A Novel Noise Elimination Method for MEMS Sensor

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It is inevitable that measured signals are contaminated with noise when MEMS sensor is used for an outdoor measurement. So the obtained signals need noise elimination, which is one of key technologies for signal conditioning. In this paper, a novel noise elimination method based on algorithm of blind source separation (BSS) for MEMS sensor is proposed to separate the source signals from the mixed signals with noises. The BSS algorithm based on maximum signal noise ratio (SNR) is a method of global optimal property, using the characteristic that SNR is maximal when statistically independent source signals are completely separated.The algorithm has a low computational complexity for instantaneous linear mixture signals. It is effective to acquire the source signals from the mixed signals with noises obtained by MEMS sensor,and is successfully verified by simulation experiment of BSS algorithm.The result of noise elimination experiment has achieved signal conditioning and eliminates ambient noises for MEMS sensor signals.

Info:

Periodical:

Edited by:

Xiaohao Wang

Pages:

779-783

DOI:

10.4028/www.scientific.net/KEM.483.779

Citation:

J. H. Lan and Z. C. Liu, "A Novel Noise Elimination Method for MEMS Sensor", Key Engineering Materials, Vol. 483, pp. 779-783, 2011

Online since:

June 2011

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$35.00

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