Abstract
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.
Highlights
Accelerometers are used in countless applications including: satellite, aircraft, robotic, and automotive inertial navigation
The use of highly accurate 3D manufacturing solutions has resulted in sensors with precise operating parameters that are uniquely suited to traditional estimation techniques without reliance on complex error models
Using this information a truth model has been generated, from which the displacement time history has been extracted and corrupted by noise to create a simulated measurement set. These noisy measurements are provided to the calibration and acceleration estimation programs
Summary
Accelerometers are used in countless applications including: satellite, aircraft, robotic, and automotive inertial navigation. In the realm of satellite design these devices are used both as navigation equipment [1,2,3,4] and as scientific instrumentation [5,6,7,8,9,10,11]. In both cases the accuracy of the estimated acceleration directly impacts the performance of the system and its ability to meet critical mission requirements. The use of highly accurate 3D manufacturing solutions has resulted in sensors with precise operating parameters that are uniquely suited to traditional estimation techniques without reliance on complex error models
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