Sparse Phase Retrieval from Short-Time Fourier Measurements

Abstract—We consider the classical 1D phase retrieval problem. In order to overcome the difficulties associated with phase re-trieval from measurements of the Fourier magnitude, we treat recovery from the magnitude of the short-time Fourier trans-form (STFT). We first show that the redundancy offered by the STFT enables unique recovery for arbitrary nonvanishing inputs, under mild conditions. An efficient algorithm for recovery of a sparse input from the STFT magnitude is then suggested, based on an adaptation of the recently proposed GESPAR algorithm. We demonstrate through simulations that using the STFT leads to improved performance over recovery from the oversampled Fourier magnitude with the same number of measurements. Index Terms—GESPAR, phase retrieval, short-time Fourier transform, sparsity