Finite Length Triple Estimation Algorithm and its Application to Gyroscope MEMS Noise Identification
نویسندگان
چکیده
Abstract The noises associated with MEMS measurements can significantly impact their accuracy. characterised by random walk and bias instability errors strictly depend on temperature effects that are difficult to specify during direct measurements. Therefore, the paper aims estimate fractional noise dynamics of stationary gyroscope based finite length triple estimation algorithm (FLTEA). deals state, order parameter originating from gyroscope, being part popular Inertial Measurement Unit denoted as SparkFun MPU9250. x , y z axes identified using a modified (TEA) approximation length. TEA allows simultaneous systems. Moreover, it is well-known number samples in difference approximations plays key role, we try show influence applying various constraints final results. validation process coming has been conducted for implementation reduction achieving 50% needed no losses. Additionally, capabilities analysis constant variable systems confirmed several numerical examples.
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ژورنال
عنوان ژورنال: Acta Mechanica et Automatica
سال: 2023
ISSN: ['1898-4088', '2300-5319']
DOI: https://doi.org/10.2478/ama-2023-0025