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Multi-component chirp signal models with equal chirp rates appear in variousradar applications, e.g., synthetic aperture radar, echo signal of a rapidmobile target, etc. Many sub-optimal estimators have been developed for suchmodels, however, these suffer from the problem of either identifiability orerror propagation effect. In this paper, we have developed theoreticalproperties of the least squares estimators (LSEs) of the parameters ofmulti-component chirp model with equal chirp rates, where the model iscontaminated with linear stationary errors. We also propose two computationallyefficient estimators as alternative to LSEs, namely sequential combinedestimators and sequential plugin estimators. Strong consistency and asymptoticnormality of these estimators have been derived. Interestingly, it is observedthat sequential combined estimator of the chirp rate parameter isasymptotically efficient. Extensive numerical simulations have been performed,which validate satisfactory computational and theoretical performance of allthree estimators. {We have also analysed a simulated radar data with the helpof our proposed estimators of multi-component chirp model with equal chirprates, which performs efficiently in recovery of inverse synthetic apertureradar (ISAR) image of a target from a noisy data.

On estimating parameters of a multi-component Chirp Model with equal chirp rates