引用本文:唐磊, 赵春霞, 唐振民, 成伟明, 张浩峰.基于模糊自适应Kalman滤波的GPS/DR数据融合[J].控制理论与应用,2007,24(6):891~894.[点击复制]
TANG Lei, ZHAO Chun-xia, TANG Zhen-min, CHENGWei-ming, ZHANG Hao-feng.GPS/DR data fusion based on fuzzy adaptive Kalman filter[J].Control Theory and Technology,2007,24(6):891~894.[点击复制]
基于模糊自适应Kalman滤波的GPS/DR数据融合
GPS/DR data fusion based on fuzzy adaptive Kalman filter
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DOI编号  10.7641/j.issn.1000-8152.2007.6.005
  2007,24(6):891-894
中文关键词  联邦Kalman滤波器  模糊自适应  数据融合
英文关键词  GPS/DR  federated Kalman filter  fuzzy adaptive  data fusion
基金项目  江苏省自然科学基金资助项目(BK2004130); 国防基础重点技术研究项目.
作者单位
唐磊, 赵春霞, 唐振民, 成伟明, 张浩峰 南京理工大学计算机科学与技术学院, 江苏南京210094 
中文摘要
      针对标准Kalman滤波器对系统模型依赖性强、鲁棒性差, 而GPS/DR系统的准确数学模型难以建立的问题, 提出了一种模糊自适应联邦卡尔曼滤波器(FAFKF). 首先通过模糊自适应滤波控制器监控观测量的残差理论值和实际值, 并通过实时增强它们的一致性来调整各子系统观测噪声方差阵, 使之更符合真实的模型, 有效提高了Kalman滤波器对模型变化的适应能力. 然后通过模糊自适应信息融合控制器对各子系统可信度进行模糊评判,并根据可信度自适应地计算信息分配系数来实现数据的融合. 理论分析和实验数据表明该滤波器在滤波精度、容错性能上都有了很大的提高.
英文摘要
      Standard Kalman filter strongly depends on the system model. Unfortunately, an accurate mathematical model of GPS(global positioning system)/DR(dead reckoning) system is difficult to set up, so a fuzzy adaptive federated Kalman filter (FAFKF) is presented for the problem. First, a real-time fuzzy adaptive filter controller is used to monitor the real value and theoretical value of residual covariance, and adjust the covariance matrices of observation noises towards the real model by enhancing their consistencies. As a result, the Kalman filter’s tolerance to model error is improved. Then a fuzzy adaptive data fusion controller is used to evaluate the reliability of each subsystem, and the information distribution coefficients of each subsystem is computed according to the reliability. Theoretical analysis and experimental data show that both the precision and fault tolerance of FAFKF are improved.