Complementary filtering (CF) is a well known method that can effectively fuse a gyroscope and accelerometer measurement in order to robustly estimate the attitude of a rigid body in a planar single degree of freedom (DOF) setting. The attitude can be estimated individually by either integrating the gyroscope measurement or by calculating the inverse tangent of the components of a 2-axis accelerometer. The gyroscope can adequately estimate the angle in the higher frequency region, but suffers from drift issues at low frequency, whereas the accelerometer can accurately measure the acceleration and thus direction of gravity, but loses this accuracy when faced with motion accelerations. CF traditionally uses linear time invariant filters, however, this paper presents an extension to the CF method by proposing time-varying parameters. A fuzzy logic method is developed to adjust the parameters. Stability analysis as well as experimental results are presented to verify the proposed method.
['Evan Chang-Siu', 'Masayoshi Tomizuka', 'Kyoungchul Kong']
Time-varying complementary filtering for attitude estimation