基于改进小波降噪的MEMS间接粗对准方法研究
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摘要
当前MEMS惯性传感器陀螺仪精度较低导致输出信噪比较小,使得MEMS捷联惯导系统初始对准时误差较大,初始偏移明显,影响后续的解算精度,定位信息不准确.为此提出了一种利用改进阈值函数的小波对原始数据降噪处理后再采用磁强计辅助的MEMS间接粗对准的方法,通过引入调节系数使阈值函数同时具备软阈值和硬阈值两种特性,使得改进后的小波函数在远离阈值处有明显的边缘特性,而在靠近阈值的地方具有较好的连续性,避免信号重构时产生突变,有效减少了使用单一软阈值或硬阈值的局限性.为了避免陀螺仪精度对初始对准结果的影响而采用磁强计辅助对准,利用小波阈值降噪来对加速度计与磁强计的原始数据进行降噪处理后再进行姿态解算,提高了初始对准精度.
Due to the low accuracy of the MEMS inertial sensor gyroscope and the initial signal-to-noise ratio of the MEMS strapdown inertial navigation system is small, the error of the initial alignment is large, the initial offset is obvious, and the subsequent solution accuracy is affected. To improve the accuracy of positioning information a method based on an improved threshold function in wavelet denoising and using the magnetometer to assist the MEMS indirect coarse alignment is proposed. By introducing the adjustment coefficient, the threshold function has both soft threshold and hard threshold, so that the improved wavelet function has obvious edge characteristics away from the threshold and good continuity near the threshold to avoid mutations in signal reconstruction, then effectively avoid the limitation of using a single soft threshold or hard threshold. In order to avoid the influence of the accuracy of the gyroscope on the initial alignment result, the magnetometer is used to assist the alignment, and the wavelet threshold denoising is used to denoise the original data of the accelerometer and the magnetometer, and then the attitude calculation is performed to improve the initial alignment accuracy.
Due to the low accuracy of the MEMS inertial sensor gyroscope and the initial signal-to-noise ratio of the MEMS strapdown inertial navigation system is small, the error of the initial alignment is large, the initial offset is obvious, and the subsequent solution accuracy is affected. To improve the accuracy of positioning information a method based on an improved threshold function in wavelet denoising and using the magnetometer to assist the MEMS indirect coarse alignment is proposed. By introducing the adjustment coefficient, the threshold function has both soft threshold and hard threshold, so that the improved wavelet function has obvious edge characteristics away from the threshold and good continuity near the threshold to avoid mutations in signal reconstruction, then effectively avoid the limitation of using a single soft threshold or hard threshold. In order to avoid the influence of the accuracy of the gyroscope on the initial alignment result, the magnetometer is used to assist the alignment, and the wavelet threshold denoising is used to denoise the original data of the accelerometer and the magnetometer, and then the attitude calculation is performed to improve the initial alignment accuracy.
引文
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[13] 马晓红,宋辉,殷福亮.自适应小波阈值语音增强新方法 [J].大连理工大学学报,2006,46(4):561-566.MA Xiaohong,SONG Hui,YIN Fuliang.A new approach for adaptive wavelet threshold speech enhancement [J].Journal of Dalian University of Technology,2006,46(4):561-566.(in Chinese)
[14] 王芳,鲁顺昌.小波软硬阈值去噪算法的研究及改进 [J].信息技术,2008(6):124-127,131.WANG Fang,LU Shunchang.Research and improved algorithm for soft-hard threshold denoising [J].Information Technology,2008(6):124-127,131.(in Chinese)
[15] 王维,张英堂,任国全.小波阈值降噪算法中最优分解层数的自适应确定及仿真 [J].仪器仪表学报,2009,30(3):526-530.WANG Wei,ZHANG Yingtang,REN Guoquan.Adaptive selection and simulation of optimal decomposition level in threshold de-noising algorithm based on wavelet transform [J].Chinese Journal of Scientific Instrument,2009,30(3):526-530.(in Chinese)
[16] LE T P.Use of the Morlet mother wavelet in the frequency-scale domain decomposition technique for the modal identification of ambient vibration responses [J].Mechanical Systems and Signal Processing,2017,95:488-505.
[2] 高勇,曹娟娟,唐海红,等.磁强计辅助基于MEMS惯性器件SINS的初始对准方法研究 [J].航天控制,2013,31(3):50-54.GAO Yong,CAO Juanjuan,TANG Haihong,et al.Study on MEMS-SINS in initial alignment with magnetometer assistance [J].Aerospace Control,2013,31(3):50-54.(in Chinese)
[3] 张剑慧,秦永元,龙瑞.捷联惯导系统双矢量定姿方法研究 [J].计算机测量与控制,2010,18(11):2634-2637.ZHANG Jianhui,QIN Yongyuan,LONG Rui.Studying on algorithm of double-vector attitude determination in SINS [J].Computer Measurement & Control,2010,18(11):2634-2637.(in Chinese)
[4] 李兵军,高伟,王慧,等.基于线性最优控制的捷联惯导初始对准方法研究 [J].弹箭与制导学报,2008(2):8-12.LI Bingjun,GAO Wei,WANG Hui,et al.Study on initial alignment of strapdown inertial navigation system based on linear optimum control [J].Journal of Projectiles,Rockets,Missiles and Guidance,2008(2):8-12.(in Chinese)
[5] ZHANG Xun,LI Juelong,XING Jianchun,et al.A particle swarm optimization technique-based parametric wavelet thresholding function for signal denoising [J].Circuits,Systems,and Signal Processing,2017,36(1):247-269.
[6] DAVOUDABADI M J,AMINGHAFARI M.A fuzzy-wavelet denoising technique with applications to noise reduction in audio signals [J].Journal of Intelligent & Fuzzy Systems,2017,33(4):2159-2169.
[7] 袁群哲,郑振宇,韩云东.基于QUEST算法的捷联惯导惯性系对准精度分析 [J].电子测量技术,2017,40(7):67-70,89.YUAN Qunzhe,ZHENG Zhenyu,HAN Yundong.Error analysis of SINS alignment in inertial frame based on QUEST attitude determination algorithm [J].Electronic Measurement Technology,2017,40(7):67-70,89.(in Chinese)
[8] CHOE Namchol,赵红宇,仇森,等.低成本MEMS磁力计校正方法研究 [J].大连理工大学学报,2018,58(1):105-110.CHOE Namchol,ZHAO Hongyu,QIU Sen,et al.Study of calibration method of low-cost MEMS magnetometer [J].Journal of Dalian University of Technology,2018,58(1):105-110.(in Chinese)
[9] 周伟.基于MATLAB的小波分析应用 [M].2版.西安:西安电子科技大学出版社,2010.ZHOU Wei.Application of Wavelet Analysis Based on MATLAB [M].2nd ed.Xi′an:Xi′an University of Electronic Science and Technology Press,2010.(in Chinese)
[10] 陈晓曦,王延杰,刘恋.小波阈值去噪法的深入研究 [J].激光与红外,2012,42(1):105-110.CHEN Xiaoxi,WANG Yanjie,LIU Lian.Deep study on wavelet threshold method for image noise removing [J].Laser & Infrared,2012,42(1):105-110.(in Chinese)
[11] 单锐,齐越,刘文.一种改进的小波阈值去噪算法 [J].兰州理工大学学报,2014,40(4):101-104.SHAN Rui,QI Yue,LIU Wen.An improved algorithm for denoising of wavelet threshold value [J].Journal of Lanzhou University of Technology,2014,40(4):101-104.(in Chinese)
[12] 卢广森,黎英,毛敏.基于新阈值函数的小波阈值去噪算法 [J].传感器与微系统,2017,36(12):141-144,148.LU Guangsen,LI Ying,MAO Min.Wavelet threshold de-noising algorithm based on new threshold function [J].Transducer and Microsystem Technologies,2017,36(12):141-144,148.(in Chinese)
[13] 马晓红,宋辉,殷福亮.自适应小波阈值语音增强新方法 [J].大连理工大学学报,2006,46(4):561-566.MA Xiaohong,SONG Hui,YIN Fuliang.A new approach for adaptive wavelet threshold speech enhancement [J].Journal of Dalian University of Technology,2006,46(4):561-566.(in Chinese)
[14] 王芳,鲁顺昌.小波软硬阈值去噪算法的研究及改进 [J].信息技术,2008(6):124-127,131.WANG Fang,LU Shunchang.Research and improved algorithm for soft-hard threshold denoising [J].Information Technology,2008(6):124-127,131.(in Chinese)
[15] 王维,张英堂,任国全.小波阈值降噪算法中最优分解层数的自适应确定及仿真 [J].仪器仪表学报,2009,30(3):526-530.WANG Wei,ZHANG Yingtang,REN Guoquan.Adaptive selection and simulation of optimal decomposition level in threshold de-noising algorithm based on wavelet transform [J].Chinese Journal of Scientific Instrument,2009,30(3):526-530.(in Chinese)
[16] LE T P.Use of the Morlet mother wavelet in the frequency-scale domain decomposition technique for the modal identification of ambient vibration responses [J].Mechanical Systems and Signal Processing,2017,95:488-505.