摘要
针对组合导航观测个数少、采用单因子自适应滤波会损失间接可测参数精度的问题,利用预测残差和选权滤波思想构造了分类自适应因子。实测算例计算结果表明,该算法不仅能够很好地控制状态扰动异常影响,而且还能避免损失间接可测参数的精度,进一步提高了导航精度。
In GPS/INS integrated navigation,the number of observations is usually less than that of the state parameters,and the single adaptive factor is usually applied in Kalman filtering,which can lead to precision loss of indirect observational parameters.A new algorithm of classified adaptive filtering is presented based on predicted residuals and selecting weight filtering,and the corresponding formulas are given.Finally,an actual calculation is given.The new algorithm can not only degrade the influence of the disturbances from the state but also avoid the loss of estimated precision of indirect observational parameters,and improve the accuracy of the navigation further.
出处
《武汉大学学报（信息科学版）》
EI
CSCD
北大核心
2012年第3期261-264,共4页
Geomatics and Information Science of Wuhan University
基金
国家自然科学基金资助项目(41004013
41020144004)
卫星导航与定位教育部重点实验室开放基金资助项目(CRC-2009003)
关键词
预测残差
选权滤波
分类因子
GPS/INS
predicted residual
selecting weight filtering
classified factors
GPS/INS
