A sensor model and methodology to estimate the forcing accelerations measured using a novel optomechanical inertial sensor with the inclusion of stochastic bias and measurement noise processes is presented. A Kalman filter for the estimation of instantaneous sensor bias is developed; the outputs from this calibration step are then employed in two different approaches for the estimation of external accelerations applied to the sensor. The performance of the system is demonstrated using simulated measurements and representative values corresponding to a bench-tested 3.76 Hz oscillator. It is shown that the developed methods produce accurate estimates of the bias over a short calibration step. This information enables precise estimates of acceleration over an extended operation period. These results establish the feasibility of reliably precise acceleration estimates using the presented methods in conjunction with state of the art optomechanical sensing technology.
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http://dx.doi.org/10.3390/s21186101 | DOI Listing |
Sensors (Basel)
April 2024
School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.
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View Article and Find Full Text PDFMicromachines (Basel)
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Department of Quantum Metrology, Institute for Quantum Technologies, German Aerospace Center (DLR e.V.), 2022 Wilhem-Runge-Straße 10, 89081 Ulm, Germany.
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