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基于卡尔曼滤波的轴向加速度动态误差补偿方法 被引量:4

Dynamic Calibration Method of Axial Acceleration Based on Kalman Filter
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摘要 为了减小高速旋转弹上加速度传感器的量测误差,提出了基于质点弹道模型的比例系数卡尔曼滤波估计算法。结合转速的实时测量,对加速度传感器输出数据进行动态补偿,得到了轴向加速度的测量值。蒙特卡洛模拟仿真和外场试验证实了理论分析的正确性和误差消除方法的有效性。外场试验表明,轴向加速度测量值相对雷达测量值误差的均值小于0.05g,均方差小于0.32g,轴向加速度测量误差的均值由0.1g降低到0.01g的量级,大幅度地提高了轴向加速度测量精度。 To reduce measurement errors of acceleration sensor on the high-speed rotating bomb, Kalman filter estimation algorithm was proposed based on scaling factor of particle traj ectory model.The rotating speed was measured real-timely,and acceleration sensor output-data were dy-namically compensated.The measured value of axial acceleration was obtained.Monte-Carlo simulations and field tests confirm that the theoretical analysis is correct,and the method of elim-inating error is effective.Field tests show that average error of axial-acceleration measured-value is less than 0.05g compared with radar measurements,and the mean square deviation is less than 0.32g.The magnitude of the average measured-error of axial acceleration decreases from 0.1g to 0.01g.The axial-acceleration measurement-accuracy is greatly improved.
出处 《弹道学报》 CSCD 北大核心 2014年第1期103-106,共4页 Journal of Ballistics
基金 国防预研基金项目
关键词 轴向加速度 卡尔曼滤波 误差补偿 axial acceleration Kalman filter error compensation
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  • 1MERHAV S J. A no gyroscopic inertial measurement unit[J]. Journal of Guidance,1982,5(3) :227--235.
  • 2孙志明.硅加速度计在末制导炮弹测试中的应用[J].弹箭与制导学报,2003,23(1):91-93. 被引量:4
  • 3FLECK V, SOMMER E. Study of real-time filtering for an inertial measurement unit with magnetometer in a 155 mm projeetile[C]//IEEE/ION Position, Location and Navigation Symposium. Coronado, USA : IEEE, 2006 : 83-- 87.
  • 4BROWN T G. Harsh military environments and microelectro- mechanical devices [ C]//The Second IEEE International Conference on Sensors. Toronto: IEEE,2003 : 753-760.
  • 5杨慧娟,黄铮,霍鹏飞,王超.旋转稳定弹轴向加速度测量误差模型分析[J].弹道学报,2013,25(4):48-52. 被引量:3
  • 6CRASSIDIS J L, MARKLEY F L. Unscented filtering for spacecraft attitude estimation [J ]. Journal of Guidance, Control, and Dynamics, 2003,26 (4) : 536 -- 542.
  • 7SIMON H. Kalman filtering and neural networks[M]. New York:John Wiley & Sons,Inc,2001:215--218.
  • 8LEONARD C. Modified projectile linear theory for rapid trajectory prediction [J]. Journal of Guidance, Control, and Dynamics. 2005,28(5) :375--377.

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