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无人飞行器的北斗卫星组合导航算法研究 被引量:2

Unmanned aerial vehicles beidou satellite navigation algorithms
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摘要 北斗卫星导航系统是中国自行研制的全球卫星定位与通信系统,为促进北斗卫星系统在导航方面的运用,降低我国导航方面对GPS的依靠,从而进一步降低成本,提高无人飞行器的导航精度,本文对捷联式惯性导航系统(INS)和北斗定位导航系统的组合导航算法进行了研究,通过惯性导航系统的原理和导航解算的过程,选择惯导系统和北斗系统的速度、位置差值作为观测量,建立组合导航系统的状态方程和观测方程,利用无迹卡尔曼滤波得到惯导系统状态量和惯性敏感器的误差,对惯导系统进行误差补偿,从而实现无人飞行器的高精度导航控制。并使用Matlab进行仿真,得出高精度的模拟输出轨迹。 The beidou satellite navigation system is developed by China's global satellite positioning and communication system, to promote the beidou satellite system used in navigation, reduce on the dependence of the GPS navigation in China, so as to further reduce the cost, improve the navigation precision of the unmanned aerial vehicles, in this paper, the strapdown inertial navigation system( INS )and beidou navigation and positioning system of the integrated navigation algorithm is studied, calculating by the principle of inertial navigation system and navigation process, select the speed of the inertial navigation system and beidou system, location difference as observed quantity, establish integrated navigation system state equation and observation equation, no trace kalman filter are used to get the state of inertial navigation system and the error of inertial sensors, compensate the error of inertial navigation system, so as to realize the high precision navigation control of unmanned aerial vehicles.And use the Maflab simulation, and high precision analog output trajectory.
作者 范项媛
出处 《网络安全技术与应用》 2014年第5期5-7,共3页 Network Security Technology & Application
关键词 无人飞行器 INS 北斗组合导航算法 扩展卡尔曼滤波(EKF) unmanned aerial vehicles INS/beidou integrated navigation algorithm Extended kalman filtering ( EKF )
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  • 1吴太旗,孙付平,易维勇,李海峰.GPS/INS组合导航系统的Matlab/Simulink仿真[J].测绘学院学报,2004,21(3):172-174. 被引量:17
  • 2杨勇,缪玲娟,沈军.Method of Improving the Navigation Accuracy of SINS by Continuous Rotation[J].Journal of Beijing Institute of Technology,2005,14(1):45-49. 被引量:22
  • 3Kim K, Park C G. INS/GPS tightly coupled approach using an INS error predictor[C]// ION Proc. o f GNSS 18th International Technical Meeting of the Satellite Division, Long Beach, CA, 2005.
  • 4Van der Merve R, Wan E A. Sigma-point Kalman filters for honlinear estimation and sensor-fusion:applications to integrated navigation[ C] // Proc. o f AIAA Guidance, Navigation & Control Conference, Providence, RI, 2004.
  • 5Julier S J, Uhlmann J K, Durrant-Whyte H F. A new approach for filtering nonlinear system[C]// Proc. of American. Control Conference, Seattle, WA , 1995:1628- 1632.
  • 6Julier S J, Uhlmann J K, Durrant-Whyte H F. A new method for the nonlinear transformation of means and covarianees in filters and estimators[J]. IEEE Trans. on Automatic Control, 2000, 45 (3) : 477 - 482.
  • 7Julier S J, Uhlmann J K. Unscented filtering and nonlinear estimation[J]. Proc. of the IEEE, 2004, 92:401-422.
  • 8Li Yong, Wang Jinling. Low-cost tightly coupled GPS/INS integration based on a nonlinear Kalman filtering design[C]//ION NTM, Monterey, CA, 2006.
  • 9Van der Merwe R, Wan E A. Sigma-point Kalman filters for integrated mavigation[C]//Proc, of the 60th Annual Meeting of The Institute of Navigation, Dayton, OH: ION, 2004 : 641 - 654.
  • 10David H T, Weston J L, Strapdown inertial navigation technology[M]. 2nd ed. Reston, VA , American Institute of Aeronautics and Astronautics, 2004.

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