Topic
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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TL;DR: The results show that the proposed beamformer produces a radiation pattern equivalent to a conventional beamformer using baseband demodulation, provided that the sampling rate is approximately 10 times the center frequency of the transducer (34% bandwidth pulse).
Abstract: A real-time 3-D imaging system requires the development of a beamformer that can generate many beams simultaneously. In this paper, we discuss and evaluate a suitable synthetic aperture beamformer. The proposed beamformer is based on a pipelined network of high speed digital signal processors (DSP). By using simple interpolation-based beamforming, only a few calculations per pixel are required for each channel, and an entire 2-D synthetic aperture image can be formed in the time of one transmit event. The performance of this beamformer was explored using a computer simulation of the radiation pattern. The simulations were done for a full 64-element array and a sparse array with the same receive aperture but only five transmit elements. We assessed the effects of changing the sampling rate and amplitude quantization by comparing the relative levels of secondary lobes in the radiation patterns. The results show that the proposed beamformer produces a radiation pattern equivalent to a conventional beamformer using baseband demodulation, provided that the sampling rate is approximately 10 times the center frequency of the transducer (34% bandwidth pulse). The simulations also show that the sparse array is not significantly more sensitive to delay or amplitude quantization than the full array.
72 citations
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ETSI1
TL;DR: It is demonstrated via analysis and simulations that minima correspond to points where output noise power is minimized, interferences are canceled, and intersymbol interference is removed, i.e., the beamformer eliminates the distortion introduced by the radiocommunication channel.
Abstract: A new approach to adaptive beamforming is presented The method is based on the property of cyclostationary signals to generate spectral lines when they pass through certain nonlinear transformations The beamformer coefficients are selected according to a new optimization objective, which consists on minimizing the mean square error between the array output after the nonlinearity and a complex exponential This approach optimally extracts any signal that generates a spectral line at the same frequency as the reference complex exponential A gradient-based algorithm is derived to compute the optimum weights Since the proposed cost function is a nonconvex function of the array coefficients, minima are analyzed for the three most common types of perturbations found in communications: Gaussian noise, multiple interferences, and multipath propagation It is demonstrated via analysis and simulations that minima correspond to points where output noise power is minimized, interferences are canceled, and intersymbol interference is removed, ie, the beamformer eliminates the distortion introduced by the radiocommunication channel >
72 citations
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TL;DR: In this paper, the adaptive array is divided into subarrays, whose input correlation matrices are adaptively averaged so as to produce a Toeplitz matrix which would be obtained when the interference did not correlate with the desired signal.
Abstract: When the interference is coherent with the desired signal, the conventional adaptive arrays working under the guiding principle of output power minimization tend to cancel the desired signal by using the coherent interference. A technique is described which enables the adaptive array to function even under such an environment. The array is divided into subarrays, whose input correlation matrices are adaptively averaged so as to produce a Toeplitz matrix which would be obtained when the interference did not correlate with the desired signal. The averaged matrix is now free from correlation terms between the desired signal and interference, and therefore may be used to derive the optimum weight for the array element just as in the ordinary radio environment of incoherent interference. Numerical examples show that the new adaptive array is highly capable to suppress the coherent interferences as well as incoherent ones.
72 citations
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TL;DR: A new antenna array beamformer based on neural networks (NNs) is presented that makes a uniform linear antenna array steer the main lobe toward a desired signal, place respective nulls toward several interference signals, and suppress the side lobe level (SLL).
Abstract: A new antenna array beamformer based on neural networks (NNs) is presented. The NN training is performed by using optimized data sets extracted by a novel invasive weed optimization (IWO) variant called modified adaptive dispersion IWO (MADIWO). The trained NN is utilized as an adaptive beamformer that makes a uniform linear antenna array steer the main lobe toward a desired signal, place respective nulls toward several interference signals, and suppress the side lobe level (SLL). Initially, the NN structure is selected by training several NNs of various structures using MADIWO-based data and by making a comparison among the NNs in terms of training performance. The selected NN structure is then used to construct an adaptive beamformer, which is compared to MADIWO-based and ADIWO-based beamformers, regarding the SLL and the ability to properly steer the main lobe and the nulls. The comparison is made, considering several sets of random cases with different numbers of interference signals and different power levels of additive zero-mean Gaussian noise. The comparative results exhibit the advantages of the proposed beamformer.
72 citations
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18 Sep 2005
TL;DR: In this article, the performance of four beamforming algorithms (Frost BF, Duvall BF, SSB, and SPOC) was compared to the conventional, data independent, beamforming.
Abstract: For over thirty years adaptive beamforming (AB) algorithms have been applied in RADAR and SONAR signal processing. Higher resolution and contrast is attainable using those algorithms at the price of an increased computational load. In this paper we consider four beamformers (BFs): Frost BF, Duvall BF, SSB, and SPOC. These algorithms are well know in the RADAR/SONAR literature. We have performed a series of simulations using ultrasound data to test the performance of those algorithms and compare them to the conventional, data independent, beamforming. Every algorithm was applied on single channel ultrasonic data that was generated using Field II. For a 32 element linear array operating at 5 MHz, beamplot results show that while the Duvall and SSB beamformers reduce sidelobes by roughly 20 dB, the sidelobes using the Frost algorithm rise by 23dB. The -6dB resolution is improved by 38%, 83%, and 43% in the case of Duvall, Frost, and SSB algorithms, respectively. In the case of SPOC, the beamplot shows a super-resolution peak with noise floor at -110 dB. Similar results were obtained for an array consisting of 64 elements.
71 citations