The performance of tracking algorithm may be seriously degraded due to the sudden state change of target.To improve the performance for maneuvering target tracking,a weight-based multi-innovation amendment algorithm with maneuvering detection is put forward.Firstly,in order to judge the moment of maneuvering precisely,we proposed a maneuvering detection algorithm based on the double error ellipses, which can increase the sensitivity to maneuvering by setting bilateral threshold.Then to decrease the maneuvering deviation caused by delayed amendment,we built up a mapping relationship between the distance and the weight based on Euclidean distance between the predicted measurement and the actual measurement.From the mapping relationship,the weight of the pre-amendment information was obtained and the utilization ratio of implicit information was improved.Finally,the simulation results of three scenarios indicated that the proposed algorithm is effective.Compared with the standard Kalman filter and adaptive fading Kalman filter,the proposed method has a higher cost-benefit ratio for both highly and weakly maneuvering target tracking.