Robust Adaptive Beamforming Using Sequential Quadratic Programming: An Iterative Solution to the Mismatch Problem

Hassanien, Aboulnasr; Vorobyov, Sergiy A.; Wong, K.M.

doi:10.1109/lsp.2008.2001115

Cited by 183 publications

(222 citation statements)

References 14 publications

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“…Therefore, the adaptive monopulse algorithm should be robust to the look direction error. The methods in [11][12][13][14][15][16][17][18][19][20][21] are robust adaptive beamforming (RAB) methods. A shrinkage-based diagonal loading (DL) method is proposed in [11].…”

Section: Introductionmentioning

confidence: 99%

“…In [12], the adaptive beamforming is transformed to a fast Fourier transform based weighted pattern synthesis problem with constraints on beamwidth and peak side lobe level. Robust adaptive beamforming methods based on steering vector estimation (SVE) can be found in [13][14][15][16][17][18][19][20][21]. The SVE-based methods can achieve high performance by adjusting the pattern look direction automatically to the SOI direction.…”

Section: Introductionmentioning

confidence: 99%

“…A modified cost function is proposed in [15] utilizing the subspace-associated power component rather than all power components in the covariance matrix. In [16][17][18], the optimization cost functions for estimating the SOI steering vector are modified and then transformed into convex optimization problems. In [19], the signal steering vector is estimated based on Oracle approximating shrinkage method.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Robust adaptive monopulse algorithm based on main lobe constraints and subspace tracking

Qiu

Sheng

et al. 2017

EURASIP J. Adv. Signal Process.

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In continuous wave (CW) radar and high pulse repetition frequency pulse-Doppler (HPRF-PD) radar, the interference plus noise sample snapshots are hard to be obtained. The desired signal in the received snapshots makes the LCMV-based adaptive monopulse algorithm sensitive to pattern look direction error. A linearly constrained subarray robust adaptive monopulse algorithm based on main lobe maintenance constraint and subspace tracking is developed in this paper. The constraint of main lobe maintenance is obtained by signal subspace projection. The bi-iterative least-square (Bi-LS) subspace tracking is used to update the signal subspace, and a power-associated method is developed to determine the dimension of the projection subspace automatically. The proposed robust adaptive monopulse algorithm can achieve high-angle estimation accuracy and good robustness to look direction error while expending only one additional degree of freedom compared to conventional LCMV-based method.Keywords: Robust adaptive monopulse algorithm, Main lobe maintenance, Subspace tracking, Dimension estimation BackgroundThe monopulse technique is utilized to perform high precision angle estimation for tracking radars. The target's angle is estimated using the ratio of difference to sum beam outputs, called monopulse ratio. Because of the linearity of monopulse ratio in 3dB beamwidth, the target's angle can be estimated bywhere θ 0 and θ s are the angle of the pattern look direction and the target direction, respectively, g (·) is the monopulse ratio, and K θ is the slope of the monopulse ratio.The adaptive array processing is first applied to monopulse technique by Davis [1]. The adaptive monopulse uses adaptive beamforming to form the sum and difference beams and suppress the spatial interferences. For the large-scale adaptive array, computation load and high data rate are two main bottlenecks for realization of the adaptive monopulse method. Subarrray *Correspondence: maxiaofeng@njust.edu.cn School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, China adaptive monopulse method can effectively alleviate such pressures and ensure angle estimation performance when limited number of interferences exist. An example of the subarray geometry is illustrated in Fig. 1a, in which regular and irregular subarray geometries are comprised. Nickel extends the adaptive monopulse technique to subarray and arbitrary array geometries and provides modified formulas of monopulse ratio. Then he systematically analyzes the performance of the adaptive monopulse technique and extends it to space-time processing [2][3][4][5].

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Robust adaptive monopulse algorithm based on main lobe constraints and subspace tracking

Qiu

Sheng

et al. 2017

EURASIP J. Adv. Signal Process.

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“…Recently, iterative-based approaches are considered for adaptive robust beamforming problem. Hassaniean et al [12] proposed a new optimization formulation to find the SV error that is solved iteratively using sequential quadratic programming (SQP). Later, Gu et.…”

Section: Introductionmentioning

confidence: 99%

“…Since the direction of the signal-of-interest (SOI) is nearer to the presumed look-direction, it is possible to distinguish the null's direction associated to the SOI from the interferences. Although numerous capon beamforming algorithms have been proposed [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15], all these algorithms suffer from the problem of saturation in the output SINR as the input SNR increases.…”

Section: Introductionmentioning

confidence: 99%

Robust Adaptive Beamforming Based on Covariance Matrix Reconstruction for Look Direction Mismatch

Mallipeddi¹,

Lie²,

Razul³

et al. 2011

PIER Letters

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Abstract-The performance degradation in traditional adaptive beamformers can be attributed to the imprecise knowledge of the array steering vector and inaccurate estimation of the covariance matrix. The inaccurate estimation of the covariance matrix is due to the limited data samples and presence of desired signal components in the training data. The mismatch between the actual and presumed steering vectors can be mainly due to the error in the look direction estimate. In this paper, we propose a novel algorithm to estimate the look direction and to reconstruct the covariance matrix so that near optimal performance without the effect of saturation can be achieved as the input SNR increases. Numerical results also show that all existing beamforming algorithms suffer from saturation effect as the input SNR increases.

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Robust adaptive phase‐only beamforming algorithm for interference suppression

Sheng

Han

et al. 2014

Adaptive Control & Signal

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The adaptive phase-only beamforming technique is very important for suppressing interferences in phased array radar. However, similar to the conventional beamforming technique, which features variable magnitudes and phases, the performance of phase-only beamforming is severely degraded by steering direction and array geometry errors. No studies on this problem are available. In this paper, the problem of adequate robustness for adaptive phase-only beamformers is investigated, and a robust phase-only beamforming algorithm based on semidefinite relaxation is proposed. This algorithm can suppress interferences by minimizing the array output power and maintain the desired signal without distortion. Robust adaptive phase-only weighting is first converted into a non-convex quadratic optimization problem and then into a convex optimization problem by the semidefinite relaxation technique, which can be solved easily. Experimental results demonstrate that the new robust adaptive phase-only beamforming algorithm can significantly reduce performance degradation caused by various array errors.

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Robust Adaptive Beamforming Using Sequential Quadratic Programming: An Iterative Solution to the Mismatch Problem

Cited by 183 publications

References 14 publications

Robust adaptive monopulse algorithm based on main lobe constraints and subspace tracking

Robust adaptive monopulse algorithm based on main lobe constraints and subspace tracking

Robust Adaptive Beamforming Based on Covariance Matrix Reconstruction for Look Direction Mismatch

Robust adaptive phase‐only beamforming algorithm for interference suppression

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