Abstract
The paper first extends the previous work of the authors dealing with optical flow-based angular rate estimation. Extension means consideration of camera position and orientation relative to the UAV body system (non-aligned camera). After the extension the proposed method is evaluated with virtual reality (Unreal-Carla) image sequences considering simulated aircraft flight trajectories and different frames per second (fps) rates. Based-on the results showing high fps requirements for agile flight scenarios a reversed method is proposed for angular rate sensor fault detection considering the integration of system dynamics based-on angular rate and velocity measurements and comparing the predicted image feature positions with the measured ones. The feature position differences are the error measures completed with up-down counters. The results are promising however, only basic evaluation of the proposed methods is done paving the way for detailed evaluation and development outlined in the conclusion.
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