Fusion of enhanced and synthetic vision system images for runway and horizon detection

Fadhil, A. F., Kanneganti, R., Gupta, L., Eberle, H. and Vaidyanathan, R. (2019) Fusion of enhanced and synthetic vision system images for runway and horizon detection. Sensors, 19 (17). 3802. ISSN 1424-8220 doi: 10.3390/s19173802

Abstract/Summary

Networked operation of unmanned air vehicles (UAVs) demands fusion of information from disparate sources for accurate flight control. In this investigation, a novel sensor fusion architecture for detecting aircraft runway and horizons as well as enhancing the awareness of surrounding terrain is introduced based on fusion of enhanced vision system (EVS) and synthetic vision system (SVS) images. EVS and SVS image fusion has yet to be implemented in real-world situations due to signal misalignment. We address this through a registration step to align EVS and SVS images. Four fusion rules combining discrete wavelet transform (DWT) sub-bands are formulated, implemented, and evaluated. The resulting procedure is tested on real EVS-SVS image pairs and pairs containing simulated turbulence. Evaluations reveal that runways and horizons can be detected accurately even in poor visibility. Furthermore, it is demonstrated that different aspects of EVS and SVS images can be emphasized by using different DWT fusion rules. The procedure is autonomous throughout landing, irrespective of weather. The fusion architecture developed in this study holds promise for incorporation into manned heads-up displays (HUDs) and UAV remote displays to assist pilots landing aircraft in poor lighting and varying weather. The algorithm also provides a basis for rule selection in other signal fusion applications.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/86281
Identification Number/DOI	10.3390/s19173802
Refereed	Yes
Divisions	Life Sciences > School of Biological Sciences > Department of Bio-Engineering
Uncontrolled Keywords	Hough transform, image fusion, image registration, intelligent transportation, runway detection, sensing, signal alignment, unmanned aircraft (UAV), wavelet transform
Publisher	MDPI
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