Tightly coupled INS/GNSS based on Robust Extended Kalman Filter algorithm is researched aiming at the observation outliers of GNSS in the INS/GNSS integrated navigation.Firstly,the INS error equations resolved into the Local Lever Frame as well as the INS/GNSS tightly coupled measurement equations are given.Secondly,the resolved model based on least-square algorithm is constructed according to the measurement equations and the equal weight covariance is constructed by the least square residual statistic,then calculation steps are given.Finally,measured data are processed to verify the algorithm.Results show that: when the outliers exist in GNSS observations,the tightly coupled INS/GNSS integration based on Robust Extended Kalman Filter can weaken the impact of the observation outliers effectively,and can improve the precision of integrated navigation system.

In order to improve GNSS integrity,a new integrity monitoring method of GNSS aided by INS with considering the phase Doppler smoothing code is proposed.In this algorithm,by the use of phase Doppler smoothing code to reduce the random error,the parity vector can be obtained by using measurement derived from INS and GNSS for fault detection and isolation.The simulative results show that the integrity monitoring method of GNSS aided by INS can increase the fault detection rate,when considering the phase Doppler smoothing code the performance improvement is more significant.