摘要
针对机载IRST系统被动测距问题,给出了一种简化的UKF(SUKF)算法。算法无需对状态变量进行扩维,对于线性状态方程使用了和卡尔曼滤波相同的时间更新方法,对于非线性测量方程保持了UKF的特征,既继承了UKF的优点又减小了算法的运算量。仿真结果表明,SUKF在测距精度和收敛速度上明显优于EKF,其性能与标准UKF相同但计算耗时少,适合于机载IRST系统被动测距的实时处理。
To solve the problem of airborne IRST passive ranging,a new algorithm of Simplified Unscented Kalman Filter（SUKF） was proposed,which did not need augment the dimension of state variable.For linear state equations,the algorithm used the same time updating method as that of the Kalman filter;for nonlinear measure equations,the characteristics of UKF were kept thus the computation cost was reduced and the advantages of UKF were inherited.The simulation results show that SUKF is markedly superior to EKF in passive ranging accuracy and convergence speed,and can achieve the same performance as UKF with shorter time cost on calculation.The SUKF is suitable for real-time processing in the airborne IRST passive ranging.
出处
《电光与控制》
北大核心
2012年第2期63-67,共5页
Electronics Optics & Control
基金
国家自然科学基金(60904038)
航空科学基金(20095196012)
光电控制技术重点实验室资助课题
关键词
机载IRST系统
被动测距
非线性滤波
简化UKF算法
airborne infrared search and track system
passive ranging
nonlinear filter
simplified unscented Kalman filter
