Adaptive beamformer

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

A multi-DSP implementation of a broad-band adaptive beamformer for use in a hands-free mobile radio telephone

Abstract: An implementation of a broadband adaptive array on a multiprocessor digital signal processing system for use in a hands free mobile radio telephone is described. This implementation of a five-microphone adaptive Griffiths-Jim array can handle FIR filters with up to 128 taps behind each microphone at a sampling rate of 8 kHz. The filter structure makes it possible to combine an adaptive array with a noise canceler. The near-field problem has been solved by using focusing, a speech-controlled adaptive algorithm, and a short hourglass. Preliminary measurements indicate a considerable potential for this technique in hands-free mobile telephony. The array gives a 20-30 dB suppression of a broadband jammer covering 300-1100 Hz, even with three reflecting walls surrounding the microphone. >

Adaptive beamforming for array imaging of plate structures using lamb waves

Abstract: Lamb waves are considered a promising tool for the monitoring of plate structures. Large areas of plate structures can be monitored using active arrays employing beamforming techniques. Dispersion and multiple propagating modes are issues that need to be addressed when working with Lamb waves. Previous work has mainly focused on standard delay-and-sum (DAS) beamforming while reducing the effects of multiple modes through frequency selectivity and transducer design. This paper presents a minimum variance distortionless response (MVDR) approach for Lamb waves using a uniform rectangular array (URA) and a single transmitter. Theoretically calculated dispersion curves are used to compensate for dispersion. The combination of the MVDR approach and the two-dimensional array improves the suppression of interfering Lamb modes. The proposed approach is evaluated on simulated and experimental data and compared with the standard DAS beamformer. It is shown that the MVDR algorithm performs better in terms of higher resolution and better side lobe and mode suppression capabilities. Known issues of the MVDR approach, such as signal cancellation in highly correlated environments and poor robustness, are addressed using methods that have proven effective for the purpose in other fields of active imaging.

Robust adaptive beamforming using variable loading

Abstract: It is well known that the performance of adaptive beamformers may degrade in the presence of steering errors or lack of training data. Diagonal loading of the sample covariance matrix is a popular technique applied to the minimum variance/minimum power distortionless response beamformer to increase robustness of the array system. However, this technique induces a trade-off between sidelobe suppression and the ability of the beamformer to adaptively cancel interference and reduce noise. Here we propose a new algorithm employing variable loading of the sample covariance matrix eigenvalues, which we show along with the standard diagonal loading technique to be a special case of a more general rational approximation problem. We also present an online implementation having computational complexity comparable to conventional methods, which in turn allows the weight vector to be efficiently updated. Simulation results indicate that in comparison with standard diagonal loading techniques, the proposed method exhibits enhanced robustness and performance.

Iterative Adaptive Kronecker MIMO Radar Beamformer: Description and Convergence Analysis

Abstract: We introduce an iterative procedure for design of adaptive KL-variate linear beamformers that are structured as the Kronecker product of K-variate (transmit) and L-variate (receive) beamformers. We focus on MIMO radar applications for scenarios where only joint transmit and receive adaptive beamforming can efficiently mitigate multi-mode propagated backscatter interference. This is because the direction-of-departure (DoD) on one interference mode, and the direction-of-arrival (DoA) on the other, coincide with those of a target, respectively. We introduce a Markov model for the adaptive iterative routine, specify its convergence condition, and derive final (stable) signal-to-interference-plus-noise ratio (SINR) performance characteristics. Simulation results demonstrate high accuracy of the analytical derivations. In addition, we demonstrate, that for the considered class of multiple-input multiple-output (MIMO) radar interference scenarios, the diagonally loaded sample matrix inversion (SMI) algorithm provides additional performance improvement and convergence rate for this iterative adaptive Kronecker beamformer.

Constrained Fast-Time STAP for Interference Suppression in Multichannel SAR

Abstract: Forming a synthetic aperture radar (SAR) image while suppressing an airborne broadband jammer can potentially destroy large regions of the image. In addition to this, multipath reflections from the ground known as hot clutter or terrain scattered interference (TSI) will add a nonstationary interference component to the image. A number of constrained fast-time space time adaptive processing (STAP) techniques are presented which exploit adaptive beamforming to suppress the interference with minimal distortion to the final image.