摘要
针对空空导弹制导过程中可能出现测量信息不全的情况,以机动目标的“当前”统计模型为基础,在螺旋机动目标模型下对机动目标进行了跟踪滤波。在深入研究了扩展卡尔曼滤波算法、衰减记忆扩展卡尔曼滤波算法的基础上,利用改进的强跟踪滤波算法进行了非全测状态下的机动目标运动信息估计。仿真实验表明:改进的强跟踪滤波算法不仅能很好地完成速度和距离跟踪;如果加上多普勒速度测量,改进的强跟踪滤波算法还可跟踪上加速度。仿真结果表明了改进的强跟踪滤波算法的有效性。
Aiming at the situation without all measurement information in the air-to-air missile guidance, based on the maneuvering target ＂current＂ statistical model, this paper is dedicated to the maneuvering target tracking problem under the spiral maneuvering target model. On the basis of the extended Kalman Filter （EKF） and the decaying extended Kalman Filter, this paper makes use of the modified strong tracking filter （STF） to estimate the maneuvering target information without all measurement information. Simulation experiment shows that the modified STF can not only track velocity and distance but also track acceleration with one more Doppler velocity measurement. Simulation results indicate that the modified STF is effective in some degree.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2007年第2期197-200,共4页
Systems Engineering and Electronics
关键词
机动目标跟踪
跟踪滤波
卡尔曼滤波
maneuvering target tracking
tracking filter
Kalman filter
