Adaptive beamformer

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

Adaptive beamforming for photoacoustic imaging using linear array transducer

Abstract: Photoacoustic signals, detected by a transducer array, need to be beamformed for subsequent use in a limited view angle tomography such as B-scan imaging. In the presence of the light scattering or phase aberration, the spatial resolution and contrast in the photoacoustic images are degraded. Phase aberration due to tissues with inhomogeneous acoustic speeds is a major source for image degradation. However, a constant speed of sound (e.g., 1540 m/s) is typically assumed in photoacoustic imaging. Such an assumption can affect the quality of photoacoustic image since changes in sound velocity cause significant phase errors in beamforming. An adaptive weighting method such as coherence factor (CF) technique can improve the ultrasound and photoacoustic image quality significantly. In addition, photoacoustic images can be further improved by applying adaptive beamforming techniques developed for ultrasound imaging. In this study, an adaptive photoacoustic image reconstruction technique that combines an adaptive weighting factor (CF) and an adaptive apodization called minimum variance method (MV) is introduced. Although MV method calculates the optimal apodization weighting factors which minimize the variance of the beamformed signal, it can lead to unexpected weighting factors since it is data dependant. In this case, CF weighting can help to avoid this problem by weighting the output from the MV method based on signal coherence. Simulations were performed to analyze the spatial resolution using a point targets and to demonstrate improvement in phase aberration correction. Numerical studies demonstrated the superior performance of MV adaptive method combined with CF weighting.

An adaptive array processor with robustness and broad-band capabilities

Abstract: A new type of receiving array which adaptively minimizes ouput noise power while simultaneously satisfying certain robustness and/or bandwidth criteria is considered. The resulting array gains are shown to be robust against direction uncertainty in the assumed look direction, against wavefront distortions and against array geometry errors. The robustness property is incorporated directly into the adaption algorithm via constraints. Extensive simulation has established very satisfactory performance of this new algorithm, both as a limited broad-band processor and as a robust narrow-band processor.

Multiple-input multiple-output over-thehorizon radar: experimental results

Abstract: Results from an experiment that applied one class of multiple-input multiple-output (MIMO) waveform techniques to over-the-horizon radar (OTHR) are reported. The experiment objective was to demonstrate that adaptive transmitter beamforming could be used in an appropriately design radar to reject spatially discrete Doppler-spread clutter. In the particular MIMO radar architecture that the authors call non-causal transmit beamforming, conventional or adaptive transmitter beamforming occurs following waveform transmission, propagation, scatter from targets and clutter sources, return propagation and finally signal reception. In the case reported herein spatially discrete clutter was successfully rejected to the noise floor of the radar return with rejection in excess of 35 dB achieved using common adaptive algorithms and straightforward training data selection. As part of the rejection algorithm the transmitted waveform direction-of-departure (DOD) from the transmitter array to the target was estimated and used as the preserved steer direction in the adaptive beamformer. The DOD estimates agree well with the geometrically determined true values. The demonstration of non-causal transmit beamforming suggests that it will be possible to create multiple simultaneous adaptive range-dependent transmitter beams with an appropriately designed OTHR. This has several applications including for the mitigation of Doppler-spread clutter.

Adaptive beamforming for rapidly moving arrays

Abstract: Adaptive beamforming procedures based on linear least squares estimation of a wanted signal have been shown to successfully excise unwanted interference from the beamformer output when the signal environment is stationary. However under non-stationary conditions, such as those experienced by an array mounted on a rapidly moving platform, performance may be significantly degraded. By modelling the dynamic behaviour of the beamforming weights the losses in performance may be recovered. In particular we show that through the estimation of a beamforming weight vector and its rate-of-change, we are able to compensate for the effects of a constant angular rotation of the array.