Active suspension systems aim at increasing safety by improving vehicle ride and handling performance while ensuring superior passenger comfort. Good control of this active system can only be achieved by providing the control algorithm with reliable and accurate signals for the required quantities. This paper presents the design and development of a state estimator that accurately provides the information required by a sky-hook controller, using a minimum of sensors. The vehicle inertial parameters are estimated by an algorithm based on Monte Carlo simulations and anthropometric data. All state updating is performed using Kalman filters. The resulting performance enhancement has been proven during test drives.