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In this paper, we address the problem of parameter estimation of a 2-D chirpmodel under the assumption that the errors are stationary. We extend the 2-Dperiodogram method for the sinusoidal model, to find initial values to use inany iterative procedure to compute the least squares estimators (LSEs) of theunknown parameters, to the 2-D chirp model. Next we propose an estimator, knownas the approximate least squares estimator (ALSE), that is obtained bymaximising a periodogram-type function and is observed to be asymptoticallyequivalent to the LSE. Moreover the asymptotic properties of these estimatorsare obtained under slightly mild conditions than those required for the LSEs.For the multiple component 2-D chirp model, we propose a sequential method ofestimation of the ALSEs, that significantly reduces the computationaldifficulty involved in reckoning the LSEs and the ALSEs. We perform somesimulation studies to see how the proposed method works and a data set has beenanalysed for illustrative purposes.

Asymptotic of Approximate Least Squares Estimators of Parameters Two-Dimensional Chirp Signal