Method based on neural network for LFMCW radar system object range superresolution estimation

To replace the traditional FFT method and realize the object range super-resolution estimation, an artificial neural network method was proposed to decompose signal's auto-correlation matrix into the summation of rank-1 matrices and convert the decomposition problem to an iterative one by using Hopfield neural network. The property of this method was investigated both theoretically and experimentally. The results were compared with five other typical super-resolution algorithms including MUSIC, etc.. It is found that the present method has a lower SNR threshold and higher range resolution.