Abstract
In underwater acoustics, wave propagation can be greatly disrupted by random fluctuations in the ocean environment. In particular, phase measurements of the complex pressure field can be heavily noisy and can defeat conventional direction-of-arrival (DOA) estimation algorithms.
In this paper, we propose a new Bayesian approach to address such phase noise through an informative prior on the measurements. This is combined to a sparse assumption on the directions of arrival to achieve a highly-resolved estimation and integrated into a message-propagation algorithm referred to as the “paSAMP” algorithm (for Phase-Aware Swept Approximate Message Passing). Our algorithm can be seen as an extension of the recent phase-retrieval algorithm “prSAMP” to phase-aware priors.
Experiments on simulated data mimicking real environments demonstrate that paSAMP outperform conventional approaches (e.g. classic beamforming) in terms of DOA estimation. paSAMP also proves to be more robust to additive noise than other variational methods (e.g. based on mean-field approximation).
G. Beaumont—This work has been supported by the DGA MRIS.
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Notes
- 1.
We assume the Bernoulli parameter to be the same for each \(m\in \{1,\ldots ,M\}\).
- 2.
Note in addition that the DOA estimation problem involves a highly-correlated matrix. This further motivates a SwAMP-like approach.
- 3.
- 4.
We justify and develop this point in the technical report [23].
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Acknowledgment
The authors thank Boshra Rajaei for sharing her MATLAB implementation of the prSAMP algorithm.
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Beaumont, G., Fablet, R., Drémeau, A. (2018). An Approximate Message Passing Approach for DOA Estimation in Phase Noisy Environments. In: Deville, Y., Gannot, S., Mason, R., Plumbley, M., Ward, D. (eds) Latent Variable Analysis and Signal Separation. LVA/ICA 2018. Lecture Notes in Computer Science(), vol 10891. Springer, Cham. https://doi.org/10.1007/978-3-319-93764-9_36
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