• Corpus ID: 239016616

Unsupervised Learned Kalman Filtering

  title={Unsupervised Learned Kalman Filtering},
  author={Guy Revach and Nir Shlezinger and Timur Locher and Xiaoyong Ni and Ruud van Sloun and Yonina C. Eldar},
In this paper we adapt KalmanNet, which is a recently proposed deep neural network (DNN)-aided system whose architecture follows the operation of the model-based Kalman filter (KF), to learn its mapping in an unsupervised manner, i.e., without requiring ground-truth states. The unsupervised adaptation is achieved by exploiting the hybrid model-based/data-driven architecture of KalmanNet, which internally predicts the next observation as the KF does. These internal features are then used to… 

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