Stochastic modeling of inertial sensor errors
Residual random errors remain in inertial sensor data even after calibrating them. This is mainly because of the noise associated with inertial sensors. Although these noise are random, they are correlated in nature, which enables us to model them stochastically. This stochastic model can be included in INS error models for various applications. In this project, different error modeling schemes are analyzed.
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