Redundant MEMS-IMU integrated with GPS for performance assessment in sports

In this article, we investigate two different algorithms for the integration of GPS with redundant MEMS-IMUs. Firstly, the inertial measurements are combined in the observation space to generate a synthetic set of data which is then integrated with GPS by the standard algorithms. In the second approach, the method of strapdown navigation needs to be adapted in order to account for the redundant measurements. Both methods are evaluated in experiments where redundant MEMS-IMUs are fixed in different geometries: orthogonally-redundant and skew-redundant IMUs. For the latter configuration, the performance improvement using a synthetic IMU is shown to be 30% on the average. The extended mechanization approach provides slightly better results (about 45% improvement) as the systematic errors of the individual sensors are considered separately rather than their fusion when forming compound measurements. The maximum errors are shown to be reduced even by a factor of 2.