Precision Navigation Using Pre-Georegistered Map Data
Abstract
Navigation performance in small unmanned aerial vehicles (UAVs) is adversely affected by limitations in current sensor technology for small, lightweight sensors. Because most UAVs are equipped with cameras for mission-related purposes, it is advantageous to utilize the camera to improve the navigation solution. This research improves navigation by matching camera images to a priori georegistered image data and combining this update with existing image-aided navigation technology. The georegistration matching is done by projecting the images into the same plane, extracting features using the techniques Scale Invariant Feature Transform (SIFT) and Speeded-Up Robust Features (SURF). The features are matched using the Random Scale and Consensus (RANSAC) algorithm, which generates a model to transform feature locations from one image to another. In addition to matching the image taken by the UAV to the stored images, the effect of matching the images after transforming one to the perspective of the other is investigated. One of the chief advantages of this method is the ability to provide both an absolute position and attitude update.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 10, 2009
- Accession Number
- ADA506527
Entities
People
- Frederick C. Webber
Organizations
- Air Force Institute of Technology