本文提出了一种基于强跟踪滤波器的自适应故障预报方法，能够对一类带时变参数的非线性系统进行故障预报。
This paper presents an adaptive fault prediction method based on strong tracking filter, which can predict faults in a class of nonlinear time varying systems.
针对线性随机系统提出了一种改进强跟踪卡尔曼滤波器(MSTKF)。
A modified strong tracking Kalman filter (MSTKF) for linear stochastic systems is proposed.
针对卡尔曼滤波器对系统模型依赖性强、鲁棒性差和跟踪机动目标能力有限的问题，提出了一种新的利用混合模糊逻辑和标准卡尔曼滤波器的联合算法。
The Kalman filter has been commonly used in target tracking, however its performance may be degraded in presence of maneuver, low robustness and strong model dependence.
应用推荐