Phase Retrieval of Real-Valued Signals in a Shift-Invariant Space

Phase retrieval arises in various fields of science and engineering and it is well studied in a finite-dimensional setting. In this paper, we consider an infinite-dimensional phase retrieval problem to reconstruct real-valued signals living in a shiftinvariant space from its phaseless samples taken either on the whole line or on a set with finite sampling rate. We find the equivalence between nonseparability of signals in a linear space and its phase retrievability with phaseless samples taken on the whole line. For a spline signal of order N , we show that it can be well approximated, up to a sign, from its noisy phaseless samples taken on a set with sampling rate 2N−1. We propose an algorithm to reconstruct nonseparable signals in a shift-invariant space generated by a compactly supported continuous function φ. The proposed algorithm is robust against bounded sampling noise and it could be implemented in a distributed manner.