Nonlinear empirical mode predictive drift extraction on fiber optical gyroscope |
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Authors: | Haiting Tian Ruiming Yuan Chunxi Zhang Jing Jin Ningfang Song Song Lin |
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Affiliation: | a North China Electric Power Research Institute Co., Ltd, No. 1, Dizang’an Nanxiang, Fuxingmenwai Dajie, Xicheng District, Beijing, China b Institute of Opto-Electronic Technology, Beihang University, No. 37 Xueyuan Road, Haidian Block, Beijing 100191, PR China |
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Abstract: | The integration drift of inertial unit is a fatal error on navigation and attitude determination system. Many approaches have been developed to extract and eliminate it. A novel fiber optical gyroscope drift extraction algorithm was proposed in this paper to ameliorate the performance of fiber optical gyroscope by extracting the trend component as the compensation. In this algorithm, the attitude quaternion of stellar sensor and the output of fiber optical gyroscope were imported into a nonlinear empirical mode predictive algorithm to extract the drift component of gyroscope. Combing the advantages of predictive filter and empirical mode decomposition in nonlinear signal processing, our proposal is more precise in drift extraction and data approximation. Software simulation and hardware verifications on gyroscope were launched, in which the results had proven the capability of the algorithm. |
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Keywords: | Attitude determination Stellar sensor Gyroscope Model error filter |
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