Topic
Adaptive beamformer
About: Adaptive beamformer is a research topic. Over the lifetime, 4934 publications have been published within this topic receiving 93100 citations.
Papers published on a yearly basis
Papers
More filters
••
TL;DR: This research presents the first-time application ofSKF algorithm to adaptive beamforming, and a new modified version of the SKF algorithm named SKF with Modified Measurement (SKFMM) is introduced to further improve the exploration capabilities of SKf algorithm by modifying the measurement-update equation.
Abstract: Adaptive beamforming is a technique used to steer the radiation pattern towards the desired signal and cancel out any interference signal by finding the appropriate weights for every element in an array antenna, to achieve maximum signal to interference plus noise ratio (SINR). There are many methods to perform adaptive beamforming and one of the method is to use metaheuristic algorithm, to estimate the weights for individual elements in an array. Over the years, various metaheuristic algorithms have been applied to adaptive beamforming. Some of the metaheuristic algorithms have been modified from the original algorithms to improve the algorithms performance in adaptive beamforming application. A new metaheuristic algorithm named Simulated Kalman Filter (SKF), is inspired by the estimation capabilities of Kalman filter, has not been applied to adaptive beamforming application. Therefore, this research presents the first-time application of SKF algorithm to adaptive beamforming. The SKF algorithm, however, often converge prematurely at local optimum due to lack of exploration, preventing it from finding better solution. A modified version of the SKF algorithm, named Opposition-Based SKF (OBSKF), introduced by K. Zakwan, applies Opposition-Based Learning method to improve the exploration capabilities of SKF algorithm. Moreover, a new modified version of the SKF algorithm named SKF with Modified Measurement (SKFMM) is introduced to further improve the exploration capabilities of SKF algorithm by modifying the measurement-update equation. The SKF, OBSKF and SKFMM is applied to an array antenna with 10 elements arranged linearly with 0.5
18 citations
••
03 Dec 2003TL;DR: Speech recognition result shows that the proposed robust adaptive beamformer guarantees the recognition performance even in a low SNR and highly reverberant environment.
Abstract: Speech recognition using circular microphone array is addressed in this paper. Eight microphones are located around the service robot to form a 2D microphone array. To enhance the speech quality, a novel adaptive beamformer composed of a delay-and-sum beamformer, adaptive blocking filters (ABFs) and adaptive cancelling filters (ACFs) is proposed. While the adaptive generalized sidelobe canceller (AGSC) connects the ABF and the ACF in feedforward, the proposed adaptive beamformer has them in feedback. The advantages of the proposed structure are the robustness to the steering vector errors and cross-talks and the reduced number of filter taps that gives the same speech quality compared to the AGSC with a larger number of filter taps. The experimental results show that the proposed structure is superior to the AGSC in objective and subjective evaluations. Speech recognition result shows that the proposed robust adaptive beamformer guarantees the recognition performance even in a low SNR and highly reverberant environment.
18 citations
01 Jan 2012
TL;DR: This paper establishes an interference subspace spanned by the interference steering vectors of the virtual antenna array, and then the interference direction information can be imported into the transformation matrix by projecting the Transformation matrix into the subspace, which will make the interference components in virtual smoothing covariance matrix enhanced as it is demonstrated by theoretical analysis.
Abstract: In this paper, we propose Modifled Interpolated Spatial Smoothing (MISS) algorithm that solves the problem when the inhibition gain generated by Interpolated Spatial Smoothing (ISS) algorithm is not su-ciently high in virtual antenna adaptive beam forming to suppress coherent interference. Using the subspace projection concept, this paper establishes an interference subspace spanned by the interference steering vectors of the virtual antenna array, and then the interference direction information can be imported into the transformation matrix by projecting the transformation matrix into the subspace, which will make the interference components in virtual smoothing covariance matrix enhanced as it is demonstrated by theoretical analysis. Employing the Minimum Variance Distortionless Response (MVDR) beam forming method, the interference inhibition gain and Signal to Interference and Noise Ratio (SINR) performance can be signiflcantly improved.
18 citations
••
TL;DR: A cascaded algorithm is presented to realise clutter suppression for NSLAR with HPRF using a novel orthogonal-waveform-based elevation adaptive beamforming method and the residual range-independent far-range clutter is suppressed by azimuth-Doppler space-time adaptive processing (STAP).
Abstract: Clutter suppression is a challenging problem in non-side-looking airborne radar (NSLAR) because of the range-dependent clutter. It is more intractable when the NSLAR operates at high pulse repetition frequency (HPRF). In this study, a cascaded algorithm is presented to realise clutter suppression for NSLAR with HPRF. A novel orthogonal-waveform-based elevation adaptive beamforming method is proposed to suppress range-dependent near-range clutter at the first stage, and the residual range-independent far-range clutter is suppressed by azimuth-Doppler space-time adaptive processing (STAP) at the second stage. The proposed elevation beamformer can provide excellent performance on near-range clutter suppression because of the developed secondary data selection strategy. After suppression of the range-dependent near-range clutter, the range independency of clutter samples is enhanced evidently. Hence, the clutter suppression performance obtained by azimuth-Doppler STAP methods could be improved dramatically. Numerical examples are given to verify the validity of the proposed algorithm.
18 citations
••
TL;DR: Exact means and variances are given for the SCR MVDR beamformer output accounting simultaneously for finite sample support, imperfect look, and inhomogeneities demonstrating biased signal estimates and potentially extreme vulnerability to undernulled interference and surprise jammers.
Abstract: The sample covariance based (SCB) minimum variance distortionless response (MVDR) beamformer has desirable properties under ideal homogeneous data conditions with perfect look. Such properties include maximum-likelihood optimality yielding an unbiased asymptotically efficient estimate of the signal parameter. When target array response mismatch exists and inhomogeneities are present, however, its performance can degrade considerably. Exact means and variances are given for the SCR MVDR beamformer output accounting simultaneously for finite sample support, imperfect look, and inhomogeneities demonstrating biased signal estimates and potentially extreme vulnerability to undernulled interference and surprise jammers.
18 citations