文章摘要
引用本文:左云龙,尹伟伟,高敬东,李开龙.基于变分贝叶斯的自适应鲁棒滤波算法[J].导航定位与授时,2017,(5):48-53 本文二维码信息
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基于变分贝叶斯的自适应鲁棒滤波算法
Adaptive Robust Filtering Algorithm Based on Variational Bayesian
  
DOI:
中文关键词:  卡尔曼滤波  变分贝叶斯  鲁棒  自适应
English Keywords:Kalman filter  Variational Bayes  Robust  Adaptive
基金项目:国家自然科学基金(61374206);国家自然科学基金(61304241);国家自然科学基金(61703419);海军工程大学自主立项项目(20161576)
作者单位
左云龙 海军工程大学导航工程系武汉 430000 
尹伟伟 海军902厂上海 200083 
高敬东 海军工程大学导航工程系武汉 430000 
李开龙 海军工程大学导航工程系武汉 430000 
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中文摘要:
      针对组合导航姿态估计中,观测同时受到野值与时变观测噪声影响的问题,构造一种基于变分贝叶斯的自适应鲁棒滤波算法。该算法可以有效地解决自适应与鲁棒滤波策略的矛盾,利用变分贝叶斯近似估计变换的观测噪声,在变分贝叶斯的滤波框架内,利用Huber滤波鲁棒化方法处理连续野值。在组合导航姿态估计试验中,验证了该算法具有良好的自适应与鲁棒性,并能够保持较高的估计精度。
English Summary:
      In this paper, an adaptive robust filtering algorithm based on variational Bayesian method is proposed to solve the problem of the simultaneous observation of outliers and time varying noises in the attitude estimation of integrated navigationThe algorithm can effectively solve the contradiction between the adaptive and robust filtering strategy, using variational Bayesian approximation to estimate the observation noise transformation, anddeal with continuous outliers by using Huber filter robust method in the variational Bayesian filtering frameworkIn the integrated navigation attitude estimation experiment, it is proved that the algorithm has good adaptability and robustness, and maintains high estimation accuracy.
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