Real-time vision-based relative navigation

Eric N. Johnson, Anthony J. Calise, Yoko Watanabe, Jincheol Ha, James C. Neidhoefer

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Scopus citations


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. By applying an Extended Kalman Filter (EKF) 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 (CORSE), 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 (SARSE), 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.

Original languageEnglish (US)
Title of host publicationCollection of Technical Papers - AIAA Guidance, Navigation, and Control Conference 2006
Number of pages46
StatePublished - 2006
EventAIAA Guidance, Navigation, and Control Conference 2006 - Keystone, CO, United States
Duration: Aug 21 2006Aug 24 2006

Publication series

NameCollection of Technical Papers - AIAA Guidance, Navigation, and Control Conference 2006


OtherAIAA Guidance, Navigation, and Control Conference 2006
Country/TerritoryUnited States
CityKeystone, CO

All Science Journal Classification (ASJC) codes

  • Engineering(all)


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