99]吉训生,王寿荣,许宜申.自适应Kalman滤波在MEMS陀螺仪信号处理中的应用. 传感器与微系统[J].2006,25(9)：330-334.
[100]Zhang Hua, Ke Xizheng, Jiao Rong. Experimental Research on Feedback Kalman Model of MEMS Gyroscope[C]. Proceedings of the Eighth International Conference on Electronic Measurement and Instruments,2007.253-256P.
[101]刘学敏,徐玉如.水下机器人运动的S面控制方法[J].海洋工程.2001,19(3)：81-84.
[102]刘建成,于华男,徐玉如.水下机器人改进的S面控制方法[J].哈尔滨工程大学学报.2002,23(1)：33-36.
[103]Berg R.. Estimation and prediction for maneuvering target trajectories[J]. IEEE Transactions on Automatic Control.1983,28(3):294-304.
[104]Platil A., Kubik J., Vopalensky M., et al. Precise AMR Magnetometer for Compass[C]. Proceedings of IEEE Sensors,2003.461-472P.
[105]安振昌.区域和全球地磁场模型[J].地球物理学进展.1995,3：63-72.
[106]安振昌.地磁场模型的计算和评述[J].地球科学进展.1993,4：45-48.
[107]熊剑,刘建业,孙永荣等.数字磁罗盘的研制[J].传感器技术.2004,23(8)：46-51.
[108]Shibin Liu, Jiaming Yan, Xiren Sun. Magnetic deviation compensation for UAV's heading measurement[J]. Acta Aeronautica et Astronautic Sinica.2000,21(1):78-80.
[109]Pengfei Guo, Zhang Ren, Haitao Qiu, Xinchun Ding. Twelve-position calibrating method without north reference for magnetic compass[J]. Journal of Chinese Inertial Technology.2007,15(5):598-601.
[110]Jing Zhang, Zhihua Jin, Weifeng Tian. Deviation calibrating for digital magnetic compass without heading reference[J]. Journal of Shanghai Jiaotong University.2004, 38(10):1757-1760.
[111]K. L. Lai, J. L. Crassidis, R. R. Harman. Real-time-attitude-independent three-axis magnetometer calibration[J]. Journal of Guidance, Control and Dynamics.2005,28(1): 115-120.
[112]王小旭,赵琳,夏全喜等.基于Unscented变换的强跟踪滤波器[J].控制与决策.2010,25(7)：1063-1068.
[113]葛哲学,杨拥民,温熙森.强跟踪UKF方法及其在故障辨识中的应用[J].仪器仪表学报.2008,29(8)：1670-1674.
[114]陆海勇,赵伟,熊剑等.强跟踪UKF滤波在SINS/GPS组合导航中的应用研究[J].航空电子技术.2008,39(4)：5-10.
[115]范利涛.自动转移飞行器自主导航方法研究[D].国防科学技术大学博士研究生学位论文.2009.
[116]周东华,席裕庚,张钟俊.一种带多重次优渐消因子的扩展卡尔曼滤波器[J].自动化学报.1991,17(6)：689-695页.
[117]周东华,席裕庚,张钟俊.非线性系统的带次优渐消因子的扩展卡尔曼滤波[J],控制与决策.1990,5(5)：1-6页.
[118]周东华.一类非线性系统故障检测与诊断的滤波器方法[D].上海交通大学博士研究生学位论文.1990.
[119]J. Eyre J. Bier. The Eolution of DSP Processors[J]. IEEE Signal Processing Magazine. 2000(17):43-51.
[120]牛海燕.基于DSP的捷联惯导系统设计[J].仪器仪表学报.2004,25(4)：214-216.
[121]孙志坚,刘学海,王玉辉.浮点DSP+FPGA在组合惯导系统中的应用[J].弹箭与制导学报.2005,25(3)：119-121.
[122]曾鸣,冯建鑫,于志伟.基于角速度频域重构的旋转矢量解算[J].中国惯性技术学报.2008,16(2)：144-147.
[123]朱威,张明,吴文启.捷联惯性导航频域算法的仿真研究[J].系统仿真技术及其应用.2006,9：75-77.
[124]岳达,吴第旻,王正志.基于离散傅里叶变换的姿态算法研究[J].计算机仿真.2010,7：21-24.
[125]高清维,程蒲,张道信.基于对称延拓的DFT频谱泄露抑制方法[J].安徽大学学报(自然科学版).2000,24(2)：30-35.
[126]钟佑明,秦树人,汤宝平.关于DFT中的延拓原理及计算结果物理意义的一些讨论[J].震动与冲击.2001,20(4)：1-3.
[127]纪跃波,秦树人,柏林等.有限区间信号边界效应问题的研究[J].震动与冲击.2002,21(4)：108-112.
[128]钟佑明,汤宝平,秦树人.离散傅里叶变换(DFT)计算中一些问题的论证[J].重庆大学学报(自然科学版).2001,24(3)：1-4.
[129]杨金显.微惯性测量系统关键技术研究[D].哈尔滨工程大学博士研究生学位论文.2008.
[130]黄昊,邓正隆.角速率输入下的航姿算法研究[J].中国惯性技术学报.2000,8(2)：21-26.
[131]A. Gadre, D. Stilwell. Toward underwater navigation based on range measurements from a single location[C]. Proceedings of the IEEE International Conference on Robotics and Automation,2004,4472-4477.
[132]D. Loebis, R. Sutton, J. Chudley. Adaptive tuning of a Kalman filter via fuzzy logic for an intelligent AUV navigation system[J]. Control Engineering Practice.2004,12: 1531-1539.
[133]Lefebvre T., Bruyninckx H., J. De Schutter. Comment on A new method for the nonlinear transformation of mean and covariances in filters and estimation [J]. IEEE Trans. Automat. Contr..2002,47(8):1406-1408.
[134]Tenne D, Singh T. The higher order unscented filter[C]. Control Conference,2003, 2441-2446.
[135]Loebis D., Naeem W., Sutton R.etc.. Navigation, guidance and control of the Hammerhead autonomous vehicle[J]. Advances in unmanned marine vehicles, IEE Control Series, IEE Press,2005.
[136]Demoz Gebre-Egziabher, Roger C. Hayward, J. David Powell. Design of Multi-Sensor Attitude Determination Systems[J]. IEEE Trans. on aerospace and electronic systems. 200440(2):627-649.
[137]Gao Zhong-yu, Niu Xiao-ji, Guo Mei-feng. Quaternion-Based Kalman Filter for Micro-machined Strapdown Attitude Heading Reference System[J]. CHINESE JOURNAL OF AERONAUTICS.2002,15(3):171-175.
[138]邓自立,王建国.非线性系统的自适应推广的Kalman滤波[J].自动化学报,1987,13(5)：375-379.
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