Beamforming with a reduced sampling rate.
The beamforming process requires a high delay resolution to avoid the deteriorating effects of the delay quantization lobes on the image dynamic range and signal to noise ratio. Wideband transducers require delay resolutions in the order of 1/16 the signal period. If oversampling is used to achieve this timing resolution, a huge data volume has to be acquired and processed in real time. This is usually avoided by sampling just above the Nyquist rate and interpolating to achieve the required delay resolution. However this increases the hardware complexity. Baseband sampling has been alternatively proposed with sampling rates as low as the transducer frequency or even lower. This approach uses two A/D converters and processing chains for every channel, thus doubling the hardware requirements. Quadrature sampling can be used instead with a single A/D converter, but the sampling rate must be a multiple of four times the transducer frequency, decreasing the application flexibility. Furthermore, it produces relatively high errors in the detected envelope if wideband transducers are used. This work presents a new approach, the selective sampling technique (SST), which keeps the lowest sampling rate required by the imaging process or the signal bandwidth (whatever is larger) and, at the same time, provides a high delay resolution to keep the highest image dynamic range. The SST is based on a second order sampling process which, differently from the mentioned approaches, does not pose any constraints in the time interval between samples and produce lower errors in the detected envelope. The hardware requirements are low (a single A/D converter and processing chain for every transducer element), working at the lowest data rate compatible with the Nyquist criterion, thus reducing the data bandwidth. Furthermore, the sampling points can be also freely chosen, so that the SST simplify the usually required scan conversion process to a simple linear interpolation easily carried out by software in real-time.
Fritsch
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Instituto de Automática Industrial (CSIC), La Poveda, Madrid, Spain. carlos@iai.csic.es
Parrilla
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Sánchez
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Martínez
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