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The calibration of (low-cost) inertial sensors has become increasinglyimportant over the past years since their use has grown exponentially in manyapplications going from unmanned aerial vehicle navigation to 3D-animation.However, this calibration procedure is often quite problematic since thesignals issued from these sensors have a complex spectral structure and themethods available to estimate the parameters of these models are eitherunstable, computationally intensive and/or statistically inconsistent. Thispaper presents a new software platform for inertial sensor calibration based onthe Generalized Method of Wavelet Moments which provides a computationallyefficient, flexible, user-friendly and statistically sound tool to estimate andselect from a wide range of complex models. The software is developed withinthe open-source statistical software R and is based on C++ language allowing itto achieve high computational performance.

A Computationally Efficient Framework for Automatic Inertial Sensor Calibration