根据实际的应用背景,对标准的UKF算法进行简化,提出一种SUKF(Simplified Unscented Kalman Filter)算法,并将其应用于无源目标跟踪。对实测数据的滤波结果表明,SUKF不仅运算复杂度低(与经典EKF相当,比UKF大大简化),而且收敛速度快、一致性好,跟踪精度高(达到了UKF同样的性能),非常适合于实时应用的场合。

A novel algorithm named Simplified Unscented Kalman Filter is proposed and is applied to passive target tracking.The algorithm is derived from conventional Unscented Kalman Filter based on specific application condition(for system with additive noise or partially linear).Experiment results show that the proposed algorithm has lower computational complexity(very close to classical EKF) than UKF,and outperforms EKF at convergence speed,consistency and tracking precision.Compared with UKF,it loses no performance and is very suitable for real-time application.

TN958.97 TN957.52