Estimating the center of mass position and the angular momentum derivative of legged systems is essential for both controlling legged robots and analyzing human motion. In this paper, a novel recursive approach to concurrently and accurately estimate these two quantities together is introduced. The proposed method employs kinetic and kinematic measurements from classic sensors available in robotics and biomechanics, to effectively exploits the accuracy of each measurement in the spectral domain. The soundness of the proposed approach is first validated on a simulated humanoid robot, where ground truth data is available, against an Extend Kalman Filter. The results demonstrate that the proposed method reduces the estimation error on the center of mass position with regard to kinematic estimation alone, whereas at the same time, it provides an accurate estimation of the derivative of angular momentum. Finally, the effectiveness of the proposed method is illustrated on real measurements, obtained from walking experiments with the HRP-2 humanoid robot.