- Volume 15 Issue 3
We present a system for the real-time visual relative navigation of a fixed-wing unmanned aerial vehicle in a GPS-denied environment. An extended Kalman filter is used to construct a vision-aided navigation system by fusing the image processing results with barometer and inertial sensor measurements. Using a mean-shift object tracking algorithm, an onboard vision system provides pixel measurements to the navigation filter. The filter is slightly modified to deal with delayed measurements from the vision system. The image processing algorithm and the navigation filter are verified by flight tests. The results show that the proposed aerial system is able to maintain circling around a target without using GPS data.
unmanned aerial vehicle;target tracking;relative navigation;delayed measurement;GPS-denied;vision-aided navigation;extended Kalman filter
- JAVNTS Center., "Vulnerability assessment of the transport infrastructure relying on the global positioning system", Office of the Assistant Secretary for Transportation Policy. U. S. Department of Transportation, 2001.
- King, A. D., "Inertial navigation-past, present, and future", In IEE Colloquium on Airborne Navigation Systems Workshop. Digest 1997/169, 1999.
- Johannessen, R., "The role of GPS in flight calibration", In IEE Colloquium on Current Future Trends Flight Calibration Radio Navigational Aids, 1991.
- Djederich, P., "Global navigation satellite systems", In IEE Airborne Navigational Aids, 1998.
- Watanabe, Y., Fabiani, P. and Vesnerais, G. L., "Simultaneous visual target tracking and navigation in a GPS-denied environment", IEEE International Conference on Advance Robotics, Munich, 2009.
- Comaniciu, D., Ramesh, V. and Meer, P., "Kernel-based object tracking", IEEE Transaction on pattern analysis and machine intelligence, Vol. 25, No. 5, 2003, pp.564-577. https://doi.org/10.1109/TPAMI.2003.1195991
- Barber, D. B., Redding, J. D., McLain, T. W., Beard, R. W. and Taylor, C. N., "Vision-based target geo-location using fixed-wing miniature air vehicle", J Intell Robot Syst, Vol. 47, No. 4. 2006, pp. 361-382. DOI:10.1007/s10846-006-9088-7 https://doi.org/10.1007/s10846-006-9088-7
- Lim, S., Kim, Y., Lee, D. and Bang, H., "Standoff target tracking using a vector field for multiple unmanned aircrafts", Journal of Intelligent & Robotic Systems, Vol. 69, No. 1-4, pp. 347-360. 2013. DOI: 10.1007/s10846-012-9765-7 https://doi.org/10.1007/s10846-012-9765-7
- Brown, R. and Hwang, P., Introduction to Random Signals and Applied Kalman Filtering, John Wiley & Sons,1997
- Bletzacker, et al., "Kalman Filter Design for Integration of Phase III GPS with an Inertial Navigation System" Computing Applications Software Technology Technical Papers, Los Alamitos, CA , 1988.
- Larsen, T. D., Andersen, N. A. and Ravn, O., "Incorporation of time delayed measurements in a discretetime Kalman filter" Proceedings of the 37th IEEE Conference on Decision & Control, Tampa, Florida, 1998.
- Monocular Vision-Based Guidance and Control for a Formation Flight vol.16, pp.4, 2015, https://doi.org/10.5139/IJASS.2015.16.4.581
- High-Precision Heading Determination Based on the Sun for Mars Rover vol.2018, pp.1687-7977, 2018, https://doi.org/10.1155/2018/1493954
- A low-cost solution for unmanned aerial vehicle navigation in a global positioning system–denied environment vol.14, pp.6, 2018, https://doi.org/10.1177/1550147718781750
Supported by : Ministry of Knowledge Economy (MKE)