16 May 2013 Vision assisted aircraft lateral navigation
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Abstract
Surface operation is currently one of the least technologically equipped phases of aircraft operation. The increased air traffic congestion necessitates more aircraft operations in degraded weather and at night. The traditional surface procedures worked well in most cases as airport surfaces have not been congested and airport layouts were less complex. Despite the best efforts of FAA and other safety agencies, runway incursions continue to occur frequently due to incorrect surface operation. Several studies conducted by FAA suggest that pilot induced error contributes significantly to runway incursions. Further, the report attributes pilot’s lack of situational awareness - local (e.g., minimizing lateral deviation), global (e.g., traffic in the vicinity) and route (e.g., distance to next turn) - to the problem. An Enhanced Vision System (EVS) is one concept that is being considered to resolve these issues. These systems use on-board sensors to provide situational awareness under poor visibility conditions. In this paper, we propose the use of an Image processing based system to estimate the aircraft position and orientation relative to taxiway markings to use as lateral guidance aid. We estimate aircraft yaw angle and lateral offset from slope of the taxiway centerline and horizontal position of vanishing line. Unlike automotive applications, several cues such as aircraft maneuvers along assigned route with minimal deviations, clear ground markings, even taxiway surface, limited aircraft speed are available and enable us to implement significant algorithm optimizations. We present experimental results to show high precision navigation accuracy with sensitivity analysis with respect to camera mount, optics, and image processing error.
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Mohamed Ibrahim Mohideen, Mohamed Ibrahim Mohideen, Dinesh Ramegowda, Dinesh Ramegowda, Peter Seiler, Peter Seiler, "Vision assisted aircraft lateral navigation", Proc. SPIE 8737, Degraded Visual Environments: Enhanced, Synthetic, and External Vision Solutions 2013, 873705 (16 May 2013); doi: 10.1117/12.2016339; https://doi.org/10.1117/12.2016339
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