Frequency estimation based on the cumulated Lomb-Scargle periodogram
  We consider the problem of estimating the period of an unknown periodic function observed in additive noise sampled at irregularly spaced time instants in a semiparametric setting. To solve this problem, we propose a novel estimator based on the cumulated Lomb-Scargle periodogram. We prove that this estimator is consistent, asymptotically Gaussian and we provide an explicit expression of the asymptotic variance. Some Monte-Carlo experiments are then presented to support our claims. 
C\'eline L\'evy-Leduc (LTCI), Eric Moulines (LTCI), Fran\c{c}ois   Roueff (LTCI)