FOG De-noising Method Based on Empirical Mode Decomposition and Allan Variance

2016 ◽  
pp. 299-308
Author(s):  
Shanshan Gu ◽  
Qinghua Zeng ◽  
Jianye Liu ◽  
Weina Chen
Keyword(s):  
Empirical Mode Decomposition ◽  
Allan Variance ◽  
Mode Decomposition

scholarly journals A Gyro Signal Characteristics Analysis Method Based on Empirical Mode Decomposition

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Qinghua Zeng ◽  
Shanshan Gu ◽  
Jianye Liu ◽  
Sheng Liu ◽  
Weina Chen
Keyword(s):  
Frequency Domain ◽  
Empirical Mode Decomposition ◽  
Three Dimensional ◽  
Allan Variance ◽  
Analysis Method ◽  
Time Frequency ◽  
Noise Characteristics ◽  
Mode Decomposition ◽  
Signal Characteristics ◽  
Characteristics Analysis

It is difficult to analyze the nonstationary gyro signal in detail for the Allan variance (AV) analysis method. A novel approach in the time-frequency domain for gyro signal characteristics analysis is proposed based on the empirical mode decomposition and Allan variance (EMDAV). The output signal of gyro is decomposed by empirical mode decomposition (EMD) first, and then the decomposed signal is analyzed by AV algorithm. Consequently, the gyro noise characteristics are demonstrated in the time-frequency domain with a three-dimensional (3D) manner. Practical data of fiber optic gyro (FOG) and MEMS gyro are processed by the AV method and the EMDAV algorithm separately. The results indicate that the details of gyro signal characteristics in different frequency bands can be described with the help of EMDAV, and the analysis dimensions are extended compared with the common AV. The proposed EMDAV, as a complementary tool of the AV, which provides a theoretical reference for the gyro signal preprocessing, is a general approach for the analysis and evaluation of gyro performance.

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