On the application of the global matched filter to DOA estimation with uniform circular arrays

Fuchs, Jean–Jacques

doi:10.1109/icassp.2000.861190

Cited by 57 publications

(100 citation statements)

References 17 publications

Supporting

Mentioning

100

Contrasting

Order By: Relevance

“…There has also been some emerging research of these ideas in the context of spectrum estimation and array processing [10][11][12][13]. Sacchi et al [10] exploit a Cauchy-prior to achieve sparsity in spectrum estimation and work out the resulting optimization problem by iterative approaches.…”

Section: Introductionmentioning

confidence: 99%

“…It was later shown [14] that the algorithm is related to the optimization of L p penalties with p ≤ 1. The work of Fuchs [13] is involved in signal localization in the beamspace domain, under the assumption that the signals are uncorrelated, and the number of snapshots is abundant. The method tries to represent the vector of beamformer outputs to unknown signals as a sparse linear combination of vectors from a basis of beamformer outputs to isolated unit power signals.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An Improved L1-SVD Algorithm Based on Noise Subspace for Doa Estimation

Liu¹,

Lu²,

Wei³

et al. 2012

PIER C

View full text Add to dashboard Cite

Abstract-In this paper, an improved L 1 -SVD algorithm based on noise subspace is presented for direction of arrival (DOA) estimation using reweighted L 1 norm constraint minimization. In the proposed method, the weighted vector is obtained by utilizing the orthogonality between noise subspace and signal subspace spanned by the array manifold matrix. The presented algorithm banishes the nonzero entries whose indices are inside of the row support of the jointly sparse signals by smaller weights and the other entries whose indices are more likely to be outside of the row support of the jointly sparse signals by larger weights. Therefore, the sparsity at the real signal locations can be enhanced by using the presented method. The proposed approach offers a good deal of merits over other DOA techniques. It not only increases robustness to noise, but also enhances resolution in DOA estimation. Furthermore, it is not very sensitive to the incorrect determination of the number of signals and can primely suppress spurious peak in DOA estimation. Simulation results are shown that the presented algorithm has better performance than the existing algorithms, such as MUSIC, L 1 -SVD algorithm.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Improved L1-SVD Algorithm Based on Noise Subspace for Doa Estimation

Liu¹,

Lu²,

Wei³

et al. 2012

PIER C

View full text Add to dashboard Cite

show abstract

“…Therefore, detection and localization of multiple concurrent, often wideband sources is needed. The direction taken here is to use Uniform Circular Arrays (UCAs), because their characteristics are almost invariant with respect to direction [2], therefore not depending on particular room dimensions, and imposing no constraint on the location of the source(s).…”

Section: Introductionmentioning

confidence: 99%

A Sector-Based, Frequency-Domain Approach to Detection and Localization of Multiple Speakers

Lathoud

Magimai-Doss

Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005.

View full text Add to dashboard Cite

Detection and localization of speakers with microphone arrays is a difficult task due to the wideband nature of speech signals, the large amount of overlaps between speakers in spontaneous conversations, and the presence of noise sources. Many existing audio multi-source localization methods rely on prior knowledge of the sectors containing active sources and/or the number of active sources. This paper proposes sector-based, frequency-domain approaches that address both detection and localization problems by measuring relative phases between microphones. The first approach is similar to delay-sum beamforming. The second approach is novel: it relies on systematic optimization of a centroid in phase space, for each sector. It provides major, systematic improvement over the first approach as well as over previous work. Very good results are obtained on more than one hour of recordings in real meeting room conditions, including cases with up to 3 concurrent speakers.

show abstract

“…In particular, uniform circular array (UCA) is extensively utilized in the context of 2-D angle estimation due to its attractive advantages, including 360 azimuthal coverage, almost unchanged directional pattern and additional elevation angle information. Common methods for 2-D angle estimation with UCAs include 2-D multiple emitter location and signal parameter estimation (MUSIC) [1], UCA-real-beam-MUSIC [2], UCA-estimation of signal parameters via rotational invariance techniques (ES-PRIT) [2], modified 2-D MUSIC [3], and global matched filter-based method [4]. Among them, the subspace-based methods [1]- [3] require eigenvalue decomposition and 2-D search while [4] needs only 2-D search.…”

Section: Introductionmentioning

confidence: 99%

“…Common methods for 2-D angle estimation with UCAs include 2-D multiple emitter location and signal parameter estimation (MUSIC) [1], UCA-real-beam-MUSIC [2], UCA-estimation of signal parameters via rotational invariance techniques (ES-PRIT) [2], modified 2-D MUSIC [3], and global matched filter-based method [4]. Among them, the subspace-based methods [1]- [3] require eigenvalue decomposition and 2-D search while [4] needs only 2-D search. Although the phase mode excitation-based UCA-ESPRIT method [2] provides a closed-form solution for the azimuth and elevation angles in the case of a single source, it still necessitates to perform eigenvalue decomposition.…”

Section: Introductionmentioning

confidence: 99%

Simple and Accurate Two-Dimensional Angle Estimation for a Single Source With Uniform Circular Array

2008

Antennas Wirel. Propag. Lett.

View full text Add to dashboard Cite

Abstract-A least squares algorithm for two-dimensional (2-D) angle estimation of a single narrowband source impinging on a uniform circular array (UCA) is presented. Utilizing the centrosymmetric array configuration, a new correlation-based method is devised to obtain closed-form estimates of the azimuth and elevation angles. Although the proposed method is computationally simpler than the conventional schemes, computer simulations show that it can approach optimum estimation performance.Index Terms-Array signal processing, circular array, two-dimensional (2-D) angle estimation.

show abstract

On the application of the global matched filter to DOA estimation with uniform circular arrays

Cited by 57 publications

References 17 publications

An Improved L1-SVD Algorithm Based on Noise Subspace for Doa Estimation

An Improved L1-SVD Algorithm Based on Noise Subspace for Doa Estimation

A Sector-Based, Frequency-Domain Approach to Detection and Localization of Multiple Speakers

Simple and Accurate Two-Dimensional Angle Estimation for a Single Source With Uniform Circular Array

Contact Info

Product

Resources

About