| 动态Allan方差改进算法及其在FOG启动信号分析中的应用 |
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| 引用本文： | 汪立新,朱战辉,李瑞.动态Allan方差改进算法及其在FOG启动信号分析中的应用[J].红外与激光工程,2016,45(7):726004-0726004(8). |
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| 作者姓名： | 汪立新 朱战辉 李瑞 |
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| 作者单位： | 1.西安市高科技研究所,陕西 西安 710025 |
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| 基金项目： | 国家自然科学基金（61503390） |
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| 摘 要： | 针对动态Allan方差运用固定长度的分析窗截取信号导致样本数据量减少，长相关时间下方差估计值置信度降低，首先，针对动态信号跟踪能力与置信度的提高不能兼顾的问题提出了一种改进算法。引入截断窗内峭度值作为表征信号短时稳定度的参数，并建立以峭度为变量的窗宽函数，该函数可以使截断窗长随着信号的平稳程度自动变化。其次，再用窗宽自适应的滑动窗分段截取陀螺随机误差，分别对每个截断窗内样本进行总方差计算以增加方差估计的自由度。最后，计算延伸后样本的Allan方差，并将其以三维形式排列出来。结果表明:应用该方法对光纤陀螺启动信号进行分析，该算法既能更有效地跟踪信号的非平稳变化，又能大幅降低长相关时间下方差的估计误差。
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| 关 键 词： | 光纤陀螺 启动信号 动态Allan方差 总方差 峭度 |
| 收稿时间： | 2015-11-05 |
Improvement algorithm of dynamic Allan variance and its application in analysis of FOG start-up signal |
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| Affiliation: | 1.High-tech Institute of Xi'an,Xi'an 710025,China |
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| Abstract: | The classical dynamic Allan variance(DAVAR) can describe the non-stationary of random error of fiber optical gyroscope(FOG) effectively. However, the method has defects such as poor confidence on the estimation of long-term -values due to the reduced amount of data captured by the fixed length windows. Besides, the method is difficult to make a satisfactory tradeoff between dynamic tracking capabilities and variance reduction. An improved DAVAR algorithm based on kurtosis and data extension was proposed to solve the problems. Firstly, the kurtosis of data inside the windows was introduced as characterization of signal's instantaneous non-stationary, and the window length function which was utilized to truncate the signal was built by taken kurtosis as variables, the function can make window length change with the non-stationary of the signal automatically. Secondly, the random error of FOG was truncated with the function. Then the data in the windows were extended by the total variance method to improve the confidence. At last the Allan variance of extended data was computed and arranged by three-dimensional. The measured data of FOG start-up signal was analyzed with the proposed algorithm and DAVAR. The results show that the proposed algorithm is an effective way to characterize non-stationary of FOG and can also obtain a lower estimation error at long-term -values. |
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