Analysis of Pseudo-Random Sequence Correlation Identification Parameters and Anti-Noise Performance
Xijin Song,
Xuelong Wang,
Zhao Dong,
Xiaojiao Zhao and
Xudong Feng
Additional contact information
Xijin Song: Key Laboratory of Photoelectric Logging and Detecting of Oil and Gas, Ministry of Education, Xi’an Shiyou University, Xi’an 710065, China
Xuelong Wang: Key Laboratory of Photoelectric Logging and Detecting of Oil and Gas, Ministry of Education, Xi’an Shiyou University, Xi’an 710065, China
Zhao Dong: The Oil Production Technology Research Institute of the First Oil Production Factory of the Chang Qing Oil Field, Yan’an 716000, China
Xiaojiao Zhao: Key Laboratory of Photoelectric Logging and Detecting of Oil and Gas, Ministry of Education, Xi’an Shiyou University, Xi’an 710065, China
Xudong Feng: Key Laboratory of Photoelectric Logging and Detecting of Oil and Gas, Ministry of Education, Xi’an Shiyou University, Xi’an 710065, China
Energies, 2018, vol. 11, issue 10, 1-18
Abstract:
Using a pseudo-random sequence to encode the transmitted waveform can significantly improve the working efficiency and depth of detection of electromagnetic exploration. The selection of parameters of pseudo-random sequence plays an important role in correlation identification and noise suppression. A discrete cycle correlation identification method for extracting the earth impulse response is proposed. It can suppress the distortion in the early stage of the excitation field and the glitches of the cross correlation function by traditional method. This effectively improves the accuracy of correlation identification. The influence of the order and the cycles of m-series pseudo-random coding on its autocorrelation properties is studied. The numerical results show that, with the increase of the order of m-sequence, the maximum out-of-phase periodic autocorrelation function decreases rapidly. Therefore, it is very beneficial to achieve synchronization. The limited-cycle m-sequences have good autocorrelation properties. As the period of the m-sequence increases and the width of the symbol decreases, the overall autocorrelation becomes closer to the impact function. The discussion of the influence of symbol width and period of m-sequence on its frequency bandwidth and power spectral density shows that the narrower the symbol width, the wider its occupied band. The longer the period, the smaller the power spectral line spacing. The abilities of m-sequence to suppress DC (Direct-current) interference, Schumann frequency noise, and sine-wave noise are analyzed. Numerical results show that the m-sequence has excellent ability to suppress DC interference and Schumann frequency noise. However, for high-order harmonic noise, the correlation identification error appears severe oscillation in the middle and late stages of the impulse response. It indicates that the ability of m-sequence to suppress high-frequency sinusoidal noise is deteriorated. In practical applications, the parameters of the transmitted waveform should be reasonably selected in combination with factors including transmitter performance, hardware noise, and ambient noise level to achieve the best identification effect.
Keywords: pseudo random sequence; impulse response of the earth; correlation identification; anti-noise performance (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://www.mdpi.com/1996-1073/11/10/2586/pdf (application/pdf)
https://www.mdpi.com/1996-1073/11/10/2586/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:11:y:2018:i:10:p:2586-:d:172510
Access Statistics for this article
Energies is currently edited by Ms. Agatha Cao
More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().