Data fusion of MIMU and GPS was commonly used to estimate the displacement and tracking of a quadrotor UAV. Meanwhile, inaccurate estimation of displacement during dynamic motion is oftentimes occurred. This error caused by noise and limited sampling rate of the sensor mainly occurs when the quadrotor changes its attitude rapidly to generate an instantaneous horizontal force. This paper proposes a data fusion based on single Kalman filter to estimate orientation and displacement. An experiment was also performed to verify the displacement accuracy, i.e. in one-axis as well as multiple axes sensor movements. The algorithm fuses data from MIMU and GPS sensors so that the acceleration data is filled in at points where GPS data is not available. With this method, the predicted displacement from the MIMU sensor can be corrected every second with data from GPS and results in an accurate estimated displacement and trajectory.
Displacement estimation and tracking of quadrotor UAV in dynamic motion
Freddy Kurniawan, Muhammad Ridlo Erdata Nasution, Harliyus Agustian, Lasmadi; Displacement estimation and tracking of quadrotor UAV in dynamic motion. AIP Conf. Proc. 2 June 2023; 2601 (1): 020008. https://doi.org/10.1063/5.0142633
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