全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...
Algorithms  2011 

Radio Frequency Interference Detection and Mitigation Algorithms Based on Spectrogram Analysis

DOI: 10.3390/a4040239

Keywords: radiometry, spectrogram, RFI, detection, mitigation

Full-Text   Cite this paper   Add to My Lib

Abstract:

Radio Frequency Interference (RFI) detection and mitigation algorithms based on a signal’s spectrogram (frequency and time domain representation) are presented. The radiometric signal’s spectrogram is treated as an image, and therefore image processing techniques are applied to detect and mitigate RFI by two-dimensional filtering. A series of Monte-Carlo simulations have been performed to evaluate the performance of a simple thresholding algorithm and a modified two-dimensional Wiener filter.

References

[1]  Skou, N.; Sidharth, M.; S?bj?rg, S.S.; Balling, J.E.; Kristensen, S.S. RFI as Experienced During Preparations for the SMOS Mission. Proceeding of International Union of Radio Science; General Assembly (URSI), Chicago, IL, USA, 7–16 August 2008.
[2]  Ellingson, S.W.; Johnson, J.T. A polarimetric survey of radio-frequency interference in C- and X-bands in the continental United States using WindSat radiometry. IEEE Trans. Geosci. Remote Sens. 2006, 44, 540–548.
[3]  Ruf, C.S.; Misra, S. Detection of Radio Frequency Interference with the Aquarius Radiometer. Proceedings of IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2007), Barcelona, Spain, 23–28 July 2007; pp. 2722–2725.
[4]  Guner, B.; Johnson, J.T.; Niamswaun, N. Time and frequency blanking for radio frequency interference mitigation in microwave radiometry. IEEE Trans. Geosci. Remote Sens. 2007, 45, 3672–3679.
[5]  Ruf, C.S.; Gross, S.M.; Misra, S. RFI detection and mitigation for microwave radiometry with an agile digital detector. IEEE Trans. Geosci. Remote Sens. 2006, 44, 694–706.
[6]  Tarongi, J.M.; Camps, A. Normality analysis for RFI detection in microwave radiometry. Remote Sens. 2010, 2, 191–210.
[7]  Johnson, J.T.; Potter, L.C. Performance Study of Algorithms for Detecting Pulsed Sinusoidal Interference in Microwave Radiometry. IEEE Trans. Geosci. Remote Sens. 2009, 47, 628–636.
[8]  Offringa, A.R.; de Bruyn, A.G.; Biehl, M.; Zaroubi, S.; Bernardi, G.; Pandey, V.N. Post-correlation radio frequency interference classification methods. Mon. Not. R. Astron. Soc. 2010, 405, 155–167.
[9]  Winkel, B.; Kerp, J.; Stanko, S. RFI detection by automated feature extraction and statistical analysis. Astron. Nachr. 2007, 238, 68–79.
[10]  Williston, K. Frequency Domain Processing. In Digital Signal Processing: World Class Designs, 1st ed. ed.; Elsevier: Burlington, VT, USA, 2009; pp. 141–142.
[11]  Tenreiro, J.A.; Rudas, I.J.; Patkai, B. Intelligent Robotics. In Intelligent Engineering Systems and Computational Cybernetics, 1st ed. ed.; Springerlink: Berlin, Germany, 2009; pp. 56–58.
[12]  Jackson, L.B. Discrete Fourier Transform. In Digital Filters and Signal Processing, 5th ed. ed.; Kluwer Academic Publishers: Norwell, MA, USA, 2002; p. 205.
[13]  Harris, F.J. On the use for windows for harmonic analysis with the discrete Fourier transform. Proc. IEEE 1978, 66, 51–83.
[14]  Smith, J.O.; Serra, X. PARSHL: An Analysis/Synthesis Program for Non-Harmonic Sounds Based on a Sinusoidal Representation. Proceedings of International Computer Music Conference, Urbana, IL, USA, 23–26 August, 1987; pp. 290–297.
[15]  Nelson, W.B. Basic Concepts and Distributions for Product Life. In Applied Life Data Analysis, 1st ed. ed.; John Wiley & Sons: Hoboken, NJ, USA, 2004; p. 41.
[16]  Lee, J.S. Digital image enhancement and noise filtering by use of local statistics. IEEE Trans. Pattern Anal. Mach. Intell. 1980, PAMI-2, 165–168.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133