  The calibration of (low-cost) inertial sensors has become increasingly
important over the past years since their use has grown exponentially in many
applications going from unmanned aerial vehicle navigation to 3D-animation.
However, this calibration procedure is often quite problematic since the
signals issued from these sensors have a complex spectral structure and the
methods available to estimate the parameters of these models are either
unstable, computationally intensive and/or statistically inconsistent. This
paper presents a new software platform for inertial sensor calibration based on
the Generalized Method of Wavelet Moments which provides a computationally
efficient, flexible, user-friendly and statistically sound tool to estimate and
select from a wide range of complex models. The software is developed within
the open-source statistical software R and is based on C++ language allowing it
to achieve high computational performance.
