一种众包空中交通通信网络定位方法
A Localization Approach for Crowdsourced Air Traffic Communication Networks
摘要：
在这项工作中，我们认为，目前最先进的飞机定位方法，如定位是不够的，特别是现代众包空中交通网络与随机的，计划外的部署几何。我们提出了一种替代方案，一个基于网格的定位方法，使用k-最近邻算法，以处理所确定的缺点。我们的建议不需要对现有的空中交通协议和发射机进行任何更改，并且仅使用低成本的商用现成硬件即可轻松实现。使用代数迭代算法进行比较，我们评估我们的方法使用真实世界的飞行数据收集与我们的协作传感器网络OpenSky。我们量化其有效性方面的飞机定位精度，监视范围，并验证错误的位置数据。我们的研究结果表明，基于网格的方法可以增加有效的空中交通监视覆盖范围相比，由高达2.5倍的扩展。由于它不会受到精度衰减的影响，因此它在噪声环境中更加鲁棒，并且在预先存在的计划外接收机部署中表现更好。我们进一步发现，与侦察相比，平均飞机定位精度可以提高高达41%，同时还能够查明从地面进行的潜在欺骗攻击的来源。
英文摘要：
In this work, we argue that current state-of-the-art methods of aircraft localization such as multilateration are insufficient, in particular for modern crowdsourced air traffic networks with random, unplanned deployment geometry. We propose an alternative, a grid-based localization approach using the k-Nearest Neighbor algorithm, to deal with the identified shortcomings. Our proposal does not require any changes to the existing air traffic protocols and transmitters, and is easily implemented using only low-cost, commercial-off-the-shelf hardware. Using an algebraic multilateration algorithm for comparison, we evaluate our approach using real-world flight data collected with our collaborative sensor network OpenSky. We quantify its effectiveness in terms of aircraft location accuracy, surveillance coverage, and the verification of false position data. Our results show that the grid-based approach can increase the effective air traffic surveillance coverage compared to multilateration by a factor of up to 2.5. As it does not suffer from dilution of precision, it is much more robust in noisy environments and performs better in pre-existing, unplanned receiver deployments. We further find that the mean aircraft location accuracy can be increased by up to 41% in comparison with multilateration while also being able to pinpoint the origin of potential spoofing attacks conducted from the ground.
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