| MEMS陀螺仪随机序列趋势项提取算法 |
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| 引用本文： | 商志刚,马晓川,刘宇,袁东玉.MEMS陀螺仪随机序列趋势项提取算法[J].信号处理,2016,32(7):827-833. |
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| 作者姓名： | 商志刚 马晓川 刘宇 袁东玉 |
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| 作者单位： | 1.中国电子科技集团公司电子科学研究院, 北京 100041 |
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| 摘 要： | MEMS陀螺仪目前广泛应用于水下航行器中，但由于在测量数据中含有趋势项，导致序列非平稳，无法应用ARMA模型等时间序列分析方法对其进行分析，因此，需要探究有效的趋势提取方法提取序列趋势项。本文提出了应用平滑先验算法提取MEMS陀螺数据趋势算法，同时介绍了多项式趋势拟合及经验模态分解趋势提取算法，应用三种算法分别对同一实测数据进行趋势提取，选用正态性检验方法，对趋势提取后残余数据的平稳性进行判断，以此判定其趋势提取效果。数据处理结果证明，三种方法均可实现对MEMS陀螺数据的趋势提取，但是各种方法均有其应用的优劣性，需根据其不同应用条件进行优化选择。
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| 关 键 词： | MEMS陀螺仪 趋势项 平滑先验算法 多项式拟合 经验模态分解 |
| 收稿时间： | 2015-05-05 |
Trend Extraction of Random Sequences of MEMS Gyroscopes |
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| Affiliation: | 1.Chinese Academy of Electronics and Information Technology, Beijing 100041, China2.Key Laboratory of Information Technology for Autonomous Underwater Vehicles,Chinese Academy of Sciences, Beijing 100190, China |
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| Abstract: | MEMS gyroscopes are widely applied in the underwater vehicles.Since the random sequences contain the trend terms, which are non stationary.We cannot use ARMA model to analyze the gyroscopes data.Thus, exploring an effective method of the trend extraction is extremely important.This paper proposes the method of the trend extraction based on smoothness prior approach.The polynomial trend fitting method and the empirical mode decomposition method are also introduced.These algorithms are applied in analyzing the experimental data.Normality test for the residual data is selected as the judgment conditions.The results verify that these methods can extract the trend.However, various methods have their advantages and disadvantages.Thus, we need choose the optimal method based on the different applications conditions. |
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