This paper proposes a new frequency domain approach for identifying the parameters of twoâdimensional complex sinusoids from a finite number of data, when the measurements are affected by additive and uncorrelated twoâdimensional white noise. The new method extends in two dimensions a frequency identification procedure of complex sinusoids, originally developed for the oneâdimensional case. The properties of the proposed method are analyzed by means of Monte Carlo simulations and its features are compared with those of other estimation algorithms. In particular the practical advantage of the method will be highlighted. In fact the novel approach can operate just on a specified subâarea of the 2D spectrum. This areaâselective feature allows a drastic reduction of the computational complexity, which is usually very high when standard time domain methods are used.
Note: Updated by Technical Report 2018-007, April 2018. See http://www.it.uu.se/research/publications/reports/2018-007.
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