A note on redundancy averaging

Indukumar, K.C.; Reddy, V.U.

doi:10.1109/78.124962

Cited by 24 publications

(9 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…An alternative approach to spatial smoothing for the ACM construction is lag redundancy averaging (LRA) [8], [24], [25]. This technique averages lag estimates from different sensor pairs of equal separation to exploit co-array redundancies and then replaces the individual estimates at that lag by their average [23], [26]. As a result, the correlation estimates populating the ACM have reduced variances.…”

Section: B Lra-based Covariance Matrix Augmentationmentioning

confidence: 99%

Wideband source enumeration and direction-of-arrival estimation using sparse array periodogram averaging in low snapshot scenarios

Yang

Buck

2017

The Journal of the Acoustical Society of America

View full text Add to dashboard Cite

This paper proposes a new sparse array source enumeration algorithm for underdetermined scenarios with more sources than sensors. The proposed algorithm decomposes the wideband signals into multiple uncorrelated frequency bands, computes the narrowband spatial periodograms and then averages periodograms to reinforce the sources' spectral information. The inverse spatial Fourier transform of the wideband periodogram estimates the spatial correlation function, which then populates the diagonals of a Hermitian Toeplitz augmented covariance matrix (ACM) after lag redundancy averaging. A modified minimum description length (MDL) criteria, termed MDLgap, is proposed for source enumeration using the eigenvalues of the constructed ACM. MDLgap provably never overestimates the number of sources present, and is asymptotically consistent when the signals present span a limited dynamic range. Numerical simulations show that the proposed MDLgap algorithm achieves improved performance over existing approaches for underdetermined source enumeration, especially in low snapshot scenarios.

show abstract

Section: B Lra-based Covariance Matrix Augmentationmentioning

confidence: 99%

Wideband source enumeration and direction-of-arrival estimation using sparse array periodogram averaging in low snapshot scenarios

Yang

Buck

2017

The Journal of the Acoustical Society of America

View full text Add to dashboard Cite

show abstract

“…After that, we sequentially redetermineΘ 1 ,Θ 2 , · · · ,Θ k and iteratively update these DOA estimates until convergence is achieved (see lines [8][9][10][11][12][13][14][15][16][17][18]. AOP-DOA stops when all of the K outer loops finished.…”

Section: Implementation Of Aop-doamentioning

confidence: 99%

“…However, the algorithm of redundancy averaging leads to biased DOA estimates [14], and the FBSS algorithm suffers from performance degradation due to the array aperture loss [15], [16]. On the other hand, iterative algorithms, including the alternating projection (AP) technique [17], [18] and the modified Gauss-Newton technique [19] are investigated to circumvent the multivariate nonlinear optimization procedure.…”

Section: Introductionmentioning

confidence: 99%

DOA Estimation of Uncorrelated, Partly Correlated and Coherent Signals Using Alternating Oblique Projection

Hou¹,

Mao²

2017

RADIOENGINEERING

View full text Add to dashboard Cite

show abstract

“…This cannot be done effectively by using R and some kind of covariance matrix correction should be done. One of the most effective methods for this purpose is DAA [Abramovich et al, 1999;Pillai and Haber, 1987;Indukumar and Reddy, 1992].…”

Section: Finding An Initial Doa Estimatementioning

confidence: 99%

Direction of arrival estimation for nonuniform linear arrays by using array interpolation

2007

View full text Add to dashboard Cite

[1] A new approach is proposed for DOA estimation in nonuniform linear arrays (NLA) based on array interpolation. A Wiener formulation is presented to improve the condition number of the mapping matrix as well as the performance for noisy observations. Noniterative and iterative methods for DOA estimation are proposed. These methods use an initial DOA which is then significantly improved by the subsequent processing. Partially augmentable nonredundant arrays (PANA) and partly filled NLA (PFNLA) are considered and initial DOA is found in a different manner for each of these arrays. PANA are used for noncoherent sources whereas PFNLA are employed when the sources are coherent. Array interpolation is used to map the sample covariance matrix of the NLA to the covariance matrix of a uniform linear array (ULA) with the same aperture size and root-MUSIC is employed as a fast subspace algorithm for DOA estimation. Proposed methods overcome some of the limitations of the conventional array interpolation. DOA estimation problem is considered for correlated and coherent sources. Proposed approaches are compared with two previous methods as well as the spectral MUSIC and root-MUSIC algorithms applied on the NLA and ULA, respectively. It is shown that DOA performance is significantly improved for a wide variety of DOA scenarios.Citation: Tuncer, T. E., T. K. Yasar, and B. Friedlander (2007), Direction of arrival estimation for nonuniform linear arrays by using array interpolation, Radio Sci., 42, RS4002,

show abstract

A note on redundancy averaging

Cited by 24 publications

References 6 publications

Wideband source enumeration and direction-of-arrival estimation using sparse array periodogram averaging in low snapshot scenarios

Wideband source enumeration and direction-of-arrival estimation using sparse array periodogram averaging in low snapshot scenarios

DOA Estimation of Uncorrelated, Partly Correlated and Coherent Signals Using Alternating Oblique Projection

Direction of arrival estimation for nonuniform linear arrays by using array interpolation

Contact Info

Product

Resources

About