# A Comprehensive Review of GNSS/INS Integration Techniques for Land and Air Vehicle Applications
## 4 Main Problems of GNSS/INS Integration and Their Solutions  
The review identified several key challenges faced by developers of integrated INS/ GNSS systems:  
* unavailability of GNSS signals, leading to the accumulation of errors in determining the position and velocity of the object due to the functioning of the integrated system in the INS mode;
* the presence of outliers and violation of integrity of GNSS measurements due to multipath effect, ionospheric and tropospheric effects, interference and environmental factors, which can lead to instability of INS measurements;the presence of errors and effects due to the characteristics of the sensors used in the integrated system, such as static and dynamic bias of the INS, lever arm effect, crosslinks, etc. Table 3 provides a comparative description of various approaches to the implementation of integrated INS/GNSS systems with complete or partial unavailability of GNSS signals. In the considered publications, the capabilities of integrated INS/GNSS systems were studied with up to four available navigation satellites and the absence of a navigation signal up to 1200 s.  
The neural networks are used to restore a temporarily absent GNSS signal in most of the works considered. Positioning accuracy of these systems reaches 4 m. Definitely, the characteristics and quality of GNSS receivers and INS sensors are of great importance as the integrated system actually operates in the INS mode in the periods of absence of GNSS signal. This increases the requirements for the accuracy and reliability of INS sensors. In particular, the accuracy of the integrated system is up to \(5\times 10^{-7}\) degrees in longitude and latitude in [15], where the gyro sensor with a constant bias \(<0.01^{\circ}\)/h, an accelerometer with a constant bias \(<50\)\(\upmu\)g and NovAtel FlexPark6 dual-frequency GNSS receiver were used. In [24], an accuracy in longitude and latitude of up to 25 m was achieved using two NovAtel OEM-4 GNSS receivers, a gyro sensor with a constant bias \(1^{\circ}\)/h and an accelerometer with a constant bias \(0.3\)\(\upmu\)g. Two Novatel OEM-4 GNSS receivers, the INS Honeywell HG 1700 with gyro sensor bias \(1^{\circ}\)/h and accelerometer bias \(1\)\(\upmu\)g, were used in [37], which made it possible to achieve an accuracy of 18 m in a northerly direction and 80 m in an easterly direction. The best accuracy of 8.33 m in the north direction and 2.94 m in the east direction in the considered publications using neural networks was obtained in [38] using the NovAtel OEM-4 GNSS receiver, CIMU INS with gyro sensor bias \(0.0022^{\circ}\)/h and accelerometer bias \(25\)\(\upmu\)g. The listed results of the work are more applicable to ground equipment. Some researchers offer interesting solutions with magnetometers for air vehicles, for example in [50] or [51]. Good accuracy results were also obtained using tightly coupled systems and robust filters. In particular, a tightly coupled system was developed in [42] using pseudoranges. Doppler shift and carrier frequency and a robust Kalman filter using measurements of the Novatel OEMV-3 receiver, INS STIM300 with a gyro sensor bias \(0.0022^{\circ}\)/h and accelerometer bias \(0.75\)\(\upmu\)g resulted in a positioning accuracy up to 4 m.  
As can be seen from the research above, the use of neural networks provides relatively good results in terms of accuracy when used in integrated GNSS/INS systems. However, the implementation of neural networks in comparison with standard approaches can significantly increase the computation time even when using high-performance digital devices. The use of tightly coupled integration systems, as well as navigation receivers that work with several navigation systems (GPS, Beidou, GLONASS), is a more reliable approach to solve the problem of temporary unavailability of GNSS measurements. Table 4 provides a comparative description of various approaches to the implementation of integrated INS/GNSS systems in the presence of outliers and violation of integrity.