An adaptive antenna array under directional constraint

Takao, K.; Fujita, Masafumi; Nishi, Toshiya

doi:10.1109/tap.1976.1141411

Cited by 179 publications

(94 citation statements)

References 14 publications

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“…This algorithm adjusts an array of sensors in real time to respond to a desired signal from a chosen direction while discriminating against noise received from other directions. The concept of adaptive systems working on the principle of minimizing the output noise power under the constrained response to specified directions, is also described in various papers [20][21][22][23][24]. One surprising result obtained by Buckley and his colleagues [24], is the observation that employing derivative constraints by linearly-constrained systems is highly dependent upon the location of the phase reference point of the array.…”

Section: Brief Literature Reviewmentioning

confidence: 99%

Study of beamforming techniques for ultrasound imaging in nondestructive testing

1996

NDT & E International

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Section: Brief Literature Reviewmentioning

confidence: 99%

Study of beamforming techniques for ultrasound imaging in nondestructive testing

1996

NDT & E International

View full text Add to dashboard Cite

“…During the past decade, several approaches, such as imposing multiple gain constraints in different directions in the vicinity of the presumed SV [1], diagonal loading [2], placing derivative constraints on the presumed SV [3] and eigenspace-based approaches [4], have been proposed to improve the robustness of adaptive beamformer design. The diagonal loading [2] has the advantage of being invariant to the type of mismatches but the choice of the loading factor is not obvious.…”

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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“…Any violation or mismatch between the assumed (nominal) and the actual knowledge will cause a substantial degradation in their performance [4]. Several approaches to improve their robustness were proposed over the past decade [5][6][7]. However, many of the proposed methods are limited to certain type of mismatches.…”

Section: Introductionmentioning

confidence: 99%

Near Optimal Robust Adaptive Beamforming Approach Based on Evolutionary Algorithm

Mallipeddi¹,

Lie²,

Suganthan³

et al. 2011

PIER B

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Abstract-The presence of desired signal in the training data for sample covariance matrix calculation is known to lead to a substantial performance degradation, especially when the desired signal is the dominant signal in the training data. Together with the uncertainty in the look direction, most of the adaptive beamforming solutions are unable to approach the optimal performance. In this paper, we propose an evolutionary algorithm (EA) based robust adaptive beamforming that is able to achieve near optimal performance. The essence of the idea is to shape the array beam response such that it has maximum response in the desired signal's angular range and minimum response in the interferences' angular range. In addition, the approach introduces null-response constraints deduced from the array observation to achieve better interference cancelation performance. As a whole, the proposed optimization is solvable using an improved variant of the differential evolution (DE) algorithm. Numerical simulations are also presented to demonstrate the efficacy of the proposed algorithm.

show abstract

An adaptive antenna array under directional constraint

Cited by 179 publications

References 14 publications

Study of beamforming techniques for ultrasound imaging in nondestructive testing

Study of beamforming techniques for ultrasound imaging in nondestructive testing

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

Near Optimal Robust Adaptive Beamforming Approach Based on Evolutionary Algorithm

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