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Adaptive beamformer

About: Adaptive beamformer is a research topic. Over the lifetime, 4934 publications have been published within this topic receiving 93100 citations.


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Journal ArticleDOI
04 May 2014
TL;DR: Theoretical arguments and simulation analysis provide evidence that a CS-based beamformer can achieve resolution beyond the classical Rayleigh limit and the theoretical findings are validated by processing a real sonar dataset.
Abstract: This paper deals with the problem of estimating the directions of arrival (DOA) of multiple source signals from a single observation vector of an array data. In particular, four estimation algorithms based on the theory of compressed sensing (CS), i.e., the classical l1 minimization (or Least Absolute Shrinkage and Selection Operator, LASSO), the fast smooth l0 minimization, and the Sparse Iterative Covariance-Based Estimator, SPICE and the Iterative Adaptive Approach for Amplitude and Phase Estimation, IAA-APES algorithms, are analyzed, and their statistical properties are investigated and compared with the classical Fourier beamformer (FB) in different simulated scenarios. We show that unlike the classical FB, a CS-based beamformer (CSB) has some desirable properties typical of the adaptive algorithms (e.g., Capon and MUSIC) even in the single snapshot case. Particular attention is devoted to the super-resolution property. Theoretical arguments and simulation analysis provide evidence that a CS-based beamformer can achieve resolution beyond the classical Rayleigh limit. Finally, the theoretical findings are validated by processing a real sonar dataset.

118 citations

Journal ArticleDOI
TL;DR: A new approach to adaptive beamforming with sidelobe control is developed that minimizes the array output power while maintaining the distortionless response in the direction of the desired signal and a sidelobe level that is strictly guaranteed to be lower than some given threshold value.
Abstract: A new approach to adaptive beamforming with sidelobe control is developed. The proposed beamformer represents a modification of the popular minimum variance distortionless response (MVDR) beamformer. It minimizes the array output power while maintaining the distortionless response in the direction of the desired signal and a sidelobe level that is strictly guaranteed to be lower than some given (prescribed) threshold value. The resulting modified MVDR problem is shown to be convex, and its second-order cone (SOC) formulation is obtained that facilitates a computationally efficient way to implement our beamformer using the interior point method.

117 citations

Journal ArticleDOI
TL;DR: In this paper, a low-complexity robust adaptive beamforming (RAB) technique which estimates the steering vector using a Low-Complexity Shrinkage-Based Mismatch Estimation (LOCSME) algorithm is proposed.
Abstract: In this work, we propose a low-complexity robust adaptive beamforming (RAB) technique which estimates the steering vector using a Low-Complexity Shrinkage-Based Mismatch Estimation (LOCSME) algorithm. The proposed LOCSME algorithm estimates the covariance matrix of the input data and the interference-plus-noise covariance (INC) matrix by using the Oracle Approximating Shrinkage (OAS) method. LOCSME only requires prior knowledge of the angular sector in which the actual steering vector is located and the antenna array geometry. LOCSME does not require a costly optimization algorithm and does not need to know extra information from the interferers, which avoids direction finding for all interferers. Simulations show that LOCSME outperforms previously reported RAB algorithms and has a performance very close to the optimum.

115 citations

Journal ArticleDOI
TL;DR: The main advantages of the new technique are: (1) the procedure requires neither reference signals nor a training period; (2) the signal intercoherency does not affect the performance or complexity of the entire procedure; and (3) the total amount of computation is tremendously reduced compared to that of most conventional beamforming techniques.
Abstract: This paper presents an alternative method of adaptive beamforming. Under an assumption that the desired signal is large enough compared to each of interfering signals at the receiver, which is preconditionally achieved in code division multiple access (CDMA) mobile communications by the chip correlator, the proposed technique provides for a suboptimal beam pattern that increases the signal-to-noise/signal-to-interference ratio (SNR/SIR) and eventually increases the capacity of the communication channel. The main advantages of the new technique are: (1) the procedure requires neither reference signals nor a training period; (2) the signal intercoherency does not affect the performance or complexity of the entire procedure; and (3) the total amount of computation is tremendously reduced compared to that of most conventional beamforming techniques such that the suboptimal beam pattern is produced at every snapshot on a real-time basis. In fact, the total computational load for generating a new set of weights including the update of an N-by-N autocovariance matrix is O(3N/sup 2/+12N). It can further be reduced down to O(11N) by approximating the matrix with the instantaneous signal vector.

113 citations

Journal ArticleDOI
TL;DR: The quantitative results of the simulations show that MVB-DMAS leads to improvement in full-width-half-maximum about 96%, 94%, and 45% and signal-to-noise ratio about 89%, 15%, and 35% compared to DAS, DMAS, MV, respectively.
Abstract: In photoacoustic imaging, delay-and-sum (DAS) beamformer is a common beamforming algorithm having a simple implementation. However, it results in a poor resolution and high sidelobes. To address these challenges, a new algorithm namely delay-multiply-and-sum (DMAS) was introduced having lower sidelobes compared to DAS. To improve the resolution of DMAS, a beamformer is introduced using minimum variance (MV) adaptive beamforming combined with DMAS, so-called minimum variance-based DMAS (MVB-DMAS). It is shown that expanding the DMAS equation results in multiple terms representing a DAS algebra. It is proposed to use the MV adaptive beamformer instead of the existing DAS. MVB-DMAS is evaluated numerically and experimentally. In particular, at the depth of 45 mm MVB-DMAS results in about 31, 18, and 8 dB sidelobes reduction compared to DAS, MV, and DMAS, respectively. The quantitative results of the simulations show that MVB-DMAS leads to improvement in full-width-half-maximum about 96%, 94%, and 45% and signal-to-noise ratio about 89%, 15%, and 35% compared to DAS, DMAS, MV, respectively. In particular, at the depth of 33 mm of the experimental images, MVB-DMAS results in about 20 dB sidelobes reduction in comparison with other beamformers.

113 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202371
2022168
2021133
2020154
2019198
2018154