| 小波去噪技术在捷联寻北仪中的应用 |
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| 引用本文： | 任明荣,刘星桥,陈家斌,张长江,谢玲,徐建华.小波去噪技术在捷联寻北仪中的应用[J].北京理工大学学报,2004,24(7):592-595. |
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| 作者姓名： | 任明荣 刘星桥 陈家斌 张长江 谢玲 徐建华 |
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| 作者单位： | 北京理工大学,信息科学技术学院自动控制系,北京,100081;北京理工大学,信息科学技术学院自动控制系,北京,100081;北京理工大学,信息科学技术学院自动控制系,北京,100081;北京理工大学,信息科学技术学院自动控制系,北京,100081;北京理工大学,信息科学技术学院自动控制系,北京,100081;北京理工大学,信息科学技术学院自动控制系,北京,100081 |
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| 摘 要： | 为了提高捷联寻北仪在动态干扰下的精度,采用小波去噪法对寻北仪的原始输出信号进行处理.通过对多尺度下信号的小波变换系数及模极大值的跟踪,发现有用信号为平稳信号,而干扰信号的模极大值并不都随尺度的增加而减少,因此提出模极大值与软阈值相结合的方法.对随尺度增大的模极大值用其左右相邻几个非模极大值平均值替代,滤去李氏指数大于0的干扰信号;对李氏指数小于0的噪声采用软阈值法去噪.该方法可使寻北精度达到1 mrad.
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| 关 键 词： | 捷联寻北仪 动态干扰 小波去噪 模极大值 软阈值 |
| 文章编号： | 1001-0645(2004)07-0592-04 |
| 收稿时间： | 2003/9/19 0:00:00 |
| 修稿时间： | 2003年9月19日 |
Wavelet Denoising for a Strapdown North Finder |
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| REN Ming-rong,LIU Xing-qiao,CHEN Jia-bin,ZHANG Chang-jiang,XIE Ling and XU Jian-hua.Wavelet Denoising for a Strapdown North Finder[J].Journal of Beijing Institute of Technology(Natural Science Edition),2004,24(7):592-595. |
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| Authors: | REN Ming-rong LIU Xing-qiao CHEN Jia-bin ZHANG Chang-jiang XIE Ling and XU Jian-hua |
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| Institution: | Department of Automatic Control,School of Information Science and Technology, Beijing Institute of Technology, Beijing100081, China;Department of Automatic Control,School of Information Science and Technology, Beijing Institute of Technology, Beijing100081, China;Department of Automatic Control,School of Information Science and Technology, Beijing Institute of Technology, Beijing100081, China;Department of Automatic Control,School of Information Science and Technology, Beijing Institute of Technology, Beijing100081, China;Department of Automatic Control,School of Information Science and Technology, Beijing Institute of Technology, Beijing100081, China;Department of Automatic Control,School of Information Science and Technology, Beijing Institute of Technology, Beijing100081, China |
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| Abstract: | To improve the accuracy of a strapdown north finder used under dynamic conditions of disturbances, a new wavelet denoising method is introduced to process the original output of the north finder. From wavelet transform modulus across scales, it is seen that useful signal is stable and some maximum modules does not decrease in larger scales. So maximum modules and soft-thresholding are proposed.Some maximum modules whose values grow larger with increase in their scales are substituted by mean value of non-maximum modules adjacent to them. Thus disturbances whose Lipschitz exponent is larger than zero are filtered. Soft-thresholding is used to filter the noise whose Lipschitz exponent is smaller than zero. The method can improve the accuracy of strapdown finder to 1 mrad. |
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| Keywords: | strapdown north finder dynamic disturbance wavelet denoising locale maximum modulus soft-thresholding |
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