Most UAVs use a GPS-based auto-landing system. However, GPS systems can fail, either through natural interference or
deliberate jamming. To safely operate in the national airspace, UAVs must include a backup auto-landing system. At 21st
Century Systems, Inc., we are developing a vision-based landing system capable of replacing GPS when GPS fails.
Existing structure-from-motion techniques operate on two frames of video. These techniques find a collection of salient
features in each frame. They correctly match the features between the two frames and then use epipolar geometry to
calculate distances to each feature. Unfortunately, these techniques are too computationally complex to meet our realtime
Instead, we have developed two closed-formed solutions that provide real-time calculations of the runway's relative
position from a single frame of video. Our first approach calculates the distance and orientation based on rectangular
features whose size and position are known. Precision runways have many standardized rectangular markings, providing
the opportunity to create multiple rectangular templates. In our approach, we use advanced image processing to identify
the feature points of these templates, and then calculate the distance to each template, combining the results across
multiple templates to reduce the effects of noise. The second approach incorporates additional pose information directly
from the UAV's internal compass and IMU. This both reduces the effect of noise from our image processing, and allows
us to calculate the UAV's pose relative to the runway from an arbitrary set of features. We are no longer limited to
rectangle shaped templates.