An attitude estimation algorithm is developed using an adaptive extended Kalman filter for low-cost micro tion algorithm is proposed\nfor fusing triaxial gyroscope and accelerometer measurements. An extended Kalman filter is implemented to estiate attitude in\ndirection cosine matrix (DCM) formation and to calibrate gyroscope biases online.We use a variable measurement covariance for\nacceleration measurements to ensure robustness against temporary non gravitational accelerations, which usually induce errors\nwhen estimating attitude with ordinary algorithms. The proposed algorithm enables accurate gyroscope online calibration by\nusing only a triaxial gyroscope and accelerometer. It outperforms comparable state-of-the-art algorithms in those cases when\nthere are either biases in the gyroscope measurements or large temporary non gravitational accelerations present. A low-cost,\ntemperature-based calibration method is also discussed for initially calibrating gyroscope and acceleration sensors. An open source\nimplementation of the algorithm is also available.
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