On Estimating Parameters of a Multicomponent Chirp Model With Equal Chirp Rates

Multicomponent chirp signal models with equal chirp rates appear in various radar applications, e.g., synthetic aperture radar, echo signal of a rapid mobile target, etc. Many suboptimal estimators have been developed for such models; however, these suffer from either identifiability or error propagation effect. In this article, we have developed theoretical properties of the least squares estimators (LSEs) of the parameters of the multicomponent chirp model with equal chirp rates, where the model is contaminated with linear stationary errors. We also propose two computationally efficient estimators as alternative to LSEs, namely, sequential combined estimators and sequential plug-in estimators. Strong consistency and asymptotic normality of these estimators have been derived. Interestingly, it is observed that a sequential combined estimator of the chirp rate parameter is asymptotically efficient. Extensive numerical simulations have been performed, which validate satisfactory computational and theoretical performance of all three estimators. We have also analyzed simulated radar data with the help of our proposed estimators of the multicomponent chirp model with equal chirp rates, which performs efficiently in the recovery of inverse synthetic aperture radar image of a target from a noisy data.