Scale Transformation for Detecting Transient Electromagnetic Weak Signal of Stochastic Resonance

详细信息   

• 责任者：Wang Guofu (Key Laboratory Cognitive Radio and Information Processing of the Ministry of Education Guil in University of Electronic Technology ; Guilin 541004 ; China) ; Zhang Hairu
• 刊名：Chinese Journal of Geophysics
• 出版年：2011
• 卷期：54(7)
• 关键词：瞬变电磁法 ; transient electromagnetic methods ; 随机过程 ; stochastic processes
• 页码：p.1928-1934
• 图表：3 illus., 1 table, 19 refs.
• 分类号：1600
• 出版序号：973
• issnNo：ISSN0001-5733
• isbnNo：CN11-2074/P

摘要

Transient Electromagnetic （TEM） signal is a large-parameter, multi-frequency signal with unknown frequency, which is weak under heavy noise in the late stage. Stochastic resonance （SR） can only be applied to small parameters, low-frequency or the known high-frequency signal detection. To solve this problem, a scale transformation for detecting TEM weak periodic signal of SR method is presented in this paper. The method is benefited from SR for detecting weak signals. The frequency limit of SR is eliminated by introducing scale transformation. The TEM weak signal is detected from heavy noise under the condition of adiabatic approximation. Theoretical analysis and simulation results show that, to deal with the unknown TEM signal mixed with heavy noise, the frequency of input signal is compressed continuously to achieve a suitable frequency for inputting to stochastic resonance system. According to the change of resonance spectral peak value, the unknown TEM frequencies can be obtained from signal with inverse transform algorithm. Compared with traditional methods, the data collection and theacquisition time is reduced ten times. The deep target signal is detected under limit SNR（SNR≤-50 dB）. The detection accuracy and investigation depth of the instrument is increased by this method.