A sparse optimisation method based on cross-correlation function for chirp signals

This letter proposes a novel time delay estimation method based on sparse optimisation of the cross-correlation function to improve the estimation accuracy of delay parameters of chirp signals in multipath environments. In this method, the time delay estimation model is converted into a correlation-function based model to estimate the parameter of exponent signals with frequency information, and the covariance matrix of such correlation function is solved by a sparse iteration optimisation algorithm abbreviated as CCF-SPICE. Experimental simulations show that the proposed delay estimation algorithm has a sharper peak with less power leakage compared with the existing SPICE algorithm. Its performance is better than the SPICE algorithm and conventional MUSIC algorithm, especially under low SNR in multipath environments. The MSE performance of the proposed CCF-SPICE algorithm is closer to Cramer-Rao bounds.