Hostname: page-component-586b7cd67f-dlnhk Total loading time: 0 Render date: 2024-11-27T23:13:31.140Z Has data issue: false hasContentIssue false
  • English
  • Français

Operation of small sensor payloads on tactical sized unmanned air vehicles

Published online by Cambridge University Press:  03 February 2016

M. C. L. Patterson  and
A. Brescia
M. C. L. Patterson
Affiliation:
[email protected], Department of Engineering, University of Arizona Tucson, Arizona, USA
A. Brescia
Affiliation:
Naval Air Systems Command (NAVAIR), Patuxent River, MD, USA
Get access Rights & Permissions [Opens in a new window]

Abstract

The miniaturisation of sensors has in recent years led to the ability to provide multiple sensor operations from a single Unmanned Aircraft System (UAS) platform. Multiple UAS platforms can be synchronised to link devices from separate UAS platforms thus proving a powerful capability for data collection, while opening up interesting opportunities in the way data is retrieved and used. A range of new sensors being investigated will be discussed with reference to selected case studies that have taken place. As we move into an increasingly growing, data rich environment, data management, quality and pedigree will become of increasing importance. Operations for both defence and non-defence applications will be discussed with reference to the present capability and what is required in future systems. This paper describes some of the sensors currently being evaluated. In the coming years it is expected that we will see a sharp increase in the use of small tactical sized autonomous vehicles in general and a large growth in the capability of the payloads being used.

Type
Research Article
Information
The Aeronautical Journal , Volume 114 , Issue 1157 , July 2010 , pp. 427 - 436
Copyright
Copyright © Royal Aeronautical Society 2010 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Gail, W.B., Remote sensing in the coming decade: the vision and the reality, J of Applied Remote Sensing, 19 January 2007, 1, 012505.Google Scholar
2. Szekielda, K.H., Marmorino, G.O, Maness, S.J, Donato, T, Bowles, J.H, Miller, W.D and Rhea, W.J., Airborne hyperspectral imaging of cyanobacteria accumulations in the Potomac River, J of Applied Remote Sensing, 26 October 2007, 1, 013544.Google Scholar
3. Sugumaran, R., Green, N. and Clayton, M., Monitoring intra-annual water quality variations using airborne hyperspectral remote sensing data in Iowa lakes, J of Applied Remote Sensing, 7 September 2007, 1, 013533.Google Scholar
4. Yang, C., and Everitt, J.H., Evaluating airborne hyperspectral imagery for mapping waterhyacinth infestations, J of Applied Remote Sensing, 15 November 2007, 1, 013546.Google Scholar
5. Cheng, Y-B, Tom, E. and Ustin, S.L., Mapping an invasive species, kudzu (Pueraria montana), using hyperspectral imagery in western Georgia, J of Applied Remote Sensing, 23 May 2007, 1, 013514.Google Scholar
6. Blanco, A., (US Environmental Protection Agency) Private Communications, May 2006.Google Scholar
7. Skidmore, E.L, Dickerson, J.D. and Shimmelpfennig, H., Evaluating surface-soil water content by measuring reflectance, 1975, Soil Sci Soc Am Proc, 39, pp 238–242.Google Scholar
8. Tucker, C.J., Remote sensing of leaf water content in the near infrared, 1980, Rem Sens Environ 10, pp 23–32.Google Scholar
9. Lobell, D.H. and Asner, G.P., Moisture effects on soil reflectance, 2002, Soil Sci Soc Am, 66, pp 722–727.Google Scholar
10. Fletcher, R.S. and Bartels, D.W., Mid-infrared digital electronic camera system for assessing natural resources, J of Applied Remote Sensing, 15 October 2007, 1, 013542.Google Scholar
11. Nasrabadi, N., Tates, M., and Kwon, H., Change detection methods for identification of mines in synthetic aperture radar imagery, J of Applied Remote Sensing, 7 August 2007, 1, 013525.Google Scholar
12. Donaldson, P., Good with Colours, Unmanned Vehicles, October 2007, pp 15 – 19.Google Scholar
13. Eye in the sky uses radio gradiometer to detect IEDs, underground tunnels www.dcmilitary.com/stories/013108/tester_27998.shtml Google Scholar
14. Patterson, M.C.L. and Brescia, A., Requirements driven UAV development, 22nd Bristol UAV Systems Conf Proc, April 2007.Google Scholar
15. Ramanathan, V., Global dimming and its masking effect on global warming, Paper A23D-01, Pres American Geophysical Union Fall Meeting, San Francisco, CA, USA, 11–15 December 2006.Google Scholar
16. Ramanathan, V., Ramana, M., Roberts, G., Kim, D., Corrigan, C., Chung, C. and Winker, D., Warming trends in Asia amplified by brown cloud solar absorption, Nature, 2 August 2007, 448, pp 575–578.Google Scholar
17. Roberts, G., Ramanathan, V., Corrigan, C., Ramana, M., and Nguyen, N., Simultaneous observations of aerosols, clouds, and radio-metric fluxes using light weight autonomous UAVs, Paper A33B-1007, Pres. American Geophysical Union Fall Meeting, San Francisco, CA, USA, 11–15 December 2006.Google Scholar
18. Ramanathan, V., Roberts, G., Ramana, M., Corrigan, C. and Nguyen, N., Simultaneous measurements of direct, semi-direct and indirect aerosol forcing with stacked autonomous UAVs: a new observing platform paper A21G-08, Pres. American Geophysical Union Fall Meeting, San Francisco, CA, USA, 11 – 15 December 2006.Google Scholar
19. Corrigan, C., Ramanathan, V., Ramana, M., Kim, D. and Roberts, G., Chasing black carbon using autonomous unmanned aerial vehicles, Paper A43A-0106, Pres. American Geophysical Union Fall Meeting, San Francisco, CA, USA, 11–15 December 2006.Google Scholar
20. Ramana, M., Ramanathan, V., Corrigan, C., Kim, D., Roberts, G. and Nguyen, N., Direct measurements of albedo and solar absorption over the Northern Indian Ocean with a new observing system of stacked multiple UAVs. Paper A13B-0921, Pres American Geophysical Union Fall Meeting, San Francisco, CA, USA, 11 – 15 December 2006.Google Scholar
21. www.popsci.com/popsci/science/6661e3568cc83110 vgnvcm1000004eecbccdrcrd.htmlGoogle Scholar
22. www.cs.ubc.ca/~mbrown/autostitch/autostitch.html Google Scholar