Two Stage Kalman Filtering for Position Estimation Using Dual Inertial Measurement Units

Herein a two stage Kalman filter based algorithm is proposed for processing of Inertial Measurement Unit (IMU) data to obtain accurate position estimation over a short period of time. The proposed algorithm uses a novel sensor placement strategy on rigid body. An Extended Kalman filter algorithm incorporates these placement constraints to achieve accurate position estimation. The results show 30% improvement in position estimation as compared to a conventional Dead Reckoning (DR) approach. To the best of the authors' knowledge, the proposed technique is the first which employs spatially separated dual IMUs on a single rigid body for position estimation.