This paper proposes a recursive solution as an estimation strategy that incorporates non-uniform sampled measurements for a Linear Time-Invariant (LTI) Systems. The estimator is based on a modified Receding Horizon Estimator. The proposed approach allows system states to be recursively estimated, reducing estimation error by including measurements available at different sampling times, using a well-known structure. A discussion of the observability of the system in the presence of non-uniform measurements and the convergence conditions of the proposed estimator are also presented. Finally, numerical simulation demonstrates the effectiveness of the proposed estimator in comparison with a method using a Kalman filter with augmented state widely reported in the literature.