  The calibration of sensors comprising inertial measurement units is crucial
for reliable and accurate navigation. Such calibration is usually performed
with specialized expensive rotary tables or requires sophisticated signal
processing based on iterative minimization of nonlinear functions, which is
prone to get stuck at local minima. We propose a novel calibration algorithm
based on principal component analysis. The algorithm results in a closed-form
formula for the sensor sensitivity axes and scale factors. We illustrate the
proposed algorithm with simulation experiments, in which we assess the
calibration accuracy in the case of calibration of a system consisting of 12
single-axis gyroscopes.
