Autoencoder neural network-based stap algorithm for airborne radar with inadequate training samples

HIGHLIGHTS

• who: Jing Liu et al. from the National Laboratory of Radar Signal Processing, Xidian University, Xi`an, China have published the Article: Autoencoder Neural Network-Based STAP Algorithm for Airborne Radar with Inadequate Training Samples, in the Journal: (JOURNAL)
• what: To overcome this problem this paper proposes a novel autoencoder neural network for clutter suppression with a unique matrix designed to be decoded and encoded. The authors propose an autoencoder neural_network-based STAP algorithm for airborne radar with inadequate training samples. The aim of this paper is to overcome the lack of sufficient IID training . . .
  

   

  

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