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 pa...
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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 2dcpfcalculationcomplexity. The NU resampling enables the 2dcpf evaluation using the 2d fast Fourier transform and searches over mixed- phase parameter. The computational complexity is reduced from O( N5) to O( N3 log2 N). The additional stage with dechirping, filtering and phase unwrapping is introduced to refine parameter estimates.
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