Title:
Real-Time Vision-Based Relative Aircraft Navigation
Real-Time Vision-Based Relative Aircraft Navigation
| dc.contributor.author | Johnson, Eric N. | |
| dc.contributor.author | Calise, Anthony J. | |
| dc.contributor.author | Watanabe, Yoko | |
| dc.contributor.author | Ha, Jin-Cheol | |
| dc.contributor.author | Neidhoefer, James C. | |
| dc.contributor.corporatename | Georgia Institute of Technology. School of Aerospace Engineering | |
| dc.date.accessioned | 2010-11-09T21:04:52Z | |
| dc.date.available | 2010-11-09T21:04:52Z | |
| dc.date.issued | 2007-03 | |
| dc.description | Received 22 February 2006; revision received 11 September 2006; accepted for publication 11 September 2006. Copyright © 2007 by Eric N. Johnson, Anthony J. Calise,YokoWatanabe, Jincheol Ha, and James C. Neidhoefer. Published by the American Institute of Aeronautics and Astronautics, Inc., with permission. | en_US |
| dc.description | Published in Journal of Aerospace Computing, Information, and Communication, Vol. 4, Issue 4, January 2004. | |
| dc.description.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. | en_US |
| dc.identifier.citation | Real-Time Vision-Based Relative Aircraft Navigation. Eric N. Johnson, Anthony J. Calise, Yoko Watanabe, Jin-Cheol Ha, James C. Neidhoefer. Journal of Aerospace Computing, Information, and Communication, 4(4):707-738, March, 2007. | en_US |
| dc.identifier.issn | 1542-9423 | |
| dc.identifier.uri | http://hdl.handle.net/1853/35879 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Georgia Institute of Technology | en_US |
| dc.publisher.original | American Institute of Aeronautics and Astronautics, Inc. | |
| dc.subject | Formation flight | en_US |
| dc.subject | Vision | en_US |
| dc.subject | Aircraft navigation | en_US |
| dc.title | Real-Time Vision-Based Relative Aircraft Navigation | en_US |
| dc.type | Text | |
| dc.type.genre | Article | |
| dspace.entity.type | Publication | |
| local.contributor.author | Johnson, Eric N. | |
| local.contributor.corporatename | Daniel Guggenheim School of Aerospace Engineering | |
| local.contributor.corporatename | Aerospace Design Group | |
| local.contributor.corporatename | College of Engineering | |
| local.contributor.corporatename | Unmanned Aerial Vehicle Research Facility | |
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