Sensor Position Identification and Vehicle State Estimation Using The Extended Kalman Filter

In this paper, an extended Kalman filter (EKF) based identification method for longitudinal and lateral sensor's positions is proposed. The previous works which have shown the effectiveness of Kalman observer for estimating states and parameters of the vehicle have motivated the presented one. This method is very effective because it provides to know at the same time an estimate of the sensor location and the vehicle state components. It uses a lateral model of the vehicle with three degrees of freedom (lateral translation, yaw rate and roll rate).