Based on the Minimum Variance Spectral Estimation of Radar Wind Profile Analysis

Jie Zhou; Jian Xin Hui; Lei Wu; Yu Chun Gao

doi:10.4028/www.scientific.net/AMR.181-182.82

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 181-182Based on the Minimum Variance Spectral Estimation...

Based on the Minimum Variance Spectral Estimation of Radar Wind Profile Analysis

Abstract:

In this paper, we apply minimum variance method for removing automatically ground and intermittent clutter (airplane echo) from wind profiler radar data. Using the concept of discrete multi-resolution analysis and non-parametric estimation theory, we develop Doppler echo power spectral, which allow us to identify the coefficients relevant for clutter and to suppress them in order to effectively restrain and remove clutter and increase the wind profile radar detection range and accuracy; must be on the air back to the effective spectrum of the spectral moments estimation. Using MATLAB simulation analysis , compared with the conventional method of analysis to verify the feasibility and effectiveness of the algorithm, also, try the algorithm is applied to the complexity of the weather with a strong interference case of precipitation particles; Data analysis showed that the actual detection, from the library in the lower spectrum moment estimation has been improved significantly.

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Advanced Materials Science and Technology, ICMST 2010

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Periodical:

Advanced Materials Research (Volumes 181-182)

Pages:

82-87

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.181-182.82

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Online since:

January 2011

Authors:

Jie Zhou, Jian Xin Hui, Lei Wu, Yu Chun Gao

Keywords:

Atmospheric Propagation, Minimum Variance Spectral Estimation (MVSE), Moment Estimation, Radio Science, Signal Processing, Spectral, Wind Profiler Radar

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References

[1] He ping . Phased gust profile radar [M]. beijing：Meteorological Press，(2006).

Google Scholar

[2] Jia peng qun, Zhao zhi qiang, Wu lei. Consultation Report [R]. China Meteorological Administration Training Centre，2007，30.

Google Scholar

[3] Zhu bing，Gao zhong hui . Wind profile radar system in the spectral data processing [J]. Radar，2003，11：21－23.

Google Scholar

[4] Dong de bao. A wind profiling radar spectral moment estimation method [J]. radar，2009，9：40-43.

Google Scholar

[5] Zhi yongfeng Zhang jun Yang bing zheng . Maximum likelihood estimation based on a new signal processing method [J]. Northwestern Polytechnic University 2008，4：180-183.

Google Scholar

[6] Brewster K.A., 1989: Quality control of wind profiler data. Profiler training manual No. 2 developed for the National Weather Service Office of Meteorology, 39pp.

Google Scholar

[7] Merritt D.A., 1995: A statistical averaging method for wind profiler Doppler spectra.J. Atmos. Oceanic Technol., 12, 985–995.

DOI: 10.1175/1520-0426(1995)012<0985:asamfw>2.0.co;2

Google Scholar