分组并行的交叠式Allan方差快速算法The overlapping fast Allan variance algorithm with grouping parallel
柳絮,王尔林
摘要(Abstract)：
针对标准式Allan方差计算效率低、稳定性差的问题,该文构建了一种局部交叠的快速Allan方差算法。该算法采用分组并行运算的方法,通过局部的交叠式处理,得到指数变步长的数据簇。然后利用标准Allan方差公式获得对应数据簇的Allan方差值,最后绘制双对数曲线分析误差类型与大小。仿真与实测结果表明:与标准式Allan方差相比较,该算法不仅能够更精确地分离和计算噪声系数,而且大幅度提高了解算效率,长度为720 000个样本点的数据解算时长从26.71 min降低到0.35 s。
关键词(KeyWords)： 交叠式Allan方差;惯性器件数据;随机误差;误差辨识;并行计算
基金项目(Foundation): 国家自然科学基金项目(41874029);; 北京建筑大学研究生创新项目(PG2020065)
作者(Author): 柳絮,王尔林
DOI: 10.16251/j.cnki.1009-2307.2021.08.003
参考文献(References)：
- [1] 马群，王庆，阳媛，等.基于Allan方差的MEMS陀螺仪随机误差辨识与抑制[J].传感器与微系统，2019,38(6):62-65.(MA Qun,WANG Qing,YANG Yuan,et al.Random error identification and suppression of MEMS gyroscope based on Allan variance[J].Transducer and Microsystem Technologies,2019,38(6):62-65.)
- [2] 吴纾婕.MIMU器件参数辨识及误差补偿技术研究[D].北京：北京理工大学，2015.(WU Shujie.Reseach on MIMU sensors parameter identification and error compensation[D].Beijing:Beijing Institute of Technology,2015.)
- [3] 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.(LI Xiaoying,HU Min,ZHANG Peng,et al.Applying overlapping Allan variance theory to better stochastic modeling of microgyro[J].Journal of Northwestern Polytechnical University,2007,25(2):225-229.)
- [4] 严恭敏，李四海，秦永元.惯性仪器测试与数据分析[M].北京：国防工业出版社，2012.(YAN Gongmin,LI Sihai,QIN Yongyuan.Inertial instrument measurement and data analysis[M].Beijing:National Defense Industry Press,2012.)
- [5] 汪立新，李灿，姜周，等.动态总方差设计及其快速算法[J].北京航空航天大学学报，2016,42(7):1352-1360.(WANG Lixin,LI Can,JIANG Zhou,et al.Design of dynamic total variance and its fast algorithm[J].Journal of Beijing University of Aeronautics and Astronautics,2016,42(7):1352-1360.)
- [6] 张小红，朱锋，薛学铭，等.利用Allan 方差分析GPS非差随机模型特性[J].测绘学报，2015,44(2):119-127.(ZHANG Xiaohong,ZHU Feng,XUE Xueming,et al.Using Allan variance to analyze the zero-differenced stochastic model characteristics of GPS[J].Acta Geodaetica et Cartographica Sinica,2015,44(2):119-127.)
- [7] 薛学铭.Allan方差分析测量数据噪声特性的性能研究[J].大地测量与地球动力学，2014,34(6):131-134.(XUE Xueming.Study on properties of noise analysis with Allan variance[J].Journal of Geodesy and Geodynamics,2014,34(6):131-134.)
- [8] EI-SHEIMY N,HOU H Y,NIU X J.Analysis and modeling of inertial sensors using Allan variance[J].IEEE Transactions on Instrumentation and Measurement,2008,57(1):140-149.
- [9] IEEE standard specification format guide and test procedure for single-axis interferometric fiber optic gyros:IEEE Std 952-1997[S].Piscataway:IEEE,1998.
- [10] 赵思浩.MEMS惯性器件误差系数的Allan方差分析方法[C]//第一届中国卫星导航学术年会论文集.出版地不详：出版者不详，2010:283-287.(ZHAO Sihao.Allan variance analysis on error coefficients of MEMS inertial components[C]//Proceedings of the First China Satellite Navigation Conference.[S.l.]:[s.n.],2010:283-287.)
- [11] 李鲁明，赵鲁阳，唐晓红，等.基于改进卡尔曼滤波的陀螺仪误差补偿算法[J].传感技术学报，2018,31(4):538-544,550.(LI Luming,ZHAO Luyang,TANG Xiaohong,et al.A compensation algorithm of gyroscope error based on modified Kalman filter[J].Chinese Journal of Sensors and Actuators,2018,31(4):538-544,550.)
- [12] 孙伟，宋如意，王宇航，等.MEMS陀螺仪随机误差KF补偿方法的普适性验证[J].大地测量与地球动力学，2019,39(11):1188-1193.(SUN Wei,SONG Ruyi,WANG Yuhang,et al.Universality verification of random error compensation method for MEMS gyroscope with Kalman filter[J].Journal of Geodesy and Geodynamics,2019,39(11):1188-1193.)
- [13] 丛琳，王小龙，燕斌.煤矿井下微机电系统陀螺随机误差辨识[J].工矿自动化，2019,45(10):95-98.(CONG Lin,WANG Xiaolong,YAN Bin.Random error identification for MEMS gyro in coal mine underground[J].Industry and Mine Automation,2019,45(10):95-98.)
- [14] 王珏，贾瑞才，乔立伟.基于带通滤波器的惯性元件随机噪声逼真模拟方法[J].中国惯性技术学报，2018,26(3):386-391.(WANG Jue,JIA Ruicai,QIAO Liwei.Realistic simulation method of inertial sensor random noise based on band pass filter[J].Journal of Chinese Inertial Technology,2018,26(3):386-391.)
- [15] 吴富梅.GNSS/INS组合导航误差补偿与自适应滤波理论的拓展[J].测绘学报，2011,40(3):401.(WU Fumei.Error compensation and extension of adaptive filtering theory in GNSS/INS integrated navigation[J].Acta Geodaetica et Cartographica Sinica,2011,40(3):401.)