This paper presents the quantitative analysis of signal-to-noise ratio (SNR) for the local polynomial Fourier transform (LPFT) used for application of inverse synthetic aperture radar (ISAR) imaging. The relationship between the LPFT and Wigner-Ville distribution (WVD) is derived and theoretical analysis on the SNR achieved by using the LPFT is given. Comparisons on the SNR performances achieved by using the LPFT, the short-time Fourier transform (STFT) and the Fourier transform (FT) are presented to illustrate the merits of using the LPFT. Measures are also taken to minimize the required computational complexity by reducing the overlap length between adjacent segments of input data. Simulation results of processing radar data show the performance improvements achieved by using the LPFT.
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Li et al. (2009) studied this question.
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