A tightly integrated image-aided Inertial Navigation System (INS), which copes with GNSS failure, is tested with a realistic data set from an Octocopter. The system integrates the inertial sensor data with position tracks of image feature points over an image sequence in an error-state extended Kalman filter (EKF). The Octocopter is equipped with a rig of three cameras in the horizontal direction with overlapping fields of view. Our main aim is to utilize the data from the three cameras as a single-sensor data. However, as an intermediate experiment, the cameras are considered as three individual sensors and the performance of the image-aided INS with the different combinations of data integration is analyzed in this study. The image-aided INS reduced the drift drastically compared to the drift in free-inertial when integrating the image data sets separately or in combinations. However, the combination of all three data sets together performed poorer than the other combinations, probably due to correlated errors that are not adequately modeled by the current EKF.
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