Vision-Based Terrain Relative Navigation on High-Altitude Balloon and Sub-Orbital Rocket
This addresses navigation challenges for high-altitude vehicles like balloons and rockets, but it is incremental as it builds on existing terrain relative navigation methods.
The paper tackled high-altitude navigation by using a camera-based method to match landmarks from satellite images with camera data, combined with inertial sensors, achieving less than 290 meters of average position error over 150 km on a balloon and less than 55 meters on a rocket.
We present an experimental analysis on the use of a camera-based approach for high-altitude navigation by associating mapped landmarks from a satellite image database to camera images, and by leveraging inertial sensors between camera frames. We evaluate performance of both a sideways-tilted and downward-facing camera on data collected from a World View Enterprises high-altitude balloon with data beginning at an altitude of 33 km and descending to near ground level (4.5 km) with 1.5 hours of flight time. We demonstrate less than 290 meters of average position error over a trajectory of more than 150 kilometers. In addition to showing performance across a range of altitudes, we also demonstrate the robustness of the Terrain Relative Navigation (TRN) method to rapid rotations of the balloon, in some cases exceeding 20 degrees per second, and to camera obstructions caused by both cloud coverage and cords swaying underneath the balloon. Additionally, we evaluate performance on data collected by two cameras inside the capsule of Blue Origin's New Shepard rocket on payload flight NS-23, traveling at speeds up to 880 km/hr, and demonstrate less than 55 meters of average position error.