Deep Learning for Large-Scale Real-World ACARS and ADS-B Radio Signal Classification

no code implementations • 20 Apr 2019 • Shichuan Chen, Shilian Zheng, Lifeng Yang, Xiaoniu Yang

In order to verify the performance of the deep learning-based radio signal classification on real-world radio signal data, in this paper we conduct experiments on large-scale real-world ACARS and ADS-B signal data with sample sizes of 900, 000 and 13, 000, 000, respectively, and with categories of 3, 143 and 5, 157 respectively.

Classification General Classification +2