Chirp parameter estimation from a sample covariance matrix

This paper considers the problem of estimating the bandwidth and the center frequency of a linear chirp signal. The nonstationarity property of chirp signals implies that the signal has high rank and reduces the applicability of subspace-based algorithms significantly. However, the special structure of the sample covariance matrix invites the use of regular frequency estimation algorithms. Herein, we show how subspace-type algorithms may be modified to provide accurate signal parameter estimates for linear chirp signals at reasonable complexity. The root-MUSIC algorithm is used as an example.