Analysis of interpolated arrays with spatial smoothing

Reddy, K. Maheswara; Reddy, V.U.

doi:10.1016/s0165-1684(97)81486-7

Cited by 7 publications

(5 citation statements)

References 14 publications

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“…Note from (19) that the asymptotic error in the ith DOA estimate is dependent only on the effective error vector Aaf (Oi). The norm of this vector can be shown to decrease with spatial smoothing (see Appendix A of Reddy & Reddy 1996b). Thus, we can expect the smoothing to improve the asymptotic performance of the Root-MUSIC applied to the transformed UCA data.…”

Section: Forward Spatial Smoothingmentioning

confidence: 99%

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Spatial smoothing with uniform circular arrays

Reddy

1998

Sadhana

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In this paper, we extend and analyse spatial smoothing with uniform circular arrays (UCA's). In particular, we study the performance of the Root-MUSIC with smoothing in the presence of correlated sources, finite data perturbations and errors in transformed steering vector that arise due to some approximations made to enable the extension of the Root-MUSIC and smoothing to UCA. Expressions are derived for the asymptotic performance of the Root-MUSIC with smoothing applied to the transformed UCA data. An attempt has been made to bring out the impact of both forward and forward-backward smoothing. Computer simulations are provided to demonstrate the usefulness of the analysis.

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Section: Forward Spatial Smoothingmentioning

confidence: 99%

“…Let us first assume that the sources are uncorrelated. Then the asymptotic error can be shown to be (see Reddy & Reddy 1996b) where…”

Section: Forward Spatial Smoothingmentioning

confidence: 99%

Spatial smoothing with uniform circular arrays

Reddy

1998

Sadhana

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“…Array signal processing has a wide range of applications in radar, communications, sonar, and acoustics. Interpolation or mapping technique from a real antenna array to a virtual antenna array is a popular topic in array signal processing [1]. Virtual array interpolation (mapping) technique was introduced in 1980s [2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

An Effective Technique for Enhancing Direction Finding Performance of Virtual Arrays

Mao

et al. 2014

International Journal of Antennas and Propagation

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The array interpolation technology that is used to establish a virtual array from a real antenna array is widely used in direction finding. The traditional interpolation transformation technology causes significant bias in the directional-of-arrival (DOA) estimation due to its transform errors. In this paper, we proposed a modified interpolation method that significantly reduces bias in the DOA estimation of a virtual antenna array and improves the resolution capability. Using the projection concept, this paper projects the transformation matrix into the real array data covariance matrix; the operation not only enhances the signal subspace but also improves the orthogonality between the signal and noise subspace. Numerical results demonstrate the effectiveness of the proposed method. The proposed method can achieve better DOA estimation accuracy of virtual arrays and has a high resolution performance compared to the traditional interpolation method.

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“…Thus the out-of-sector response is reduced but not totally suppressed. In contrast, in the works of Friedlander et al, see for example [4], [5], and [7]- [10], the transformation matrix is found as the LS solution that best maps the array response vector of the planar array to that of a ULA for a finite set of angles within the in-sector. Although this method is simple, it is intuitively incomplete as it neglects the out-ofsector response.…”

Section: Introductionmentioning

confidence: 96%

“…Practical considerations such as hardware cost and the size and shape of the mounting platform [4], [5] can restrict the choice of array geometry. Moreover, ULAs cannot provide 360° of coverage in the azimuthal plane which is necessary in many applications such as radar, sonar and wireless communications.…”

Section: Introductionmentioning

confidence: 99%

An improved array interpolation approach to DOA estimation in correlated signal environments

Lau

Cook

Leung

2004 IEEE International Conference on Acoustics, Speech, and Signal Processing

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Many popular direction-of-arrival (DOA) estimators rely on the fact that the array response vector of the array is Vandermonde, for example, that of a uniform linear array (ULA). Array interpolation is a preprocessing technique to transform the array response vector of a planar array of arbitrary geometry to that of a ULA over an angular sector. While good approximation within the target sector is attained in the existing array interpolation approaches, the response of the interpolated array in the out-ofsector region is at best partially controlled. Accordingly, out-ofsector signals, especially those highly correlated with the insector signals, can degrade significantly the performance of DOA estimators (e.g., MUSIC with spatial smoothing) that rely on the Vandermonde form to work correctly. In this paper, we propose an improved array interpolation approach that takes into account the array response over the full azimuth. We present also numerical examples to demonstrate the shortcomings of the existing approaches and the effectiveness of our proposal.

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Analysis of interpolated arrays with spatial smoothing

Cited by 7 publications

References 14 publications

Spatial smoothing with uniform circular arrays

Spatial smoothing with uniform circular arrays

An Effective Technique for Enhancing Direction Finding Performance of Virtual Arrays

An improved array interpolation approach to DOA estimation in correlated signal environments

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