MIDW‐Net: A multi‐tasking network architecture for radar intra‐pulse parameter description

Abstract The automatic modulation recognition (AMR) of radar signals has become a popular research topic in recent years. However, most algorithms focus on the type signal and lack further understanding signal. To address this gap, network architecture for multi‐tasking intra‐pulse description words (MIDW‐Net) is proposed herein. In framework, denoising algorithm employs convolutional autoencoder, which an effective method suppressing noise interference preserving information. multiscale feature‐extraction capability feature pyramid (FPN) utilized to expand perceptual domain without losing high‐frequency features image. Finally, AMR parameter estimation are accomplished via multitask learning. Experiments performed simulated using four descriptors verified effectiveness algorithm.