Multi-source off-grid DOA estimation with single snapshot using non-uniform linear arrays

Ma, Yanan; Cao, Xianbin; Wang, Xiangrong; Greco, Maria; Gini, Fulvio

doi:10.1016/j.sigpro.2021.108238

Cited by 14 publications

(5 citation statements)

References 46 publications

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“…The Cramér-Rao bound (CRB) [24] is drawn as a benchmark for RMSE comparison. Two parameters utilized in (10) are given as η = 10 −5 and µ = σ M ln(M ) [38] with σ denoting the standard deviation of the noise vector, which is assumed to be known a priori in our simulations.…”

Section: Simulationmentioning

confidence: 99%

“…However, this condition may not be satisfied in practice, since the region of interest (ROI) contains infinite candidates and hence grid mismatch almost always exists when we split the ROI into a finite number of grids. This is known as the off-grid issue and has attracted a lot of research interest in array signal processing during the past decade, see for example [8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

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Off-Grid Direction-of-Arrival Estimation Using Second-Order Taylor Approximation

Huang,

So,

Zoubir

2021

Preprint

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The problem of off-grid direction-of-arrival (DOA) estimation is investigated in this paper. We develop a gridbased method to jointly estimate the closest spatial frequency (the sine of DOA) grids, and the gaps between the estimated grids and the corresponding frequencies. By using a second-order Taylor approximation, the data model under the framework of joint-sparse representation is formulated. We point out an important property of the signals of interest in the model, namely the proportionality relationship, which is empirically demonstrated to be useful in the sense that it increases the probability of the mixing matrix satisfying the block restricted isometry property. Simulation examples demonstrate the effectiveness and superiority of the proposed method against several state-of-the-art grid-based approaches.

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Section: Simulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Off-Grid Direction-of-Arrival Estimation Using Second-Order Taylor Approximation

Huang,

So,

Zoubir

2021

Preprint

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“…The direction-of-arrival (DOA) estimation of signals impinging on a sensor array is a well-studied problem in signal processing with a variety of applications, such as communications, radar, and sonar (see, e.g. [1]- [3] and references therein), and various solutions have been proposed [4]- [7]. In particular, the DOA estimation of a seismic signal can be used to determine the seismic source origin, distinguish between different seismic phases, separate waves from various seismic events, such as earthquakes and human-made explosions, and improve the signal-to-noise ratio (SNR) [8].…”

Section: Introductionmentioning

confidence: 99%

Geometry Design for DOA Estimation in Seismic 2D-Arrays: Simulation Study

Katz,

Khatib,

Ben-Horin

et al. 2024

IEEE Access

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Sensor array geometry has a direct impact on the direction-of-arrival (DOA) estimation of a seismic signal. In this paper, we design a planar array that aims to optimize the DOA estimation of a narrowband signal in the sense of the minimum mean-squared-periodic-error (MSPE) obtained by the maximum a-posteriori (MAP) estimator of the DOA. We investigate the MSPE of the MAP estimator as a main design criterion and compare it with the criteria: 1) the cyclic Bayesian Cramér-Rao bound (CBCRB); and 2) the expected log-likelihood (ELL). The theoretical properties of these criteria are discussed. We show that minimizing the CBCRB is equivalent to maximizing the expected Fisher information matrix. Additionally, maximizing the ELL under a uniform prior is equivalent to minimizing the Kullback-Leibler divergence between the posterior PDF and its estimation. The criteria are compared across three different array geometries, specifically: small arrays, uniform circular arrays (UCAs), and concentric circular arrays (CCAs). Simulation results show that 1) direct MAP-MSPE optimization notably exceeds CBCRB-and ELL-based designs, especially in small arrays; 2) UCAs have suboptimal performance compared to noncircular arrays in many scenarios; 3) under the MAP-MSPE criterion, CCAs match unconstrained design performance with lower computational complexity, making them preferable for smaller arrays; 4) for CCAs and larger UCAs, CBCRB and MAP-MSPE designs yield similar results, while the ELL design excels in the case of small UCAs. Our results highlight the need for selecting suitable array geometries and design criteria in accordance with the scenario and array size in order to achieve the best DOA estimation results.INDEX TERMS array design, cyclic Bayesian Cramér-Rao bound (CBCRB), direction-of-arrival (DOA), expected log-likelihood (ELL), minimum mean-squared-periodic-error (MSPE), seismology, seismic array This article has been accepted for publication in IEEE Access.

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“…Thus, some researchers build the off‐grid parameter models for off‐grid estimation to save much computational time. Off‐grid DOA [18] iteratively corrects the DOA by estimating the off‐grid parameter based on a closed‐form estimator. Correlation‐aware sparse Bayesian learning [19] introduces a 1‐D searching procedure to determine the optimal off‐grid parameter and refine DOA estimates.…”

Section: Introductionmentioning

confidence: 99%

Weighted sparse Bayesian method for direction of arrival estimation based on grid fission

Wei

2023

IET Signal Processing

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An off-grid weighted sparse Bayesian learning algorithm based on grid fission for direction of arrival estimation is proposed. The existing grid fission algorithms can use fewer grid points with variant intervals to estimate the true DOAs. However, their learning processes are based on the traditional sparse Bayesian algorithm, which only assigns the same prior distribution assumption to the signals on all grids, but ignores the difference of signal distribution of different grid points. It will result in inaccurate fission location and fission direction because of the insufficient resolution of the spatial spectrum, reducing the estimation accuracy. Moreover, the fission strategy will cost much computation time due to the increase of grid points. To solve these problems, the proposed algorithm utilises the orthogonality of signal subspace and noise subspace to design the weights for prior signal distribution assumption, making the peaks of spatial spectrum more pronounced and easy to distinguish, using more accurate estimated DOAs and offgrid parameter to determine the fission location and direction. In addition, the fission process deletes redundant grid points to simplify calculations. Compared with the existing grid fission algorithms, the proposed method has superior performance in estimation accuracy and computational time.

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Multi-source off-grid DOA estimation with single snapshot using non-uniform linear arrays

Cited by 14 publications

References 46 publications

Off-Grid Direction-of-Arrival Estimation Using Second-Order Taylor Approximation

Off-Grid Direction-of-Arrival Estimation Using Second-Order Taylor Approximation

Geometry Design for DOA Estimation in Seismic 2D-Arrays: Simulation Study

Weighted sparse Bayesian method for direction of arrival estimation based on grid fission

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