Tracking a maneuvering target using sensors of variable quality

In an environment subject to sudden change, the accuracy of tracking and pr ediction is strongly influenced both by the sensor architecture and by the quality of the sensors. An image-enhanced algorithm is presented for both p ath following and covariance estimation in applications where the sensors a re subject to sudden and unpredictable variation in quality. For an illustr ative trajectory, the performance of the algorithm is contrasted with an ex tended Kalman filter (EKF) and an image-enhanced algorithm based upon the n ominal sensors.