A Mixing Vector Based an Affine Combination of Two Adaptive Filters for Sensor Array Beamforming

Sun, Jinping; Wang, Guohua; Lu, Yilong

doi:10.2528/pier11090204

Cited by 4 publications

(3 citation statements)

References 39 publications

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“…A versatile approach of array signal processing is beamforming [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19], which is used to detect and enhance a desired signal while suppressing interference and noise at the output of an array of sensors. It is well known that the benefits brought by beamforming such as signal-to-noise ratio enhancement and spatial resolution are restricted by the ratio of array aperture size relative to the working wavelength.…”

Section: Introductionmentioning

confidence: 99%

Robust Superdirective Beamforming for Hf Circular Receive Antenna Arrays

Zhou¹,

Gao²,

Zhang³

et al. 2013

PIER

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Abstract-Superdirective beamforming can highly reduce the aperture size of high-frequency receive array. At the same time, the closely spaced elements of a small aperture array can make it low efficiency and sensitivity to the array uncertainty, which limit its application in practice. Using a parameter called sensitivity factor, we found that array efficiency and robustness against array error could be considered simultaneously. On that basis, we derive a novel superdirective beamforming criterion based on a constrained sensitivity factor for the HF circular receive array. New method is analytical and computationally inexpensive. Through making the directive gain with a given sensitivity factor maximum, we calculate the optimal weights of the array elements. To illustrate the proposed method can increase the acceptance of HF superdirective receive arrays in practice, several numerical results are provided.

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Section: Introductionmentioning

confidence: 99%

Robust Superdirective Beamforming for Hf Circular Receive Antenna Arrays

Zhou¹,

Gao²,

Zhang³

et al. 2013

PIER

View full text Add to dashboard Cite

show abstract

“…Angleof-arrival (AOA) estimation [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18] and beamforming [19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38] have been main research topics of the array signal processing. Note that array signal processing can also be applied to radar signal processing [39][40][41][42][43].…”

Section: Introductionmentioning

confidence: 99%

Efficient Implementation of the Capon Beamforming Using the Levenberg-Marquardt Scheme for Two Dimensional Aoa Estimation

Cho¹,

Lee²

2013

PIER

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Abstract-In this paper, we adopt the Levenberg-Marquardt (LM) algorithm to implement the nonlinear multivariable optimization for azimuth/elevation angle-of-arrival (AOA) estimation based on the Capon beamforming algorithm. The formulation is based on the fact that the cost function of the Capon algorithm can be expressed in a least-squares form. The performance in terms of the root mean square error (RMSE) and the computational complexity is illustrated via numerical results.

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“…Thus, many techniques have been proposed to improve the robustness of adaptive beamformers in the past decades ( [8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23], and many references therein). One popular and widely used approach is the so-called diagonal loading technique [5], where the array covariance matrix is diagonally loaded with a scaled identity matrix.…”

Section: Introductionmentioning

confidence: 99%

Robust Adaptive Beamforming Against Array Calibration Errors

Yang¹,

Zhao²,

Liu³

2013

PIER

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Abstract-Adaptive beamforming methods degrade in the presence of model mismatch. In this paper, we develop a modified interference covariance matrix reconstruction based beamformer that is robust against large array calibration errors. The calibration errors can come from the element position errors, and/or amplitude and phase errors, etc.. The proposed method is based on the fact that the sample covariance matrix can approximate the interference covariance matrix properly when the desired signal is small, and a reconstructed covariance matrix based on the Capon spectral will be better than the sample covariance matrix when the desired signal is large. A weighted summation of two covariance matrices in references is used to reconstruct the interference covariance matrix. Moreover, a computationally efficient convex optimization-based algorithm is used to estimate the mismatch of the steering vector associated with the desired signal. Several simulation cases are applied to show the superiority of the proposed method over other robust adaptive beamformers.

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A Mixing Vector Based an Affine Combination of Two Adaptive Filters for Sensor Array Beamforming

Cited by 4 publications

References 39 publications

Robust Superdirective Beamforming for Hf Circular Receive Antenna Arrays

Robust Superdirective Beamforming for Hf Circular Receive Antenna Arrays

Efficient Implementation of the Capon Beamforming Using the Levenberg-Marquardt Scheme for Two Dimensional Aoa Estimation

Robust Adaptive Beamforming Against Array Calibration Errors

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