Variational Temporal Deep Generative Model for Radar HRRP Target Recognition

@article{Guo2020VariationalTD,
  title={Variational Temporal Deep Generative Model for Radar HRRP Target Recognition},
  author={Dandan Guo and Bo Chen and Wenchao Chen and C. Wang and Hongwei Liu and Mingyuan Zhou},
  journal={IEEE Transactions on Signal Processing},
  year={2020},
  volume={68},
  pages={5795-5809}
}
We develop a recurrent gamma belief network (rGBN) for radar automatic target recognition (RATR) based on high-resolution range profile (HRRP), which characterizes the temporal dependence across the range cells of HRRP. The proposed rGBN adopts a hierarchy of gamma distributions to build its temporal deep generative model. For scalable training and fast out-of-sample prediction, we propose the hybrid of a stochastic-gradient Markov chain Monte Carlo (MCMC) and a recurrent variational inference… 

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