De-noising stochastic noise in FOG based on second-generation DB4 wavelet and SURE-threshold |
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Authors: | Shuwen Dang Weifeng Tian Zhihua Jin |
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Institution: | (1) Dipartimento di Electrotecnica ed Elettronica, Politecnico di Bari, Via Re Dvid 200, Bari, Italy |
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Abstract: | An effective de-noising method for fiber optic gyroscopes (FOGs) is proposed. This method is based on second-generation Daubechies
D4 (DB4) wavelet transform (WT) and level-dependent threshold estimator called Stein’s unbiased risk estimator (SURE). The
whole approach consists of three critical parts: wavelet decomposition module, parameters estimation module and SURE de-noising
module. First, DB4 wavelet is selected as lifting base of the second-generation wavelet in the decomposition module. Second,
in the parameters estimation module, maximum likelihood estimation (MLE) is used for stochastic noise parameters estimation.
Third, combined with soft threshold de-noising technique, the SURE de-noising module is designed. For comparison, both the
traditional universal threshold wavelet and the second-generation Harr wavelet method are also investigated. The experiment
results show that the computation cost is 40% less than that of the traditional wavelet method. The standard deviation of
de-noised FOG signal is 0.012 and the three noise terms such as angle random walk, bias instability and quantization noise
are reduced to 0.007 2° /ℴh, 0.004 1° / h, and 0.008 1°, respectively. |
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