Real-Time Vision-Based Relative Aircraft Navigation
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Abstract
This paper describes two vision-based techniques for the navigation of an aircraft relative
to an airborne target using only information from a single camera fixed to the aircraft. These
techniques are motivated by problems such as "see and avoid", pursuit, formation flying,
and in-air refueling. By applying an Extended Kalman Filter for relative state estimation,
both the velocity and position of the aircraft relative to the target can be estimated. While
relative states such as bearing can be estimated fairly easily, estimating the range to the
target is more difficult because it requires achieving valid depth perception with a single
camera. The two techniques presented here offer distinct solutions to this problem. The
first technique, Center Only Relative State Estimation, uses optimal control to generate an
optimal (sinusoidal) trajectory to a desired location relative to the target that results in
accurate range-to-target estimates while making minimal demands on the image processing
system.The second technique, Subtended Angle Relative State Estimation, uses more rigorous
image processing to arrive at a valid range estimate without requiring the aircraft to follow
a prescribed path. Simulation results indicate that both methods yield range estimates of
comparable accuracy while placing different demands on the aircraft and its systems.
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2007-03
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