A neural network for fast-response ultrasonic distance sensors
Franco Ferraris, U. Grimaldi, Marco Parvis, Salvatore Graziani · 2002
Ultrasonic techniques can provide a cost effective solution for distance measurements, but frequently suffer from poor resolution and acoustic noise. A new approach based on neural networks to process the echo signal is described. It permits the improvement of the resolution of distance measuring systems by employing ultrasonic techniques and requires a negligible computing time, even though the network is implemented without special purpose hardware. The results obtained with inexpensive piezoelectric transducers and a neural network are described. The neural network performance is compared with that of traditional techniques. A sub-millimeter resolution is obtained even in the presence of some acoustic noise, which could prevent other simple detection strategies.>