关键词: 目标跟踪, 转弯率, 交互式多模型, 反向传播（BP）神经网络, 特征向量

Abstract: As the Interacting Multiple Model（IMM） algorithm on target tracking adopts the cooperative turn model as one of the models, the difficulty of realtime turn rate estimation and low precision leads to tracking accuracy decreasing, a IMM algorithm is proposed innovatively based on new adaptive turn model. The trajectory feature vector is constructed by using three methods of mapping turn rate, and the average turning rate of the trajectory segment in the time window is estimated in real time through the trained BP（Back Propagation） neural network, so that the accuracy of turning rate estimation is improved, and the tracking accuracy is improved. Simulation experiments show that the proposed IMM algorithm based on adaptive turning model has higher tracking accuracy than the IMM algorithm of traditional adaptive turning model when the turn rate is large, which has high scalability and development prospects.

Key words: target tracking, turn rate, interacting multiple model, Back Propagation（BP） neural network, feature vector