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Parameter estimation of 2D polynomial phase signals using NU sampling and 2D CPF

Parameter estimation of 2D polynomial phase signals using NU sampling and 2D CPF

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The two-dimensional (2D) cubic phase function (CPF) is known as a highly accurate 2D polynomial phase signal estimator, but it has limited applicability due to the requirement for the 3D search for second-order partial phase derivatives. The authors propose an interpolation-based approach simulating non-uniform (NU) signal sampling in order to reduce the 2D CPF calculation complexity. The NU resampling enables the 2D CPF evaluation using the 2D fast Fourier transform and searches over mixed-phase parameter. The computational complexity is reduced from to . The additional stage with dechirping, filtering and phase unwrapping is introduced to refine parameter estimates.

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