Energy-Aware Adaptive Attitude Estimation Under External Acceleration for Pedestrian Navigation

In this paper, we consider the problem of a rigid body attitude estimation under external acceleration using a small inertial/magnetic sensors module containing a triad of gyroscope, accelerometer, and magnetometer. This paper is focused on two main challenges. The first one concerns the attitude estimation during dynamic cases, in which external acceleration occurs. In order to compensate for such external acceleration, we design a quaternion-based adaptive Kalman filter q-AKF. Precisely, a smart detector is designed to decide whether the body is in static or dynamic case. Then, the covariance matrix of the external acceleration is estimated to tune the filter gain. The second challenge is related to the energy consumption issue of gyroscope. In order to ensure a longer battery life for the inertial measurement units, we study the way to reduce the gyro measurements acquisition by switching on/off the sensor while maintaining an acceptable attitude estimation. The switching policy is based on the designed detector. The efficiency of the proposed scheme is evaluated by means of numerical simulations and experimental tests.