摘要
提出了一种利用UKF算法实现对机动目标进行无源定位与跟踪的滤波方法.仿真结果表明,与扩展卡尔曼滤波器相比,UKF算法的滤波精度和稳定性都有了明显提高.该算法能更好地解决测量模型非线性问题条件下的单站无源定位跟踪问题.
Application of unscented Kalman filter（UKF）to the passive location tracking system is presented.The simulation results showed that the precision and stability of UKF were greatly improved compared with those of EKF.It can be concluded that UKF solves the problem of non-linearity of observation model better.
出处
《吉首大学学报（自然科学版）》
CAS
2014年第6期70-72,共3页
Journal of Jishou University(Natural Sciences Edition)
基金
总装备部基金资助项目(5140104C703CB0102)
关键词
无迹变换
时空信息
非线性
unscented transformation
temporal and spatial information
non-linearity
