一种新的模糊控制多模型算法在目标跟踪中的应用

摘要

An innovative snakelike terminal maneuvering trajectory model of anti⁃ship missiles, in which the missiles are regarded as controllable mass points and can be tracked by passive sensors, is introduced to compete with the continuous penetrating enhancing of modern anti⁃ship missiles by adopting dynamic modeling method. A novel adaptive unscented Kalman filter algorithm based on the fuzzy control interacting multiple algorithm is proposed. The proposed algorithm can achieve the real⁃time adjustment of the matrix of transition probability, faster convergence rate due to the fuzzy control and state error covariance adaptive algorithm which is based on the principle of Sage⁃Husa noise statistical estimator. Simulation results verify the ballistic model is established for the detection, recognition and tracking of anti⁃ship missile technology research has certain reference value. Besides, the improved tracking algorithm can quickly adjust the probability model to bring about faster convergence speed and better robustness, which can effectively reduce the error of bearing⁃only target tracking and can achieve the stability and reliability of the snakelike terminal maneuvering trajectory model of anti⁃ship missiles.%为解决传统的蛇形建模方法不能反映出反舰导弹典型运动特性的问题，引入动力学建模方法研究弹道问题，把导弹视为可控质点，建立了反舰导弹末端蛇形机动弹道模型。采用被动传感器进行跟踪，提出一种新的基于模糊控制的交互式多模型自适应无迹卡尔曼滤波算法，根据Sage－Husa噪声统计估值器的原理提出了状态误差协方差自适应算法，克服了传统噪声自适应算法在目标发生强机动时收敛速度慢的缺点，同时利用模糊控制方法实现了实时调整交互式多模型算法中的转换概率矩阵。仿真实表明：所建立的弹道模型对探测、识别和跟踪反舰导弹技术的研究有一定的参考价值；改进的跟踪算法能够快速调整模型概率，使得其估计误差的收敛速度比交互式多模型算法更快，鲁棒性更强，并且能够有效降低纯方位目标跟踪的误差，实现对反舰导弹末端蛇形弹道模型的稳定跟踪。