| Popis: |
Low-power excitation and/or low sensitivity transducers, such as electromagnetic acoustic transducers (EMATs), piezoelectric paints, air-coupled transducers, or small elements of dense arrays may produce signals below the noise threshold at the receiver. The information from those noisy signals can be recovered after averaging or pulse-compression using binary (one-bit) quantisation only without experiencing significant losses. Hence, no analog-to-digital converter is required, which makes the electronics faster, more compact and energy efficient. All this is especially attractive for applications that require arrays with many channels and high sampling rates, where the sampling rate can be as high as the system clock. In this paper, the theory of binary quantisation is reviewed, mainly from previous work on wireless sensor networks, and the signal-to-noise ratio (SNR) of the input signals under which binary quantisation is of practical interest for ultrasound applications is investigated. The main findings are that in most practical cases binary quantisation can be used with small errors when the input SNR is in the order of 8 dB or less. Moreover, the maximum SNR after binary quantisation and averaging can be estimated as 10 log10 N −2 dB, where N is the number of averages. |
