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

Aida Makni (1) , Hassen Fourati (1) , Alain Kibangou (1)

1 NECS - Networked Controlled Systems

In this paper, we consider the problem of rigid bodyattitudeestimationunderexternalaccelerationusingasmallinertial/magneticsensors module containing a triad of gyroscope, accelerometer,andmagnetometer.Thepaperisfocusedontwomainchallenges. The first challenge concerns the attitude estimationduring dynamic case, in which external acceleration occurs. Thislatter leads to lose performance in attitude estimation methods. Aquaternion-based adaptive Kalman filter (q-AKF) compensatingexternal acceleration from the residual in the accelerometer isdesigned. At each step, the covariance matrix of the externalacceleration is estimated to tune the filter gain adaptively. Thesecond challenge is related to the energy consumption issue ofgyroscope. In order to ensure a longer battery life for the InertialMeasurement Units (IMUs), we study the way to reduce the gyromeasurements acquisition by switching on/off the sensor whilemaintaining an acceptable attitude estimation. A smart detectionapproach isproposed to decide whether the body is indynamic orstatic case. The efficiency of the q-AKF is demonstrated throughnumerical simulations and experimental tests.

Keywords: quaternion; dynamic and static cases; Attitude estimation; adaptive Kalman filter; detection

Domains: Automatic

Aida Makni, Hassen Fourati, Alain Kibangou. Energy-aware Adaptive Attitude Estimation Under External Acceleration for Pedestrian Navigation. IEEE/ASME Transactions on Mechatronics, 2016, 21 (3), pp.1366-1375. ⟨10.1109/TMECH.2015.2509783⟩. ⟨hal-01241403⟩