An Improved Motion Compensation Algorithm Based on Discriminant Analysis

Da Lei Song; Zhao Long Su; Yong Fang Wang; Li Ping Chen

doi:10.4028/www.scientific.net/AMR.850-851.918

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 850-851An Improved Motion Compensation Algorithm Based on...

An Improved Motion Compensation Algorithm Based on Discriminant Analysis

Abstract:

Considering the problem that vibration signals which are generated by three-axis accelerations will impact turbulence signal, an improved motion compensation algorithm based on discriminant analysis is proposed. The characteristics of three axis acceleration signals are got by using cross validation discriminant analysis method to test the performance of de-noising among different filtering orders which are got by three-axis accelerations vibration signals. Finally the discriminant function is found to get the optimal filter order. The results of simulation and real sea experiment data statistical analysis shows that the algorithm improves the de-noising performance and can be better applied to ocean turbulence signal de-noising processing.

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Periodical:

Advanced Materials Research (Volumes 850-851)

Pages:

918-921

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.850-851.918

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Online since:

December 2013

Authors:

Da Lei Song*, Zhao Long Su, Yong Fang Wang, Li Ping Chen

Keywords:

Cross Validation Method, Discriminant Analysis, Three-Axis Accelerometer, Turbulence

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References

[1] A. Ganachaud, C. Wunsch: Nature, (2000)408, 453-456.

Google Scholar

[2] Timothy Prestero: Verification of a six-degree of freedom simulation model for the REMUS autonomous underwater vehicle, (2001).

DOI: 10.1575/1912/3040

Google Scholar

[3] Louis Goodman, R. Edward. Levine, G. Rolf. Lueck: Jouranl of Atmospheric and Oceanic Technology, Volume. (2006)23, 977-990.

Google Scholar

[4] A. Arthur. Giordano. M. Frank. Hsu: Least Square Estimation with Applications to Digital Signal Processing. John Wiley & Sons, Inc. New York, NY, USA, (1985).

Google Scholar

[5] Dalei Song, Jingjing Sun, Bing Xue, Chuan Tian: The fixed-point Ocean Turbulence Observation on Submerged Buoy. Intelligent Control, Automatic Detection and High-End Equipment (ICADE), (2012)72-77.

DOI: 10.1109/icade.2012.6330102

Google Scholar

[6] William R. Klecka: Discriminant Analysis.

Google Scholar

[7] R. Kohavi: A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection. Appears in the International Joint Conference on Articial Intelligence (LJCAI). (1995)1137–1143.

Google Scholar

[8] Rolf Lueck: Converting Shear Probe, Thermistors and Microconductivity Signals into Physical Units. Rockland Science International Inc, (2010)1-6.

Google Scholar

[9] Schleher, D. Curtis: MTI and Pulsed Doppler radar. (1991)639.

Google Scholar