In this contribution, we present a new approach for the estimation of the parameters of exponentially damped si-nusoids based on the second order statistics of the observations. The method may be seen as an extension of the minimum norm principal eigenvectors method (see 1]) to cyclo-correlation statistics domain. The proposed method exploits the nullity property of the cyclo-correlation of stationary processes at non-zero cyclo-frequencies 2]. This property allows in a pre-processing step to get rid from stationary additive noise. This approach presents many advantages in comparison with existing higher order statistics based approaches 3]: (i) First it deals only with second order statistics which require generally few samples in contrast to higher-order methods, (ii) it deals either with Gaus-sian and non-Gaussian additive noise, and (iii) also deals either with white or temporally colored (with unknown au-tocorrelation sequence) additive noise. The eeectiveness of the proposed method is illustrated by some numerical simulations .