摘要
传统的弱信号恢复方法在强噪声背景下具有较大的局限性,有用的信息往往淹没在强噪声背景下不易被识别。针对这个难点,提出一种基于三维曲波变换的弱信号恢复的方法。该方法将三维曲波变换和自适应滤波器相融合,从而提高数据中弱信号的能量,使得弱信号更易于被恢复。为了验证该方法的有效性,对楔形模型与实际三维数据进行处理。实验结果表明,恢复后的数据信噪比提高了2 d B到3 d B,频带也被拓宽了150 Hz,弱信号得到较好的恢复。
Conventional methods of weak signal recovery are limited under strong noise condition. Useful information is often submerged in heavy noise, which is not easy to identify. As to this problem, a weak signal recovery method based on 3D-curvelet transform is proposed in this paper. Combining 3D-curvelet transform with the adaptive filter is to recover weak signal. Model of wedge and actual data are processed by this method. The experimental results show that the signal to noise ratio of data improves 2 dB to 3 dB and the frequency is increased 150 Hz. Obviously, the weak signal is recovered.
作者
胡雨
谢凯
阮宁君
伍鹏
贺建飚
刘从浩
HU Yu;XIE Kai;RUAN Ningjun;WU Peng;HE Jianbiao;LIU Conghao(Institute for Oil & Gas Information Processing and Identification, Electronics & Information College, Yangtze University,Jingzhou, Hubei 434023, China;College of Information Engineering, China University of Geosciences, Wuhan 430074, China;National Engineering Research Center for Geographic Information System, Wuhan 430074, China;School of Information Science and Engineering, Central South University, Changsha 410083, China)
出处
《计算机工程与应用》
CSCD
北大核心
2016年第18期199-202,共4页
Computer Engineering and Applications
基金
国家自然科学基金(No.61272147)
湖北省教育厅项目(No.B2015446)
关键词
弱信号恢复
三维曲波变换
信噪比
自适应最优阈值
自适应滤波器
recovery of weak signal
3D-curvelet transform
signal to noise ratio
adaptive optimal threshold
adaptive filter
