Phase Detection Using Neural Networks

摘要

A likelihood of detecting a reflected signal characterized by phasediscontinuities and background noise is enhanced by utilizing neural networks to identify coherency intervals. The received signal is processed into a predetermined format such as a digital time series. Neural networks perform different tests over arbitrary testing intervals to determine the likelihood of a phase discontinuity occurring in any such interval. An integration time generator subsequently uses this information to define a series of contiguous coherency intervals over the duration of the received signal. These coherency intervals are then used for piece-wise processing of the received signal by parallel quadrature receivers. The outputs are combined and processed for detecting the presence of the reflected signal.