UKF Filtering of UAV MEMS Gyro Based on Time-Series Model

2011 ◽  
Vol 121-126 ◽  
pp. 4885-4891
Author(s):  
Jia Xu ◽  
Qing Li

The algorithms and the applications of UKF filtering of UAV MEMS Gyro based on time-series model are presented in this paper. First Gyro output signals are preprocessed and modeled by time-series analysis theory, and then use UKF filtering method to compensating error based on the time-series model. Examples with actual experiment demonstrate that the method has apparent superiority. The simulation result shows that, both in static and dynamic cases, after eliminate the precision error MEMS gyro accuracy can achieve the miniature UAV standards.

2013 ◽  
Vol 440 ◽  
pp. 237-242
Author(s):  
Jun Bin Peng ◽  
Xiao Yi Hu ◽  
Yong Jun Liu

Current criteria to judge wheel skid of trains such as velocity difference often cannot recognize wheel skid timely and have no uniform critical value for different trains or railway lines. Aiming at the disadvantages, new criteria based on time series analysis are proposed. With appropriate method of order determination and parameter estimation, AR time series model is established for the data series of velocity difference. Then, Greens function and characteristic equation are constructed with the parameters of the model to determine wheel skid by the convergence state of Greens function or the value of characteristic equations roots. Simulation result shows that the two criteria based on time series model can recognize wheel skid earlier than velocity difference. Moreover, the roots of characteristic equation can also be used as a criterion with a uniform critical value under different application conditions.


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