Abstract

For flight automation tolerable to satellite navigation dropouts, this paper presents a simultaneous localization and mapping method based on radar altimeter measurements and monocular camera images. The novelty within mapping is the combination of radar distance and image triangulation. This approach verifies whether the radar measurement fits to a specific horizontal plane in the map, yielding the sub-set of image features that do most probably correspond with the radar measurement. With this map match of the radar altitude, ambiguities in the radar measurement can be resolved. Since unusable radar measurements are suppressed, this method is suitable for positioning in non-flat terrain, e.g. in mountain areas. For matched data, the method estimates a scale correction factor for the image projection rays in order to remove scale ambiguities of the monocular navigation. Together with mapping, vehicle localization is done which is essentially camera resectioning. Localization can be parameterized with the required number of degrees of freedom depending on the availability of additional position sensors. The incremental positioning is tested in kilometer-scale outdoor flights of a 30 kg unmanned airplane as well as in flights with a Cessna 172R equipped with camera and radar sensors. The tests show the benefits of the proposed method in flat and hilly terrain, and demonstrate reduction of accumulation errors down to 2–6% over the distance flown. Some constraints of the method for the altitude range are existent, however it is highlighted that this method will generally work on typical flight profiles.

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