Characterization of Mountain Drainage Patterns for GPS-Denied UAS Navigation Augmentation

We present a novel approach to use mountain drainage patterns for GPS-Denied navigation of small unmanned aerial systems (UAS such as Scan Eagle), utilizing a down-looking fixed focus monocular imager. We leverage the analogy between mountain drainage patterns, human arteriograms, and human fingerprints. We match local drainage patterns to GPU-rendered parallax occlusion maps of offline geo-registered radar returns (GRRR) in real-time. We represent a given mountain area with a set of spatially distributed minutiae of drainage patterns so that conventional minutiae-based fingerprint matching approaches can be used. We use medical arteriography processing techniques to extract these patterns. The minutiae-based representation of mountains is achieved by exposing mountain ridges/valleys with a series of filters and then extracting mountain minutiae from these ridges/valleys. Effectiveness of minutiae-based mountain representation method is experimentally validated with no human interaction and no human-made geographic objects. Our research was in part funded by Rockwell Collins.