# A Comprehensive Review of GNSS/INS Integration Techniques for Land and Air Vehicle Applications
## 2 GNSS/INS Integration Techniques
To improve the reliability and performance of the integrated INS/SNS system, various modifications of the integration algorithm based on the Kalman filter are used. For example, the use of neural networks for learning to predict the motion of GNSS satellites during the periods when their measurements are unavailable [15; 24], the use of a robust Kalman filter to eliminate outliers in the measurements of the position and velocity of GNSS satellites, unscented Kalman filter [35; 63; 64]. The accuracy of various implementations of loosely coupled and tightly coupled integrated systems in terms of mean error or root mean square error (RMSE) characterizing the deviation of estimated data from reference data are provided in Table 1 and Table 2, respectively. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Publication**} & **RMSE/Mean** & **RMSE/** & **RMSE/Mean** & **RMSE/** & **RMSE/** & **Mean** & **Integration** & **Improving** \\  & **Position [NED]/** & **Mean Position** & **Velocity** & **Mean** & **Attitude** & **Technique** & **Method** \\  & **[Lat,Lon,Alt]** & **3D** & **[\(\mathbf{v}_{N}\), \(\mathbf{v}_{E}\), \(\mathbf{v}_{D}\)]** & **Velocity** & **3D** & **[P,R,Y]** & & \\ \hline \multirow{3}{*}{Integrated INS/GPS Navigation System [2]} & RMSE & & RMSE & & & & \\  & N = 2.379 m & - & \(\mathbf{v}_{N}=0.3067\) m/s & - & - & 15-state KF & Update rate & increasing \\  & & \(\mathbf{v}_{E}=1.010\) m & \(\mathbf{v}_{E}=0.1048\) m/s & - & - & & \\  & D = 3.438 m & & \(\mathbf{v}_{D}=0.9269\) m/s & & & & \\ \hline \multicolumn{10}{c}{The Performance Analysis of a Real-Time Integrated INS/GPS Vehicle Navigation \(\text{E}=6.0\) m } & RMSE & RMSE & RMSE & & & \\  & D = 22.3 m & \(\mathbf{v}_{E}=0.35\) m/s & RMSE & \(\mathbf{P}=0.26^{\circ}\) & 15-state KF & - \\  & & \(\mathbf{v}_{E}=0.54\) m/s & \(\mathbf{v}_{E}=0.15^{\circ}\) & \(\mathbf{v}_{D}=0.22\) m/s & & \(\mathbf{Y}=9.02^{\circ}\) & \\  & & & & & & & \\ \hline \multicolumn{10}{c}{Performance analysis of GNSS/INS loosely coupled integration N \(\text{N}=0.01\) m } & RMSE & & RMSE & & & \\  & & \(\mathbf{v}_{N}=0.005\) m/s & - & \(\mathbf{P}=0.009^{\circ}\) & 15-state KF & Smoothing in \\  & systems under GNSS & \(\mathbf{\varepsilon}=0.02\) m & - & \(\mathbf{v}_{E}=0.005\) m/s & - & \(\mathbf{R}=0.007^{\circ}\) & 15-state KF & postprocessing \\  & signal blocking & D = 0.011 m & \(\mathbf{v}_{D}=0.006\) m/s & & \(\mathbf{Y}=0.007^{\circ}\) & & smoothing \\  & environment [11] & & & & & & \\ \hline \multicolumn{10}{c}{Performance Evaluation of GPS/INS Main} & RMSE & - & \(\mathbf{v}_{N}=0.1013\) m/s & - & - & 18-state KF & - \\  & Integration Approach [12] & Lon = 0.000228\({}^{\circ}\) & - & \(\mathbf{v}_{E}=0.227\) m/s & & & & \\  & & & \(\mathbf{v}_{D}=0.0\) m/s & & & & & \\ \hline \multicolumn{10}{c}{A modified loosely coupled approach [13]} & - & Mean & - & Mean & - & 15-state KF & \multicolumn{10}{c}{DOP of real GPS satellites} \\ \hline \multicolumn{10}{c}{A modified loosely coupled approach to INS/GPS integration [13]} & - & Mean & - & Mean & - & 15-state KF & \multicolumn{10}{c}{DOP of artificial GPS satellites} \\ \hline \multicolumn{10}{c}{Bridging GPS outages} & RMSE & & & & & \\  & & Lat = 4.7 m & - & - & - & - & \multicolumn{10}{c}{Al-base segmented forward network network network network network} \\ position and velocity & \(\text{Alt}=3.6\) m & & & & & & & \\ \hline \multicolumn{10}{c}{A new method of seamless land} & RMSE & - & - & - & 14-state KF & \multicolumn{10}{c}{In SINS, wavelet multi-resolution} \\ \multicolumn  
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\begin{tabular}{c c c c c c c c c} \hline \hline  
on the basis of which the attitude of the object and gyro sensor static bias are subsequently calculated. In [67], the Kalman filter is used integrate the AHRS and GNSS measurements. It estimates the attitude described by the quaternion and the gyro sensor static bias, and GNSS measurements are used to correct the acceleration determined by the accelerometer.