Ultrasonic distance measurement and data fusion to aid estimators with initialisation mechanisms

We present a solution for two problems for the precise perception of the environment, distance measurement using an ultrasonic transducer and data fusion for positioning a detected object. The distance measurement algorithm is based on the measurement of time of flight and is determined by intercorrelation between a function of the signal emitted and the signal received. The data fusion is employed for estimating the tangent from the point measured to the object detected. The fusion is effected by the recursive least squares identification algorithms and is based on a Kalman filter, with initialisation of the covariance matrix conditioned by an estimation of a large variation error and with immunity to repetitive initialisation. The distance measurement is validated by experiment and the data fusion by simulation.