Study on Data Fusion of SMR and ADS-B Based on Deep Learning
This paper describes a method of real-time monitoring by using SMR and ADS-B information fusion based on the movement scenes of various aircrafts on the airport scene.In order to solve the problem of unbalanced amount of data collected from different observation sources,this method uses a trained deep learning algorithm for fusion,and compares the error with the most commonly used Kalman filter fusion.The results show that under the condition of unbalanced data information,the method has better accuracy and higher reliability,and has certain engineering application value.
deep learningdata fusionsurface surveillance radarautomatic dependent surveillance-broadcast
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