A method based on neural network for LFMCW radar system object range super-resolution estimation

To replace the traditional FFT method to realize the object range super-res olution estimation, an artificial neural network method was proposed to dec ompose signal's auto-correlation matrix into the summation of rank-1 matric es, and convert the decomposition problem to an iterative one by using Hopf ield neural network. The property of this method was investigated both theo retically and experimentally. And the results were compared with five other typical super-resolution algorithms including MUSIC, etc., and it was foun d that the present method has a lower SNR threshold and higher range resolu tion.