UM2000 Spectrum Estimation Using Multiple Signal Classification Method

Shen Liu; Fu Ping Wang; Xiu Cheng Liu

doi:10.4028/www.scientific.net/AMR.734-737.2622

Paper Titles

Testing Apparatus Design of High-Concentration Slurry Transport in Environment-Friendly Dredging
p.2603

A Telemetry and Telecontrol Universal Simulator
p.2609

Automation Control Method of Time-Varying in Heat Conduction Coefficient and Pure Steam Output Interference
p.2613

The Extraction and Identification of Target Infrared Image Signature Based on Instantaneous Polarization
p.2618

UM2000 Spectrum Estimation Using Multiple Signal Classification Method
p.2622

Research Status of Broken Belt Protector in Belt Conveyor
p.2630

Algorithm Study of the Models Merge Based on Delaunay Triangulation
p.2634

Analysis of Variable Section Piezoelectric Harvester
p.2638

Automated Design of Mechanical System for Generating Alternate Mechanism Concepts
p.2642

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 734-737UM2000 Spectrum Estimation Using Multiple Signal...

UM2000 Spectrum Estimation Using Multiple Signal Classification Method

Abstract:

This paper focused on UM2000 signal spectrum estimation using MUSIC algorithm. Because of the limitation of data window length, traditional frequency discrimination methods fail to meet the requirement of high frequency resolution. In this paper, the influence of SNR on MUSIC spectrum estimation is analyzed and MDL (minimum description length) principle is used to determine the dimension of the signal. Simulation results based on several other modern spectral estimation methods are also presented and compared with that of MUSIC method, from which the superiority of MUSIC method is verified.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 734-737)

Pages:

2622-2629

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.734-737.2622

Citation:

Cite this paper

Online since:

August 2013

Authors:

Shen Liu, Fu Ping Wang, Xiu Cheng Liu

Keywords:

Frequency Resolution, Locomotive Track Circuit, Music, Spectrum Estimation, UM2000

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Guangshu Hu. Digital signal processing: Tsinghua University Press, 2003. (In Chinese)

Google Scholar

[2] Schmidt R.O. Multiple emitter location and signal parameter estimation. IEEE Trans. Antennas Propag. 1986, 34(March):276~280

DOI: 10.1109/tap.1986.1143830

Google Scholar

[3] Burg J.P. The relationship between maximum entropy and maximum likelihood spectra. Geophysics, 1972, 37: 375~376

DOI: 10.1190/1.1440265

Google Scholar

[4] Cadzow J.A. Spectral estimation: an overdetermined rational model equation approach. Proc. IEEE, 1982, 70(Sept): 907~938

DOI: 10.1109/proc.1982.12424

Google Scholar

[5] Yongliang Wang, Hui Chen. Space spectrum estimation theory and algorithm: Tsinghua University Press, 2004 (In Chinese)

Google Scholar

[6] Min Shi, Zhengguo Wu, Weiming Yin. Inter-harmonic parameter estimation based on multi-signal classification and prony method. Power System Technology. 2005, 29(Aug): 81~84 (In Chinese)

Google Scholar

[7] Wax M, Kailath T. Detection of signals by information theoretic criteria. IEEE Tran. on ASSP, 1985, 33(2): 387~392

DOI: 10.1109/tassp.1985.1164557

Google Scholar

[8] Xin Wang, Chunhui Zhao, Jiangang Rong. MUSIC signal frequency Estimation Algorithm based on MDL principle. Journal of Data Acquisition and Processing. 2008, 23(Sep)

Google Scholar

[9] Barron A.R, Cover T.M. Minimum complexity density estimation[J]. IEEE Transactions on Information Theory, 1991, 37(4): 1034-1054

DOI: 10.1109/18.86996

Google Scholar