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Vision Assisted Aircraft Lateral Navigation

机译:视觉辅助飞机横向导航

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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.
机译:目前,水面运行是飞机运行中技术最少的阶段之一。日益严重的空中交通拥堵使得在恶劣的天气和夜间需要更多的飞机运行。在大多数情况下,传统的水面程序效果很好,因为机场的水面并未拥挤,而且机场的布局也不太复杂。尽管FAA和其他安全机构做出了最大的努力,但由于不正确的地面操作,跑道入侵仍然经常发生。美国联邦航空局(FAA)进行的几项研究表明,飞行员造成的失误极大地影响了跑道的入侵。此外,该报告将飞行员缺乏情况意识的原因归结为该问题:局部(例如,最小化横向偏差),全局(例如,附近的交通)和路线(例如,到下一弯的距离)。增强视觉系统(EVS)是正在考虑解决这些问题的一个概念。这些系统使用车载传感器在可见性差的情况下提供态势感知。在本文中,我们建议使用基于图像处理的系统来估计飞机相对于滑行道标记的位置和方向,以用作侧向导航辅助。我们估计飞机的偏航角和滑行道中心线的坡度以及消失线的水平位置的横向偏移。与汽车应用不同,可以提供多种提示,例如以最小的偏差沿着指定的路线进行飞机操纵,清晰的地面标记,甚至滑行道表面,有限的飞机速度,这些使我们能够实现重要的算法优化。我们提供的实验结果表明,通过对摄像头安装,光学器件和图像处理误差进行灵敏度分析,可以显示高精度的导航精度。

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