Adaptive beamformer

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

Robust Adaptive Beamforming Based on Low-Rank and Cross-Correlation Techniques

Abstract: This paper presents cost-effective low-rank techniques for designing robust adaptive beamforming (RAB) algorithms. The proposed algorithms are based on the exploitation of the cross-correlation between the array observation data and the output of the beamformer. First, we construct a general linear equation considered in large dimensions whose solution yields the steering vector mismatch. Then, we employ the idea of the full orthogonalization method (FOM), an orthogonal Krylov subspace based method, to iteratively estimate the steering vector mismatch in a reduced-dimensional subspace, resulting in the proposed orthogonal Krylov subspace projection mismatch estimation (OKSPME) method. We also devise adaptive algorithms based on stochastic gradient (SG) and conjugate gradient (CG) techniques to update the beamforming weights with low complexity and avoid any costly matrix inversion. The main advantages of the proposed low-rank and mismatch estimation techniques are their cost-effectiveness when dealing with high-dimension subspaces or large sensor arrays. Simulations results show excellent performance in terms of the output signal-to-interference-plus-noise ratio (SINR) of the beamformer among all the compared RAB methods.

Adaptive beamforming algorithm for OFDM systems with antenna arrays

Abstract: This paper presents an adaptive beamforming algorithm for an OFDM system with an adaptive array antenna. The proposed algorithm for adaptive beamforming in the OFDM system is derived by (1) calculating the pilot error signals in the frequency domain, (2) transforming the frequency-domain error signals into time-domain error signals, (3) updating the filter coefficients of the adaptive beamformer in the direction of minimizing the MSE. The convergence behavior and performance improvement of the proposed approach are investigated through computer simulation by applying it to the conventional OFDM system.

Collaborative Null-Steering Beamforming for Uniformly Distributed Wireless Sensor Networks

Abstract: Null-steering transmit beamformers aim to maximize the received signal power in the direction of the intended receiver while substantially reducing the power impinging on the unintended receivers located in other directions. The existing null-steering beamformers may not be directly applied in wireless sensor networks (WSNs) as they do not conform with the decentralized nature of WSNs and require every node to be aware of the locations of all other nodes in the network. This manuscript presents a novel collaborative null-steering beamformer that can be implemented in uniformly distributed WSNs in which each node is oblivious of other nodes' locations. The average beampattern expression of the proposed beamformer is derived and it is shown that the beampattern associated with any arbitrary realization of the nodes' locations converges with probability one to the so-obtained average beampattern as the number of collaborating nodes grows large. Properties of the average beampattern are analytically studied. In particular, it is proven that the average gain of the proposed beamformer is inversely proportional to the number of collaborating nodes in the directions of unintended receivers and further, if a mild condition is satisfied, it is approximately equal to that of the collaborative conventional beamformer in the directions with far angular distance from any unintended receiver. It is argued that if virtual unintended receivers are assumed at proper directions, then the proposed collaborative null-steering beamformer can form an average beampattern with sidelobe peaks substantially smaller than those of the average beampattern of the collaborative conventional beamformer. To substantiate this argument, the optimal direction of a virtual unintended receiver is obtained such that its associated collaborative null-steering beamformer forms an average beam-pattern with minimal largest side-lobe peak. Depending on the number of collaborating nodes, it is further shown that the largest average sidelobe peak of the latter beamformer is up to 6.6 (dB) less than that of the collaborative conventional beamformer.

A Novel Adaptive Beamforming Technique Applied on Linear Antenna Arrays Using Adaptive Mutated Boolean PSO

Abstract: The present work introduces a new optimization technique suitable for adaptive beamforming of linear antenna arrays. The proposed technique is a new PSO variant called Adaptive Mutated Boolean PSO (AMBPSO) where the update formulae are implemented exclusively in Boolean form by using an e-ciently adaptive mutation process. The AMBPSO aims at estimating the excitation weights applied on the array elements considering that a desired signal and several interference signals are received by the array at respective directions of arrival. In order to exhibit the robustness of the technique, the optimization process does not take into account the interference correlation matrix. A certain power level of additive Gaussian noise is also considered by the technique. The AMBPSO has been applied in several cases of uniform linear antenna arrays with difierent spacing between adjacent elements and difierent noise power level and therefore seems to be quite promising in the smart antenna technology.

Time-Domain Wideband Adaptive Beamforming for Radar Breast Imaging

Abstract: A novel wideband microwave radar imaging method is presented to detect regions of significant dielectric contrast within the breast. Clutter reduction is paramount to any radar imaging algorithm, especially with clinical patient data where the tissue composition of the breast is inhomogeneous. Time-domain data-adaptive imaging methods have been previously applied in a narrowband manner for microwave radar breast imaging when the received signal spectral content was wideband. In this study, a wideband time-domain adaptive imaging approach is presented to perform data-adaptive focusing across the spectrum to reduce clutter. An equalization filter is adapted to compensate for the propagation distortion through tissue using a calculated estimate of the average dielectric properties of the breast. The effectiveness of the proposed wideband adaptive imaging approach is evaluated in conjunction with the delay-and-sum (DAS) method using numerical, experimental, and clinical data. Target scatterers are clearly detected while clutter levels are reduced significantly, between 4 and 6 dB, when compared to the DAS technique.