Detection and estimation of DOA's of signals via Bayesian predictive densities

@article{Cho1994DetectionAE,
  title={Detection and estimation of DOA's of signals via Bayesian predictive densities},
  author={Chao-Ming Cho and Petar M. Djuric},
  journal={IEEE Trans. Signal Processing},
  year={1994},
  volume={42},
  pages={3051-3060}
}
A new criterion based on Bayesian predictive densities and subspace decomposition is proposed for simultaneous detection of signals impinging on a sensor array and estimation of their direction-of-arrivals (DOA’s). The solution is applicable for both coherent and noncoherent signals and an arbitrary array geometry. The proposed detection criterion is strongly consistent and outperforms the MDL and AIC criteria, particularly for a small number of sensors and/or snapshots, and/or low SNR, without… CONTINUE READING
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