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

Lau, Buon Kiong; Cook, Gregory J.; Leung, Yee Hong

doi:10.1109/icassp.2004.1326238

Cited by 24 publications

(30 citation statements)

References 15 publications

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“…In this particular case, it shows a good performance at low SNR but the same characteristics is not seen for other DOA scenarios due to mapping errors and bias for NLA. It is more effective for other array geometries and when the number of sensors is large [Lau et al, 2004]. Figure 7 shows the Figure 5.…”

Section: Multipath Signalsmentioning

confidence: 99%

“…We compare the proposed approaches with the same number of sensor ULA and methods in Friedlander and Weiss [1992] and Lau et al [2004]. When two signals, s 1 (t) and s 2 (t) are coherent (multipath case), s 2 (t) = re jf s 1 (t) where r is uniformly distributed in [0.5, 1] and f is also uniformly distributed in [0, 2p] Figure 5 shows the DOA performance when there is no multipath and two sources are at 78 and 80 degrees, respectively.…”

Section: Multipath Signalsmentioning

confidence: 99%

“…A weighted least squares design is used in Lau et al [2004] and further developed in Lau et al [2005] in order to minimize the effects of out of sector sources. This method is compared with Friedlander and Weiss [1992] and Pesavento et al [2002] and it is shown that a better performance can be obtained in certain cases [Lau et al, 2004]. It is based on multi-sector processing and returns highly biased estimates especially when the number of sensors is small.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

2007

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[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,

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Section: Multipath Signalsmentioning

confidence: 99%

Section: Multipath Signalsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

2007

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“…which dovetails with (11). The characteristic of MVDR method is that higher interference power in array generates stronger inhabitation in these directions.…”

Section: Theoretical Analysismentioning

confidence: 99%

“…In Friedlander's Virtual Array Transformation (VAT) method [9], the arbitrary shaped real antenna array can be transformed into virtual antenna array with the Vandermonde manifold by interpolating in the interested array scanning sector. The decorrlation problem in an arbitrary shaped array can be solved by applying the spatial smoothing technique through the virtual array [10][11][12]. Virtual array transformation can increase the degrees of freedom of an antenna array and realize the transformation between different array geometry.…”

Section: Introductionmentioning

confidence: 99%

On Adaptive Beamforming for Coherent Interference Suppression via Virtual Antenna Array

Li¹,

Li²,

Yu³

2012

PIER

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Abstract-In this paper, we propose Modified Interpolated Spatial Smoothing (MISS) algorithm that solves the problem when the inhibition gain generated by Interpolated Spatial Smoothing (ISS) algorithm is not sufficiently high in virtual antenna adaptive beam forming to suppress coherent interference.Using the subspace projection concept, this paper establishes an interference subspace spanned by the interference steering vectors of the virtual antenna array, and then the interference direction information can be imported into the transformation matrix by projecting the transformation matrix into the subspace, which will make the interference components in virtual smoothing covariance matrix enhanced as it is demonstrated by theoretical analysis. Employing the Minimum Variance Distortionless Response (MVDR) beam forming method, the interference inhibition gain and Signal to Interference and Noise Ratio (SINR) performance can be significantly improved.

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An adaptive moving target tracking algorithm for smart antenna systems

Song

Zheng

et al. 2008

J. Electron.(China)

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In wireless communication environment, the time-varying channel and angular spreads caused by multipath fading and the mobility of Mobile Stations (MS) degrade the performance of the conventional Direction-Of-Arrival (DOA) tracking algorithms. On the other hand, although the DOA estimation methods based on the Maximum Likelihood (ML) principle have higher resolution than the beamforming and the subspace based methods, prohibitively heavy computation limits their practical applications. This letter first proposes a new suboptimal DOA estimation algorithm that combines the advantages of the lower complexity of subspace algorithm and the high accuracy of ML based algorithms, and then proposes a Kalman filtering based tracking algorithm to model the dynamic property of directional changes for mobile terminals in such a way that the association between the estimates made at different time points is maintained. At each stage during tracking process, the current suboptimal estimates of DOA are treated as measurements, predicted and updated via a Kalman state equation, hence adaptive tracking of moving MS can be carried out without the need to perform unduly heavy computations. Computer simulation results show that this proposed algorithm has better performance of DOA estimation and tracking of MS than the conventional ML or subspace based algorithms in terms of accuracy and robustness.

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

Cited by 24 publications

References 15 publications

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

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

On Adaptive Beamforming for Coherent Interference Suppression via Virtual Antenna Array

An adaptive moving target tracking algorithm for smart antenna systems

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