Study on Threshold Detection of Micro-Seismic Signal Based on Constraint Judgment

Article Preview

Abstract:

Double threshold detection based on constraint judgment is proposed for micro-seismic signal detection. The improvement effect on Probability of False Alarm and influence on Probability of Detection are quantitatively analyzed with constraint judgment. The mathematical models of total PFA and PD of double threshold detection based on constraint judgment are built, and the validity of the mathematical model is verified by simulation tests and experiments. The results show that the signal-to-noise ratio under scheduled PFA and PD Call be decreased by introducing constraint judgment to double threshold detection, and improve the identification accuracy of micro-seismic signal.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 255-260)

Pages:

2898-2903

Citation:

Online since:

May 2011

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2011 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Dai X z, Xu J, Peng Y N, and Xia x J: A new method of improving the weak target detection performance based on the MIMO radar. International Conference on Radar, (2006), p.1~4.

DOI: 10.1109/icr.2006.343265

Google Scholar

[2] Cui Wei, Zhu Xin-guo, and Wu Si-liang: Study on Double Threshold Detection Based on Constraint Judgment. Journal of Electronic & Information Technology. Vol. 31(2009), p.2074~(2078)

Google Scholar

[3] Wang J, Wu S L, and Hou S J: Study of motion target parameters estimation based on high resolution radar. Journal of System Simulation, Vol. 19(2007), p.3005~3008.

Google Scholar

[4] Jin Y W and Friedlander B: A CFAR adaptive subspace detector for second-order Gaussian signals. IEEE Transactions D, Signal Processing, Vol. 53(2005), p.871~884.

DOI: 10.1109/tsp.2004.842196

Google Scholar

[5] Ji CP, and Dai Wei: AE Signal Extraction under the Strong Noise. WSCP 2009.

Google Scholar

[6] Zeng H, Liu L, Tan J, and Tan X H: Time smoothing ML estimation of covariance matrix and performance analysis Journal of System Simulation, Vol. 19(2007), p.4517~4520.

Google Scholar