摘要
采用“当前”统计模型、匀加速模型以及匀速模型 ,运用交互式多模型算法的思想 ,提出了一种用于机动目标跟踪的交互式多模型自适应滤波算法。基本思路是上述三种模型并行工作 ,利用马尔可夫切换系数在它们之间进行切换 ,目标状态估计是上述三种模型交互作用的结果。蒙特卡罗结果表明该算法不仅克服了上述三种模型各自的缺点 ,提高了对机动目标的跟踪精度 ,同时具有全面自适应跟踪能力。
A new Interacting Multiple Model(IMM)adaptive filtering algorithm is presented.In this algorithm“Current”statistical model、constant velocity model and constant acceleration model are running in parallel,Markovian switching coefficients jump between these models,target status estimation is the result of interaction of these models.The comparison of the new algorithm with the three models are evaluated through Monte-Carlo simulation.The results show that this algorithm not only overcomes the shortcoming of adaptive Kalman filtering algorithm with these three models,improves the tracking accuracy for maneuvering targets,but also has the capability of “overall”adaptive tracking.
出处
《火力与指挥控制》
CSCD
2000年第4期36-38,42,共4页
Fire Control & Command Control
