Kim Euiho, Seo Jiwon
Department of Mechanical & System Design Engineering, Hongik University, 94, Wausan-ro, Mapo-gu, Seoul 04066, Korea.
School of Integrated Technology, Yonsei University, 85 Songdogwahak-ro, Incheon 21983, Korea.
Sensors (Basel). 2017 Sep 22;17(10):2183. doi: 10.3390/s17102183.
In the Federal Aviation Administration's (FAA) performance based navigation strategy announced in 2016, the FAA stated that it would retain and expand the Distance Measuring Equipment (DME) infrastructure to ensure resilient aircraft navigation capability during the event of a Global Navigation Satellite System (GNSS) outage. However, the main drawback of the DME as a GNSS back up system is that it requires a significant expansion of the current DME ground infrastructure due to its poor distance measuring accuracy over 100 m. The paper introduces a method to improve DME distance measuring accuracy by using a new DME pulse shape. The proposed pulse shape was developed by using Genetic Algorithms and is less susceptible to multipath effects so that the ranging error reduces by 36.0-77.3% when compared to the Gaussian and Smoothed Concave Polygon DME pulses, depending on noise environment.
在联邦航空管理局(FAA)于2016年宣布的基于性能的导航战略中,FAA表示将保留并扩展测距设备(DME)基础设施,以确保在全球导航卫星系统(GNSS)中断时具备可靠的飞机导航能力。然而,DME作为GNSS备份系统的主要缺点是,由于其在超过100米的距离测量精度较差,需要大幅扩展当前的DME地面基础设施。本文介绍了一种通过使用新的DME脉冲形状来提高DME距离测量精度的方法。所提出的脉冲形状是通过遗传算法开发的,对多径效应的敏感度较低,因此与高斯和光滑凹多边形DME脉冲相比,根据噪声环境的不同,测距误差可降低36.0 - 77.3%。