摘要
常用的双极性同步采样方法对瞬变电磁系统的观测噪声具有一定的抑制作用,但在实际工作中其噪声抑制能力仍显不足.本文在双极性同步采样方法基础上提出一种优化方法,以提升瞬变电磁系统的噪声抑制能力,即:通过对取样道加高斯窗函数的方式,赋予取样道内各采样点合适的累加权重,提升系统对取样道内高频噪声的抑制能力;使用高斯窗函数与梳状滤波器构造复合窗函数,通过对包含所有叠加周期的完整观测序列加复合窗函数的形式优化各周期的叠加权重,提升系统对实际工频噪声的抑制能力.对优化前后不同采样函数的谱特性及野外实测数据的处理效果进行比较,结果表明本文提出的方法较传统双极性同步采样方法具有更强的噪声抑制能力.
The bipolar synchronous sampling method is widely used for noise reduction in Transient Electromagnetic Measurement （TEM）. If the noise could be recognized satisfied as the assumption of statistical stationery, this method would be effective theoretically. However, in practice the ability of this method is limited. In this paper, we propose an improved method for optimization of the Instrument Sampling Function （ISF） to enhance the noise reducing ability of the system. A Gauss function is designed and used as a window function for the corresponding gate function to improve the high frequency noise reducing ability and another Gauss function filtered by a notching filter is designed and used as a window function for the weighting function in order to improve the industrial noise reducing ability. Finally we compared the results of data processing with the different instrument sampling functions before and after the optimization. The results prove that this new method has stronger ability in noise reduction for TEM measurement than the traditional bipolar synchronous sampling method.
作者
武欣
薛国强
肖攀
饶丽婷
郭睿
方广有
WU Xin XUE Guo-Qiang XIAO Pan RAO Li-Ting GUO Rui FANG Guang-You(Key Laboratory of Electromagnetic Radiation and Detection Technology, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China Key Laboratory of Mineral Resources, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China University of Chinese Academy of Sciences, Beijing 100049, China)
出处
《地球物理学报》
SCIE
EI
CAS
CSCD
北大核心
2017年第9期3677-3684,共8页
Chinese Journal of Geophysics
基金
国家重大科研装备研制项目"深部资源探测核心装备研发"子项目"航空瞬变电磁勘探仪"(ZDYZ2012-1-03)资助
关键词
瞬变电磁系统
噪声
仪器采样函数
高斯窗
复合窗
梳状滤波器
Transient electromagnetic system
Noise
Instrument sampling function
Gauss function
Complex window function
Notching filter
