A MEMS random error analysis method fused with genetic algorithm

Duanyang Gao; An Li; Jun Fu; Ruichen Zhang

doi:10.1117/12.2504183

31 August 2018 A MEMS random error analysis method fused with genetic algorithm

Duanyang Gao, An Li, Jun Fu, Ruichen Zhang

Proceedings Volume 10835, Global Intelligence Industry Conference (GIIC 2018); 1083510 (2018) https://doi.org/10.1117/12.2504183
Event: Global Intelligent Industry Conference 2018, 2018, Beijing, China

Abstract

According to the characteristics of the random errors of MIMU, an Allan variance analysis method fused with genetic algorithm is proposed, which can effectively evaluate the different random errors. Firstly, how to analyze and identify the errors of inertial devices by Allan variance analysis method is introduced in detail. Then, according to the characteristics of genetic algorithm that can achieve global optimum, an Allan variance analysis method fused with genetic algorithm is proposed. Finally, by long-time experiment to test the MEMS inertial devices of three different manufacturers, the measured data of gyro and accelerometer are processed and compared respectively, and the numerical results of each random error have been calculated, which proved the validity of the method. This method combines genetic algorithm with Allan variance analysis method, providing a new idea for the theoretical study of random error field in MEMS inertial devices.

Citation Download Citation

Duanyang Gao, An Li, Jun Fu, and Ruichen Zhang "A MEMS random error analysis method fused with genetic algorithm", Proc. SPIE 10835, Global Intelligence Industry Conference (GIIC 2018), 1083510 (31 August 2018); https://doi.org/10.1117/12.2504183

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