基于自适应扩展H_∞滤波的机动目标被动跟踪  

Maneuvering target passive tracking based on adaptive extended H_∞ filter

作　　者：周航[1] 冯新喜[1] 王蓉[1] 张婧[1] 

机构地区：[1]空军工程大学信息与导航学院,陕西西安710077

出　　处：《系统工程与电子技术》2013年第2期256-262,共7页Systems Engineering and Electronics

基　　金：国家自然科学基金(60805015);空军装备部资助项目(KJ09131);陕西省自然科学基金(2011JM8023)资助课题

摘　　要：为提高对机动目标的跟踪效果,提出了一种基于扩展H∞滤波的自适应交互多模多被动传感器机动目标跟踪算法。利用简化的Sage-Husa自适应滤波器与交互多模相结合,对多被动传感器测得的目标角度信息进行融合,解决了被动式跟踪系统的可观测性及非线性问题,将扩展H∞滤波器作为模型条件滤波器,通过调节扩展H∞滤波器参数和量测噪声预测协方差矩阵,增强了对外界干扰的鲁棒性。仿真结果表明,所提算法比扩展卡尔曼滤波交互多模算法和标准交互多模算法具有更高的跟踪性能,在多站被动红外搜索与跟踪中是一种有效的跟踪算法。To improve the performance of maneuvering target tracking, an interacting multiple model （IMM） algorithm is proposed based on the adaptive extended H∞ filter. The improved Sage-Husa adaptive filter is intergrated with the IMM model to fuse the measurements of multiple passive sensors to alleviate the unob- servability and the nonlinearity simultaneously. The extended H∞filter works as the model-conditional filter. Its parameters and observed noise predicted covariance matrix are adjusted for robustness. The simulation re- sults show that the extended H∞ fusion tracking algorithm has higher tracking precision than the extended Kal- man filter interacting multiple model and the traditional interacting multiple model. The extended H∞ fusion tracking algorithm is an effective tracking algorithm for the multiple stations passive infrared search and tracking system.

关 键 词：机动目标跟踪 纯方位跟踪 扩展H∞滤波 集中融合 

分 类 号：TN953[电子电信—信号与信息处理]