摘要
在当前统计模型的基础上,提出了一种基于当前统计模型(CS)的模糊自适应算法(CSFA)。该算法使用了模糊推理技术,使系统状态噪声方差随着机动特性能够自适应调整,提高了系统在目标作非机动或者弱机动时的跟踪精度以及在强机动时的快速响应能力。蒙特卡罗仿真结果表明了该算法的有效性。
A fuzzy adaptive tracking algorithm for maneuvering target based on current statistical model is presented. The fuzzy inference technique is used to adjust the system process noise covariance adaptively along with the characteristic of maneuvering, which improves both the estimation accuracy when the target is not in the maneuvering state and the rapid response when the target maneuvers rapidly. The Monte-Carlo simulation results show the method is valid.
出处
《系统仿真学报》
CAS
CSCD
2004年第6期1181-1183,1186,共4页
Journal of System Simulation
基金
"十五"国防科技预研课题(413060301)
国防基金课题(J23-1.5)。
关键词
当前统计模型
机动目标跟踪
模糊推理
滤波
current statistical model
maneuvering target tracking
fuzzy inference
filter