To improve the tracking accuracy and stability of an optic-electronic target tracking system,the concept of generalized synergic target and an algorithm named error-space estimate method is presented.In this algorithm...To improve the tracking accuracy and stability of an optic-electronic target tracking system,the concept of generalized synergic target and an algorithm named error-space estimate method is presented.In this algorithm,the motion of target is described by guide data and guide errors,and then the maneuver of the target is separated into guide data and guide errors to reduce the maneuver level.Then state estimate is implemented in target state-space and error-space respectively,and the prediction data of target position are acquired by synthesizing the filtering data from target state-space according to kinematic model and the prediction data from errorspace according to guide error model.Differing from typical multi-model method,the kinematic and guide error models work concurrently rather than switch between models.Experiment results show that the performance of the algorithm is better than Kalman filter and strong tracking filter at the same maneuver level.展开更多
基金supported by the Hi-Tech Research and Development Program of China.
文摘To improve the tracking accuracy and stability of an optic-electronic target tracking system,the concept of generalized synergic target and an algorithm named error-space estimate method is presented.In this algorithm,the motion of target is described by guide data and guide errors,and then the maneuver of the target is separated into guide data and guide errors to reduce the maneuver level.Then state estimate is implemented in target state-space and error-space respectively,and the prediction data of target position are acquired by synthesizing the filtering data from target state-space according to kinematic model and the prediction data from errorspace according to guide error model.Differing from typical multi-model method,the kinematic and guide error models work concurrently rather than switch between models.Experiment results show that the performance of the algorithm is better than Kalman filter and strong tracking filter at the same maneuver level.
