We present an alternative by using a compact source of geo-referenced data and representing it in a sparse but salient manner, which while offering large coverage area, is accurate, and open-source.Ĭelik et. Nonetheless it presents a big-data problem worthy of a large scale data center. Since all UAS include a monocular imager as part of their standard equipage, absolute navigation with real-time aerial images versus a geo-referenced map is an attractive idea. Without GPS, position, velocity and attitude (PVA) solution obtained from even highest quality inertial and air data sensors are subject to drift. However, GPS being essentially a radio it is subject to denial due to signal blockage or interference, as well as receiver malfunction. GPS is a critical global coverage sensor for small Unmanned Air Systems (UAS). This research was in part funded by Rockwell Collins Inc.
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Furthermore, we study how to select landmarks for UAS navigation based on the proposed mountain representation and give a set of examples to show its feasibility. Our results are experimentally validated on actual terrain data and show the effectiveness of minutiae-based mountain representation method.
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The minutiae-based representation of mountains is achieved by first exposing mountain ridges and valleys with a series of filters and then extracting mountain minutiae from these ridges/valleys. We use medical arteriography processing techniques to extract the patterns. For recognition purposes, we represent a given mountain area with a set of spatially distributed mountain minutiae, i.e., details found in the drainage patterns, so that conventional minutiae-based fingerprint matching approaches can be used to match real-time camera image against template images in the training set. The matching occurs in real-time, while GRRR data is loaded on-board the aircraft pre-mission, so as not to require a scanning aperture radar during the mission. Details of our actual GPU algorithm is beyond the subject of this paper, and is planned as a future paper. We leverage the analogy between mountain drainage patterns, human arteriograms, and human fingerprints, to match local drainage patterns to Graphics Processing Unit (GPU) rendered parallax occlusion maps of geo-registered radar returns (GRRR). Our proposal allows extension of missions to GPS-denied mountain areas, with no assumption of human-made geographic objects.
In this way, you can contact us for any suggestions and improvements in a few clicks.We present a novel approach to use mountain drainage patterns for GPS-Denied navigation of small unmanned aerial systems (UAS) such as the ScanEagle, utilizing a down-looking fixed focus monocular imager. Feedback can be sent directly from the application. Moreover, the application is available in 7 languages (English, French, German, Spanish, Italian, Japanese and Chinese). This version has been optimized for macOS High Sierra and later. This avoids many potential problems with OEM software. MakerNotes tags may be edited but not created or deleted. More than 90 image formats are supported (HEIC, MOS, CR2, CR3, DNG, NEF, NRW, JPEG, PNG, TIFF, RAW, and much more).
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The application is designed for professional needs. In this way, you can directly inspect your photos from Photos.app. The application even includes a Photos extension. In this way, the application fits your personal needs. Besides, users can customize the displayed tags in the preferences. Moreover, a special interface is provided for geographical and thumbnail data. The application has been designed to improve your workflow. It is the first editor that allows you to edit EXIF, IPTC and XMP tags as well as MakerNotes in a beautiful and familiar interface. MetaImage is the ultimate tool to read, write and edit images metadata.
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