Fractional Fourier Analysis Using the Möbius Inversion Formula

Compared with the Fourier analysis, the fractional Fourier analysis is more suitable to process linear frequency modulation type non-stationary functions. To the best of our knowledge, the theoretical framework of the fractional Fourier analysis has not well established yet, especially for the fractional Fourier series (FrFS) and the discrete fractional Fourier transform (DFrFT) algorithms. To tackle with these problems, the efficient FrFS and DFrFT algorithms based on the Möbius function are proposed. First, the existence and applicability of the FrFS are analyzed basing on the Möbius inversion formula. Second, two kinds of fast algorithms for the infinite/finite FrFS are proposed. Then, based on the amplitude scaling relationship between the FrFS and samples of the FrFT, two efficient DFrFT algorithms are obtained, which are noted as the arithmetic discrete fractional Fourier transform (ADFrFT)-I and the ADFrFT-II. Importantly, the multiplication complexity of the two proposed ADFrFT algorithms is reduced to O(M), which is less than that of the state-of-the-art DFrFT algorithms. The parallel butterfly structure of the ADFrFT-II algorithm is suitable for the very large scale integration implementation. Finally, the simulations justify the efficiency of the ADFrFT algorithms in filtering and parameter evaluation of radar and optical signals.