目前国内的行人导航系统一般采用北斗卫星导航系统(英语:COMPASS,中文音译名称BeiDou)和微机电系统M E M S(英语:Mmicroelectromechanical System,缩写为MEMS)组合导航的方式进行定位,其定位精度容易受到BD定位数据中的误差,特别是定位...目前国内的行人导航系统一般采用北斗卫星导航系统(英语:COMPASS,中文音译名称BeiDou)和微机电系统M E M S(英语:Mmicroelectromechanical System,缩写为MEMS)组合导航的方式进行定位,其定位精度容易受到BD定位数据中的误差,特别是定位粗差的影响。粗差可能会导致完全错误的定位结果。为了减少这种影响,本文提出了基于抗差卡尔曼滤波的BD/MEMS紧耦合算法,可以在一定程度上提高定位的精度。本算法首先对BD/MEMS进行基于伪距、伪距率的紧耦合定位建模,然后输入抗差卡尔曼中进行滤波校正反馈。通过实测数据的仿真分析表明,在BD定位误差较大或含有粗差的情况下,该算法可以明显的剔除粗差,减小导致定位完全错误的可能性,有效地提高了定位导航精度。展开更多
In micro-electro-mechanical system based inertial navigation system（MEMS-INS）/global position system（GPS） integrated navigation systems, there exist unknown disturbances and abnormal measurements. In order to obta...In micro-electro-mechanical system based inertial navigation system（MEMS-INS）/global position system（GPS） integrated navigation systems, there exist unknown disturbances and abnormal measurements. In order to obtain high estimation accuracy and enhance detection sensitivity to faults in measurements, this paper deals with the problem of model-based robust estimation（RE） and fault detection（FD）. A filter gain matrix and a post-filter are designed to obtain a RE and FD algorithm with current measurements, which is different from most of the existing priori filters using measurements in one-step delay. With the designed filter gain matrix, the H-infinity norm of the transfer function from noise inputs to estimation error outputs is limited within a certain range; with the designed post-filter, the residual signal is robust to disturbances but sensitive to faults. Therefore, the algorithm can guarantee small estimation errors in the presence of disturbances and have high sensitivity to faults. The proposed method is evaluated in an integrated navigation system, and the simulation results show that it is more effective in position estimation and fault signal detection than priori RE and FD algorithms.展开更多
文摘目前国内的行人导航系统一般采用北斗卫星导航系统(英语:COMPASS,中文音译名称BeiDou)和微机电系统M E M S(英语:Mmicroelectromechanical System,缩写为MEMS)组合导航的方式进行定位,其定位精度容易受到BD定位数据中的误差,特别是定位粗差的影响。粗差可能会导致完全错误的定位结果。为了减少这种影响,本文提出了基于抗差卡尔曼滤波的BD/MEMS紧耦合算法,可以在一定程度上提高定位的精度。本算法首先对BD/MEMS进行基于伪距、伪距率的紧耦合定位建模,然后输入抗差卡尔曼中进行滤波校正反馈。通过实测数据的仿真分析表明,在BD定位误差较大或含有粗差的情况下,该算法可以明显的剔除粗差,减小导致定位完全错误的可能性,有效地提高了定位导航精度。
基金co-supported by the National Natural Science Foundation of China(No.61153002)the Aeronautical Science Foundation of China(No.20130153002)
文摘In micro-electro-mechanical system based inertial navigation system（MEMS-INS）/global position system（GPS） integrated navigation systems, there exist unknown disturbances and abnormal measurements. In order to obtain high estimation accuracy and enhance detection sensitivity to faults in measurements, this paper deals with the problem of model-based robust estimation（RE） and fault detection（FD）. A filter gain matrix and a post-filter are designed to obtain a RE and FD algorithm with current measurements, which is different from most of the existing priori filters using measurements in one-step delay. With the designed filter gain matrix, the H-infinity norm of the transfer function from noise inputs to estimation error outputs is limited within a certain range; with the designed post-filter, the residual signal is robust to disturbances but sensitive to faults. Therefore, the algorithm can guarantee small estimation errors in the presence of disturbances and have high sensitivity to faults. The proposed method is evaluated in an integrated navigation system, and the simulation results show that it is more effective in position estimation and fault signal detection than priori RE and FD algorithms.
