Bayesian Calibration of MEMS Accelerometers

This study aims to investigate the utilization of Bayesian techniques for calibration micro-electro-mechanical systems (MEMS) accelerometers. These devices have garnered substantial interest in various practical applications and typically require through error-correcting functions. The parameters these functions are determined during a process. However, due sources noise, cannot be with precision, making it desirable incorporate uncertainty models. modeling offers natural complete way reflecting by treating model as variables rather than fixed values. Additionally, enables incorporation prior knowledge, an ideal choice calibration. Nevertheless, is infrequently used sensor introduces methods MEMS accelerometer data straightforward manner using recent advances probabilistic programming.