摘要
提出了一种基于模糊联合卡尔曼滤波器的信息融合方法。这一方法主要应用于机场泊位系统中,解决基于单一传感器的引导系统当测量值发生波动时系统可靠性降低的问题。该方法通过监视测量值是否发生波动,应用模糊推理系统调整各局部滤波器输出状态向量的协方差阵,对全局滤波器内各融合信息的权值在线修正,降低波动数据的影响。通过实验证明了该算法对测量值波动情况有较强的鲁棒性,有助于提高机场泊位系统的可靠性。
This paper presents a novel method based on Fuzzy Federal Kalman Filtering . This method is mainly used for the Airport Automatic Docking Guidance System to improve the reliability of the system while the measure values of sensors fluctuated. By monitoring if the measure values are fluctuated, this algorithm modifies the state vector covarianee of each local filtering using the Fuzzy Inference System （FIS） to modify the weight of each fusion data online in main filtering, accordingly reduce the disturbance of the fluctuation data. Experiment results prove that this algorithm is feasible to improve the reliability of the system.
出处
《微计算机信息》
北大核心
2008年第30期32-34,共3页
Control & Automation
