Multi-Aspect Target Classification and Detection via the Infinite Hidden Markov Model

@article{Ni2007MultiAspectTC,
  title={Multi-Aspect Target Classification and Detection via the Infinite Hidden Markov Model},
  author={Kai Ni and Yuting Qi and Lawrence Carin},
  journal={2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07},
  year={2007},
  volume={2},
  pages={II-433-II-436}
}
A new multi-aspect target detection method is presented based on the infinite hidden Markov model (iHMM). The scattering of waves from multiple targets is modeled as an iHMM with the number of underlying states treated as infinite, from which a full posterior distribution on the number of states associated with the targets is inferred and the target-dependent states are learned collectively. A set of Dirichlet processes (DPs) are used to define the rows of the HMM transition matrix and these… CONTINUE READING