ECF-MUSIC: An empirical characteristic function based direction of arrival (DOA) estimation in the presence of impulsive noise

Asghari, Mohsen; Zareinejad, Mohammad; Rezaei, Seyed Mehdi; Amindavar, Hamidreza

doi:10.1016/j.dsp.2022.103440

Cited by 8 publications

(3 citation statements)

References 31 publications

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“…Our main purpose is to build a natural positive definite matrix estimator essential for MUSIC to work in practice. As recently shown in [16], a MUSIC-based α-EC model as follows: combined with Eq. ( 1) and Eq.…”

Section: α-Music: the Proposed Approach To Sslmentioning

confidence: 99%

“…Besides, a natural way to get a positive definite shape matrix was designed in [15] for various complex elliptically contoured distributions. Recent researches also focused on using complex multivariate elliptically contoured α-stable (α-EC) distributions for SSL where parameters are estimated through the empirical characteristic function (ECF) [16]. However, ECF-based algorithm can be tricky to estimate [17].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Elliptically Contoured Alpha-Stable Representation for MUSIC-Based Sound Source Localization

Fontaine

Carlo²,

Sekiguchi

et al. 2022

2022 30th European Signal Processing Conference (EUSIPCO)

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This paper introduces a theoretically-rigorous sound source localization (SSL) method based on a robust extension of the classical multiple signal classification (MUSIC) algorithm. The original SSL method estimates the noise eigenvectors and the MUSIC spectrum by computing the spatial covariance matrix of the observed multichannel signal and then detects the peaks from the spectrum. In this work, the covariance matrix is replaced with the positive definite shape matrix originating from the elliptically contoured α-stable model, which is more suitable under real noisy high-reverberant conditions. Evaluation on synthetic data shows that the proposed method outperforms baseline methods under such adverse conditions, while it is comparable on real data recorded in a mild acoustic condition.

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Section: α-Music: the Proposed Approach To Sslmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Elliptically Contoured Alpha-Stable Representation for MUSIC-Based Sound Source Localization

Fontaine

Carlo²,

Sekiguchi

et al. 2022

2022 30th European Signal Processing Conference (EUSIPCO)

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show abstract

“…The MUSIC method as a solution for multiple snapshots scenario has a high-resolution capability with moderate computational cost [14]. MUSIC is widely used for DoA estimation in array signal processing [15,16] where it is evolved by numerous modified algorithms to enhance both complexity and the accuracy [17,18,19]. It has been used for scatterers profile retrieval in To-moSAR applications [8,20].…”

Section: Introductionmentioning

confidence: 99%

A Sequential MUSIC algorithm for Scatterers Detection 2 in SAR Tomography Enhanced by a Robust Covariance 3 Estimator

Naghavi,

Fazel,

Beheshti

et al. 2022

Preprint

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Synthetic aperture radar (SAR) tomography (TomoSAR) is an appealing tool for the extraction of height information of urban infrastructures. Due to the widespread applications of the MUSIC algorithm in source localization, it is a suitable solution in TomoSAR when multiple snapshots (looks) are available. While the classical MUSIC algorithm aims to estimate the whole reflectivity profile of scatterers, sequential MUSIC algorithms are suited for the detection of sparse point-like scatterers. In this class of methods, successive cancellation is performed through orthogonal complement projections on the MUSIC power spectrum. In this work, a new sequential MUSIC algorithm named recursive covariance canceled MUSIC (RCC-MUSIC), is proposed. This method brings higher accuracy in comparison with the previous sequential methods at the cost of a negligible increase in computational cost. Furthermore, to improve the performance of RCC-MUSIC, it is combined with the recent method of covariance matrix estimation called correlation subspace. Utilizing the correlation subspace method results in a denoised covariance matrix which in turn, increases the accuracy of subspace-based methods. Several numerical examples are presented to compare the performance of the proposed method with the relevant state-of-the-art methods. As a subspace method, simulation results demonstrate the efficiency of the proposed method in terms of estimation accuracy and computational load.

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DOA Estimation of Noncircular Signals Under Impulsive Noise Using a Novel Empirical Characteristic Function-Based MUSIC

Asghari

Zareinejad

Rezaei

et al. 2023

Circuits Syst Signal Process

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ECF-MUSIC: An empirical characteristic function based direction of arrival (DOA) estimation in the presence of impulsive noise

Cited by 8 publications

References 31 publications

Elliptically Contoured Alpha-Stable Representation for MUSIC-Based Sound Source Localization

Elliptically Contoured Alpha-Stable Representation for MUSIC-Based Sound Source Localization

A Sequential MUSIC algorithm for Scatterers Detection 2 in SAR Tomography Enhanced by a Robust Covariance 3 Estimator

DOA Estimation of Noncircular Signals Under Impulsive Noise Using a Novel Empirical Characteristic Function-Based MUSIC

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