Register      Login
Publications of the Astronomical Society of Australia Publications of the Astronomical Society of Australia Society
Publications of the Astronomical Society of Australia
RESEARCH ARTICLE

An Efficient Profile Detection Method for Fiber Spectrum Images with Low SNR Based on Wigner Bispectrum

Jia Zhu A , Zhangqin Zhu A and Zhongfu Ye A B
+ Author Affiliations
- Author Affiliations

A Institute of Statistical Signal Processing, Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei 230027, China

B Corresponding author. Email: yezf@ustc.edu.cn

Publications of the Astronomical Society of Australia 28(2) 144-149 https://doi.org/10.1071/AS11012
Submitted: 29 November 10  Accepted: 4 March 11   Published: 22 June 2011

Abstract

A novel profile detection method is proposed for astronomical fiber spectrum data with low signal-to-noise ratio. This approach can be applied to the pretreatment for 2-D astronomical spectrum data before the extraction of spectra. The Wigner bispectrum, a classical higher-order spectrum analysis method, is introduced and applied to deal with the spectrum signal in this article. After analyzing the Wigner higher-order spectra distribution of the target profile signal, the combination of the Wigner bispectrum algorithm and the fast Fourier transform algorithm is used to weaken the effect of the noise to obtain more accurate information. Both the reconstruction method of the Wigner bispectrum and inverse fast Fourier transform are used to acquire the detection signal. At the end of this paper, experiments with both simulated and observed data based on the Large Sky Area Multi-Object Fiber Spectroscopy Telescope project are presented to demonstrate the effectiveness of the proposed method.

Keywords: line: profiles — methods: data analysis — techniques: spectroscopic


References

Benesty, J., Chen, J. D. and Huang, Y. T., 2008, IEEE Trans. Audio Speech Lang. Process., 16(4), 757
Crossref | GoogleScholarGoogle Scholar |

Blondin, S., Walsh, J. R., Leibundgut, B. and Sainton, G., 2005, , 431, A&A, 431, 757
Crossref | GoogleScholarGoogle Scholar |

Chernogor, L. F., Lazorenko, O. V. & Vishnivezky, O. V., 2006, in Proc. Int. Conf. Ultrawideband Ultrashort Impulse Signals 3, 297

Cui, B., Ye, Z. F. and Bai, Z. R., 2008, AcASn, 49(3), 327

de Boer, K. S. and Snijders, M. A. J., 1981, IUENN, 14, 154

Fonollosa, J. R. and Nikias, C. L., 1991, in ICASSP, 5, 3085

Gerr, N. L., 1988, Proc. IEEE, 76(3), 290
Crossref | GoogleScholarGoogle Scholar |

Horne, K., 1986, PASP, 609, 617

Marsh, T. R., 1989, PASP, 98, 609

Piskunov, N. E. and Valenti, J. A., 2002, , 385, A&A, 385, 1095
Crossref | GoogleScholarGoogle Scholar |

Pych, W., 2004, PASP, 116, 148
Crossref | GoogleScholarGoogle Scholar |

Rhoads, J. E., 2000, PASP, 112, 703
Crossref | GoogleScholarGoogle Scholar |

Robertson, J. G., 1986, PASP, 1220, 1231

Sanchez, S. F., 2006, AN, 327, 850

Ville, J., 1948, Cables Transm., 2A, 61

Wigner, E. P., 1932, PhRv, 40, 749

Zhu, Z. Q., Zhu, J. and Ye, Z. F., 2010, Image Signal Process., 3, 4118