scholarly journals Application of Fast Dynamic Allan Variance for the Characterization of FOGs-Based Measurement While Drilling

Sensors ◽  
2016 ◽  
Vol 16 (12) ◽  
pp. 2078 ◽  
Author(s):  
Lu Wang ◽  
Chunxi Zhang ◽  
Shuang Gao ◽  
Tao Wang ◽  
Tie Lin ◽  
...  
Keyword(s):  
Allan Variance ◽  
Measurement While Drilling ◽  
Fast Dynamic

scholarly journals Application of Improved Fast Dynamic Allan Variance for the Characterization of MEMS Gyroscope on UAV

2018 ◽  
Vol 2018 ◽  
pp. 1-6 ◽  
Author(s):  
Qian Zhang ◽  
Xueyun Wang ◽  
Shiqian Wang ◽  
Chaoying Pei
Keyword(s):  
Microelectromechanical Systems ◽  
Computation Time ◽  
Allan Variance ◽  
Mems Sensors ◽  
Mems Gyroscope ◽  
Core Components ◽  
Practical Tool ◽  
And Performance ◽  
Fast Dynamic

Microelectromechanical systems (MEMS) are core components in unmanned aerial vehicles (UAV). The precision of MEMS sensors is very important when the GPS signal is invalid. However, the precision and performance of MEMS sensors will be degraded by the changing of environment. Therefore, estimation and identification of the various noise terms existing in MEMS sensors are deemed to be necessary. The Allan variance is a common and standard method to analyze MEMS sensors, but it cannot be used to analyze the dynamic characteristics. The dynamic Allan variance (DAVAR) is a sliding version of the Allan variance. It is a practical tool that could represent the nonstationary behavior of the MEMS signal. As the DAVAR needs to estimate the Allan variance at each time epoch, the computation time grows significantly with the length of the signal series. In this paper, in the case of MEMS gyroscope on UAV, an improved fast DAVAR algorithm based on the choice of relevant time is proposed to shorten the computation time. As an experimental validation, numerical experiments are conducted under the proposed method. The results demonstrate that the improved method could greatly increase the computation speed and does not affect the accuracy of estimation.

scholarly journals Characterization of error sources in an inertial unit using Allan variance and nonlinear parameter adjustment

2020 ◽  
Vol 1674 ◽  
pp. 012004
Author(s):  
W A Hernandez ◽  
J S Castillo-Corredor ◽  
J A Ramos-Cifuentes ◽  
F Fuentes ◽  
L F Castañeda
Keyword(s):  
Allan Variance ◽  
Nonlinear Parameter ◽  
Error Sources ◽  
Parameter Adjustment ◽  
Inertial Unit

scholarly journals Characterization of Received Signal Strength Perturbations Using Allan Variance

2018 ◽  
Vol 54 (2) ◽  
pp. 873-889 ◽  
Author(s):  
Chunbo Luo ◽  
Pablo Casaseca-de-la-Higuera ◽  
Sally McClean ◽  
Gerard Parr ◽  
Peng Ren
Keyword(s):  
Signal Strength ◽  
Received Signal Strength ◽  
Allan Variance

Characterization of digitizer timebase jitter by means of the Allan variance

2003 ◽  
Vol 25 (1) ◽  
pp. 15-22 ◽  
Author(s):  
Pasquale Arpaia ◽  
Pasquale Daponte ◽  
Sergio Rapuano
Keyword(s):  
Allan Variance
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