The invention discloses an ADS-B (Automatic Dependent Surveillance-Broadcast) overlapped signal separation method and equipment based on deep learning and a medium, aiming at solving the inevitable problem of ADS-B signal interleaving. The intelligent detection and separation method based on the deep learning algorithm is provided, the optimal performance can be achieved without accurately calibrating an array, and the method has the advantages that the types of processable signals are diversified, and meanwhile the number of the arrived signals is not limited. Intelligent detection and separation of time-frequency aliasing ADS-B signals are realized through training of a deep learning network and a detection and separation algorithm of the ADS-B signals, and the method has the advantage of wide application.
本发明公开了一种基于深度学习的ADS‑B重叠信号分离方法、设备及介质,针对ADS‑B信号交织不可避免的问题进行解决。提出了一种利用深度学习算法的智能检测与分离方法,不需要精确校准阵列即可达到最佳性能,且具有可处理信号样式多样、同时到达信号个数不限等优点。通过深度学习网络的训练和ADS‑B信号的检测与分离算法实现对时频混叠的ADS‑B信号的智能检测与分离,具有应用广泛的优势。
ADS-B overlapped signal separation method and device based on deep learning, and medium
一种基于深度学习的ADS-B重叠信号分离方法、设备及介质
2023-07-07
Patent
Elektronische Ressource
Chinesisch
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