刘孝博,
王迪,
刘射德
1.兰州交通大学自动控制研究所 ??兰州 ??730070
2.甘肃省高原交通信息工程及控制重点实验室 ??兰州 ??730070
基金项目:国家自然科学基金(61863024, 71761023)、甘肃省基础研究创新群体计划(1606RJIA327)、甘肃省自然基金(18JR3RA107, 1610RJYA034)、甘肃省高等学校科研项目资助(2018C-11)、甘肃省科技计划资助(18CX3ZA004)
详细信息
作者简介:陈光武：男，1976年生，教授，研究方向为惯导和组合导航
刘孝博：男，1994年生，硕士，研究方向为惯性导航、传感器数据处理
王迪：男，1991年生，硕士，研究方向为组合导航
刘射德：男，1994年生，硕士，研究方向为视觉导航
通讯作者:陈光武 cgwyjh1976@126.com
中图分类号:U666.1; TN911.7计量
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被引次数:0
出版历程
收稿日期:2018-06-13
修回日期:2018-12-25
网络出版日期:2019-01-04
刊出日期:2019-05-01
Denoising of MEMS Gyroscope Based on Improved Wavelet Transform
Guangwu CHEN,,Xiaobo LIU,
Di WANG,
Shede LIU
1. Automatic Control Research Institute, Lanzhou Jiaotong University, Lanzhou 730070, China
2. Gansu Provincial Key Laboratory of Traffic Information Engineering and Control, Lanzhou 730070, China
Funds:The National Natural Science Foundation of China (61863024, 71761023), The Gansu Basic Research Innovation Group Program (1606RJIA327), The Gansu Natural Science Foundation (18JR3RA107 1610RJYA034), Granted by Gansu Provincial Higher Education Research Project (2018C-11), The Gansu Province Science and Technology Plan Funding (18CX3ZA004)
摘要
摘要:为提高MEMS陀螺仪测量精度，抑制测量噪声对其造成的影响，该文分析了某型号MEMS陀螺仪误差特性，提出基于递归最小二乘法(RLS)多重小波分解重构的强追踪自反馈模型，建立新的软阈值函数。由于模型处理后的数据带有部分奇异值，该文提出了一种改进的中值滤波算法。对于陀螺仪零偏噪声问题，提出零偏不稳定性抑制算法，并对该算法模型进行了详细的描述。将某项目研究中列车姿态测量系统的实验数据应用到该算法模型中。测试实验分为静态、动态两组，其结果均表明：该算法减小了信号中的噪声，有效地抑制了MEMS陀螺仪随机漂移，提高了姿态解算的精度。肯定了该算法对陀螺仪输出信号噪声去除，以及使用精度提升的可行性和有效性。
关键词:MEMS陀螺仪/
小波分解/
姿态估计
Abstract:In order to improve the measurement accuracy of Micro Electro Mechanical Systems (MEMS) gyroscopes, the influence of measurement noise on them is suppressed. The error characteristics of a certain type of MEMS gyroscope are analyzed. A strong tracking self-feedback model based on Recursive Least Square (RLS) multiple wavelet decomposition reconstruction is proposed to establish a new soft threshold function. Since the model processed data has partial singular values, an improved median filtering algorithm is proposed. For the problem of gyro zero-bias noise, a zero-bias stability suppression algorithm is proposed. In this paper, the algorithm model is described in detail, and the experimental data of the train attitude measurement system in a project research are applied to the algorithm model. The test experiments are divided into static and dynamic groups. The results show that the algorithm reduces the noise in the signal, suppresses effectively the random drift of the MEMS gyroscope and improves the accuracy of the attitude calculation. The feasibility and effectiveness of this method are affirmed to remove the signal noise of the gyroscope output and improve the accuracy of the use.
Key words:MEMS gyroscope/
Wavelet decomposition/
Attitude estimation
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