磁记忆梯度张量测量信号预处理方法  

Metal magnetic memory gradient tensor signal processing method

作　　者：陈海龙[1] 王长龙[1] 左宪章[1] 朱红运[1] CHEN Hailong WANG Changlong ZUO Xianzhang ZHU Hongyun(Department of Unmanned Aerial Vehicles Engineering, Ordnance Engineering College, Shijiazhuang 050003, Chin)

机构地区：[1]军械工程学院无人机工程系,河北石家庄050003

出　　处：《系统工程与电子技术》2017年第3期488-493,共6页Systems Engineering and Electronics

基　　金：河北省自然科学基金(E2015506004)资助课题

摘　　要：为降低磁记忆测量信号中各种噪声干扰,提高磁记忆信号梯度张量解算精度,提出形态滤波和经验模态分解组合的方法消除噪声。首先,根据矢量合成原理将磁分量信号转换成总场幅值和方向信号,保证降噪处理过程中不改变各磁分量之间的内在关系;然后,利用形态滤波器对幅值和方向信号进行处理,消除信号中的瞬时强脉冲噪声;最后,将信号进行经验模态分解降噪,消除低频和局部干扰噪声。将上述方法用于磁记忆实测信号处理,结果表明,提出的方法能有效消除磁分量信号不同类型干扰噪声,解算得到高精度的磁记忆梯度张量数据。In order to improve the precision of metal magnetic memory （MMM） gradient tensor data, a method that combines the morphological filter and empirical mode decomposition（EMD） is proposed. To preserve the inter relation information between different magnetic field components while removing the noises, the data of magnetic field component is transformed into magnetic total-field strength and direction firstly. Then the data of magnetic field strength and direction is processed by the morphological filter to eliminate the influence of the instantaneous strong pulse. Finally, the processed data is decomposed with EMD to eliminate the influence of stochastic noise. An experiment on the actually acquired data is carried out to verify the proposed method, and the result shows that this method can effectively eliminate the noises in magnetic field components measurement signals and receive highprecision data of magnetic memory gradient tensor.

关 键 词：磁记忆 梯度张量 经验模态分解 形态滤波 降噪 

分 类 号：TN911.72[电子电信—通信与信息系统] TH878[电子电信—信息与通信工程]