Deterministic and Bayesian Sparse Signal Processing Algorithms for Coherent Multipath Directions-of-Arrival (DOAs) Estimation

Das, Anup

doi:10.1109/joe.2018.2851119

Cited by 15 publications

(5 citation statements)

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“…• firstly, a source is added by solving the global optimization problem (12). To this end, the maximum of η [k] (defined in (13)) is searched on a finite grid, and used as initialization for a local optimization.…”

Section: The Sliding Frank-wolfe Algorithmmentioning

confidence: 99%

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Gridless three-dimensional compressive beamforming with the Sliding Frank-Wolfe algorithm

Chardon

Boureau

2021

The Journal of the Acoustical Society of America

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The application of the Sliding Frank-Wolfe algorithm to gridless compressive beamforming is investigated, for single and multi-snapshots measurements, and estimation of the three-dimensional position of the sources and their amplitudes. Sources are recovered by solving an infinite dimensional optimization problem, promoting sparsity of the solutions, and avoiding the basis mismatch issue. The algorithm does not impose constraints on the source model or the array geometry. A variant of the algorithm is proposed for greedy identification of the sources. Experimental results and Monte-Carlo simulations in three dimensional settings demonstrate the performances of the method, and its numerical efficiency compared to the state of the art.

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Section: The Sliding Frank-wolfe Algorithmmentioning

confidence: 99%

“…A first approach is to approximate a source at an arbitrary point by a source on a finite grid, corrected by an additional term given by a Taylor expansion. The numerical problem is then solved using sparsity based method 10,11 , or sparse Bayesian learning 12,13 .…”

Section: Introductionmentioning

confidence: 99%

Gridless three-dimensional compressive beamforming with the Sliding Frank-Wolfe algorithm

Chardon

Boureau

2021

The Journal of the Acoustical Society of America

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“…These results suggest that the proposed method still maintains better effectiveness and higher robustness compared to its counterparts, even though the number of sources is as many as seven and the target signal is contaminated by real ocean ambient noise. It is worth noting that the signals from different sources are not totally uncorrelated with each other, especially for those encountered in a towed array sonar system [47]- [49]. The magnitudes of correlation are related to the type and working conditions of sources, the frequency and bandwidth of signals, and the underwater environment [50]- [52].…”

Section: Experiments Of Sea Trial Datamentioning

confidence: 99%

Robust Wideband DOA Estimation Based on Element-Space Data Reconstruction in a Multi-Source Environment

Zhu

Fang

et al. 2021

IEEE Access

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In the presence of multiple sources, the performance of direction-of-arrival (DOA) estimation based on beam power maximization is susceptible to the energy leaking from the interference beams to the target beam, especially in the case that the signal of interest (SOI) is quite weak. To address this issue, a robust wideband DOA estimation method is proposed in this paper. Unlike those conventional high-resolution methods which mitigate the influence of energy leakage by reducing beamwidths and sidelobe levels, the proposed method achieves this by directly reconstructing the element-space data to approach the received hydrophone data of the single-source scenario containing only the SOI. Elementspace data reconstruction (ESDR) for the SOI is achieved by removing the element-space waveforms of all the interference signals from the received hydrophone data. Moreover, an iterative algorithm is developed to adaptively extract the element-space waveform of each interference signal, without requiring the prior information of the array amplitude response coefficients and hydrophone coordinates of a distorted towed array. Simulation results show that the proposed method outperforms its counterparts in terms of estimation accuracy for a multi-source scenario. Meanwhile, the DOA estimation performance of the proposed method in a multi-source environment is close to that obtained by the beam power maximization method in the single-source scenario, even if the signal-to-interference ratio (SIR) is as low as-25 dB. At-sea experimental results prove that, even though the number of signal sources is as many as seven and the SOI is contaminated by real ocean ambient noise, the proposed method still achieves a better DOA estimation performance compared to existing state-of-the-art methods. INDEX TERMS Distorted towed array, element-space waveform estimation, energy leakage, multi-source environment, wideband direction-of-arrival (DOA) estimation.

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“…Moreover, the use of excessively dense partitions may lead to column-correlated overcomplete dictionaries that violates the condition for the sparse signal recovery. To settle these problems, many Bayesian algorithms for DOA estimation based on the off-grid model have been proposed [29][30][31][32][33] . However, these methods assume that different subband signals share the same bandwidth, which may not hold true in practice.…”

Section: Introductionmentioning

confidence: 99%

Combined UAMP and MF Message Passing Algorithm for Multi-Target Wideband DOA Estimation with Dirichlet Process Prior

Guan,

Lu,

et al. 2024

Tsinghua Sci. Technol.

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When estimating the direction of arrival (DOA) of wideband signals from multiple sources, the performance of sparse Bayesian methods is influenced by the frequency bands occupied by signals in different directions. This is particularly true when multiple signal frequency bands overlap. Message passing algorithms (MPA) with Dirichlet process (DP) prior can be employed in a sparse Bayesian learning (SBL) framework with high precision. However, existing methods suffer from either high complexity or low precision. To address this, we propose a low-complexity DOA estimation algorithm based on a factor graph. This approach introduces two strong constraints via a stretching transformation of the factor graph. The first constraint separates the observation from the DP prior, enabling the application of the unitary approximate message passing (UAMP) algorithm for simplified inference and mitigation of divergence issues. The second constraint compensates for the deviation in estimation angle caused by the grid mismatch problem. Compared to state-of-the-art algorithms, our proposed method offers higher estimation accuracy and lower complexity.

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Deterministic and Bayesian Sparse Signal Processing Algorithms for Coherent Multipath Directions-of-Arrival (DOAs) Estimation

Cited by 15 publications

References 100 publications

Gridless three-dimensional compressive beamforming with the Sliding Frank-Wolfe algorithm

Gridless three-dimensional compressive beamforming with the Sliding Frank-Wolfe algorithm

Robust Wideband DOA Estimation Based on Element-Space Data Reconstruction in a Multi-Source Environment

Combined UAMP and MF Message Passing Algorithm for Multi-Target Wideband DOA Estimation with Dirichlet Process Prior

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