MESSAGE COLLISION IDENTIFICATION APPROACH USING MACHINE LEARNING

摘要

Machine learning algorithms, in particular k-nearest neighbors (kNN) and support vector machine (SVM), are employed to estimate the potential success in decodifying ADS-B messages in highly congested areas. The main aim of this study is to optimize automatic dependent surveillance-broadcast (ADS-B) reception on-board low Earth orbit satellites. In this first approach, simulations are performed to obtain the training and testing signals. First, ADS-B communication system is described; second, machine learning, kNN and SVM are introduced. Third, the developed simulator is presented and the kNN and SVM algorithms are described with its results. Finally, the performance of these two is compared.