Development of a deep learning approach for automotive radar interference suppression
Automotive radars are increasingly being utilized in a wide range of applications, e.g., automated driving systems in vehicles and high performance surveillance drone. With a rise in the number of radars in civil applications, mutual interference between these radars is becoming a growing issue. The focus of this project is to develop a deep learning-based approach to suppress the distortion due to interference in the received radar signal.
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