自适应FLP滤波在激光陀螺IMU标定中的应用
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摘要
激光陀螺的高频机抖使得激光陀螺惯性测量单元(IMU)的测量数据包含较大的随机噪声。传统标定方法通过延长测量时间消除对随机噪声的影响,降低了标定效率。提出了应用自适应前向线性预测(FLP)滤波对激光陀螺IMU的标定数据进行降噪,在较小标定数据量情况下提高系统的标定精度。首先通过四方位正反速率标定试验获得原始标定数据;然后通过自适应FLP滤波器对标定数据进行噪声抑制;最后利用降噪后的数据计算标定参数。试验结果表明,该方法能够有效抑制标定数据中的随机噪声,提高信号的信噪比(SNR),从而在标定数据量较小的情况下得到较高精度的标定参数,提升系统的导航精度。
Ring laser gyro inertial measurement unit(IMU) encounters the problem of relatively large stochastic noise because of the strenuous dithering motion. The conventional calibration method eliminates the impact on the stochastic noise by extending the measurement time,which undoubtedly reduces the calibration efficiency. To solve the problem,the adaptive forward linear prediction(FLP) filter is adopted to suppress the stochastic noises of ring laser gyro IMU calibration data and improve the calibration accuracy of the system with small amount of calibration data. Firstly,the original data is acquired from the four-position rotation calibration experiment. Secondly,the calibration data is de-noised by the adaptive FLP filter to improve its signal noise ratio(SNR). Finally,the calibration parameters are calculated with the de-noised data. The experimental results show that the stochastic noises of calibration data are de-noised effectively by the adaptive FLP filter,the SNR of the signal is improved,and more accurate calibration parameters are acquired with small amount of calibration data,which enhances the navigation accuracy of the system.
Ring laser gyro inertial measurement unit(IMU) encounters the problem of relatively large stochastic noise because of the strenuous dithering motion. The conventional calibration method eliminates the impact on the stochastic noise by extending the measurement time,which undoubtedly reduces the calibration efficiency. To solve the problem,the adaptive forward linear prediction(FLP) filter is adopted to suppress the stochastic noises of ring laser gyro IMU calibration data and improve the calibration accuracy of the system with small amount of calibration data. Firstly,the original data is acquired from the four-position rotation calibration experiment. Secondly,the calibration data is de-noised by the adaptive FLP filter to improve its signal noise ratio(SNR). Finally,the calibration parameters are calculated with the de-noised data. The experimental results show that the stochastic noises of calibration data are de-noised effectively by the adaptive FLP filter,the SNR of the signal is improved,and more accurate calibration parameters are acquired with small amount of calibration data,which enhances the navigation accuracy of the system.
引文
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[13]陈熙源,许常燕.基于前向线性预测算法的光纤陀螺零漂的神经网络建模[J].中国惯性技术学报,2007,15(3):334-337.CHEN X Y,XU C Y.Neural network modeling for FOG zero point drift based on forward linear prediction algorithm[J].Journal of Chinese Inertial Technology,2007,15(3):334-337(in Chinese).
[14]易康,李廷志,吴文启.FLP滤波算法在光纤陀螺信号预处理中的应用[J].中国惯性技术学报,2005,13(5):58-62.YI K,LI T Z,WU W Q.Application of forward linear prediction filter in signal process of FOG[J].Journal of Chinese Inertial Technology,2005,13(5):58-62(in Chinese).
[15]NG L C,PINES D J.Characterization of ring laser gyro performance using the Allan variance method[J].Journal of Guidance Control&Dynamics,2012,20(1):211-214.
[16]SAVAGE P G.Analytical modeling of sensor quantization in strapdown inertial navigation error equations[J].Journal of Guidance Control&Dynamics,2012,25(5):833-842.
[2]LI J,FANG J,GE S S.Kinetics and design of a mechanically dithered ring laser gyroscope position and orientation system[J].IEEE Transactions on Instrumentation&Measurement,2013,62(1):210-220.
[3]FANG J,CHEN L,YAO J.An accurate gravity compensation method for high-precision airborne POS[J].IEEE Transactions on Geoscience&Remote Sensing,2014,52(8):4564-4573.
[4]程骏超,房建成,吴伟仁,等.一种激光陀螺惯性测量单元混合标定方法[J].中国惯性技术学报,2014,22(4):445-452.CHENG J C,FANG J C,WU W R,et al.Integrated calibration method for RLG IMU[J].Journal of Chinese Inertial Technology,2014,22(4):445-452(in Chinese).
[5]LI J,JIAO F,FANG J,et al.Integrated calibration method for dithered RLG POS using a hybrid analytic/Kalman filter approach[J].IEEE Transactions on Instrumentation&Measurement,2013,62(12):3333-3342.
[6]李建利,房建成,马艳海,等.INS全温六方位速率标定及分段线性插值补偿[J].北京航空航天大学学报,2012,38(10):1331-1335.LI J L,FANG J C,MA Y H,et al.Six-position rotation rate calibration and piecewise linear interpolation compensation for INSin full temperatures[J].Journal of Beijing University of Aeronautics and Astronautics,2012,38(10):1331-1335(in Chinese).
[7]SANG M S,LEE J G,CHAN G P.Equivalent ARMA model representation for RLG random errors[J].IEEE Transactions on Aerospace&Electronic Systems,2000,36(1):286-290.
[8]HAN S,WANG J.Quantization and colored noises error modeling for inertial sensors for GPS/INS integration[J].IEEE Sensors Journal,2011,11(6):1493-1503.
[9]钟麦英,闫东坤.激光陀螺POS惯性数据滤波及时延补偿[J].中国惯性技术学报,2011,19(6):670-675.ZHONG M Y,YAN D K.Predictive filtering and delay compensation of RLG position and orientation system[J].Journal of Chinese Inertial Technology,2011,19(6):670-675(in Chinese).
[10]李建利,陈安升,钟麦英,等.基于线性相位无限长单位冲击响应滤波器的机抖激光陀螺POS低时延降噪方法[J].中国惯性技术学报,2012,20(6):644-649.LI J L,CHEN A S,ZHONG M Y,et al.Low time delay de-noising method for mechanically dithered RLG POS based on linear phase infinite impulse response filter[J].Journal of Chinese Inertial Technology,2012,20(6):644-649(in Chinese).
[11]高伟,祖悦,王伟,等.基于二代小波的光纤陀螺实时降噪方法研究[J].仪器仪表学报,2012,33(4):774-780.GAO W,ZU Y,WANG W,et al.Research on real-time de-noising of FOG based on second generation wavelet transform[J].Chinese Journal of Scientific Instrument,2012,33(4):774-780(in Chinese).
[12]张通,张骏,张怡.基于改进小波阈值的激光陀螺漂移信号降噪[J].仪器仪表学报,2011,32(2):258-263.ZHANG T,ZHANG J,ZHANG Y.Ring laser gyro drift signal denoising based on improved wavelet threshold[J].Chinese Journal of Scientific Instrument,2011,32(2):258-263(in Chinese).
[13]陈熙源,许常燕.基于前向线性预测算法的光纤陀螺零漂的神经网络建模[J].中国惯性技术学报,2007,15(3):334-337.CHEN X Y,XU C Y.Neural network modeling for FOG zero point drift based on forward linear prediction algorithm[J].Journal of Chinese Inertial Technology,2007,15(3):334-337(in Chinese).
[14]易康,李廷志,吴文启.FLP滤波算法在光纤陀螺信号预处理中的应用[J].中国惯性技术学报,2005,13(5):58-62.YI K,LI T Z,WU W Q.Application of forward linear prediction filter in signal process of FOG[J].Journal of Chinese Inertial Technology,2005,13(5):58-62(in Chinese).
[15]NG L C,PINES D J.Characterization of ring laser gyro performance using the Allan variance method[J].Journal of Guidance Control&Dynamics,2012,20(1):211-214.
[16]SAVAGE P G.Analytical modeling of sensor quantization in strapdown inertial navigation error equations[J].Journal of Guidance Control&Dynamics,2012,25(5):833-842.
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