Multireference Alignment is Easier with Nonperiodic Distribution

Multireference alignment is the problem of estimating a signal from its circularly translated copies in the presence of noise. We show that in the regime of low SNR, the distribution of translations plays a significant role in terms of the required number of samples. We use lower-order statistics for solving the problem, establish some theoretical guarantees, and introduce practical methods.