# Integrity Analysis for GPS-Based Navigation of UAVs in Urban Environment
## 2 Integrity Monitoring  
The purpose of the integrity monitoring is to detect errors and generate timely warnings in case the integrity limits are violated. The integrity criteria defined by ICAO [24] are:  
* Horizontal/Vertical Protection Levels (HPL/VPL),
* Horizontal/Vertical Alert Limits (HAL/VAL),
* Time-to-Alert (TTA), and
* Integrity Risk. VAL/HAL and VPL/HPL represent a vertical distance and a radius of circle in the horizontal plane with center at the true user position, as illustrated in Figure 2[25]. TTA is the maximum allowable time before warnings, and accordingly, integrity risk is the probability of computing a position that is out of defined bounds without warning within the TTA. Figure 2: Integrity Alert Limits and Protection Levels. Alert limits are defined based on the requirements of missions and applications, while protection levels are calculated by users at the receiver level. Simply, protection levels are set statistically as boundaries of the position errors of the particular navigation equipment. Although there are no commonly accepted regulations for alert limits and TTA for UAV navigation, an initial approximation can be obtained from ICAO's requirements for Category I approach operations. According to these requirements, vertical guidance (APV-I) is set to 40 m and 50 m for HAL and VAL, respectively; TTA is specified as 10 s, and integrity risk should be less than 1-2 \(\times\) 10\({}^{-7}\)/h. Alert limits defined by the European GNSS Agency for safety-critical applications [26] are tighter: 5-10 m horizontally and 10-25 m vertically. The environment for urban UAV operations can be characterized based on reasonable assumptions of 30 m street width and 65 m building height, which are common in the US and Europe [27]. Therefore, in this study, 10 m and 25 m are selected as HAL and VAL limits, respectively, for positioning integrity simulations in urban environments using a generic GPS receiver. Integrity can be monitored based on analysis of different types of errors. The error sources that affect GNSS performance and their usage in integrity monitoring were discussed in [28; 29]. RAIM is the simplest way for monitoring navigation performance because it only needs pseudo-range measurements by the receiver. RAIM is not operational with less than five satellites, although the pseudo-range measurements are still available. Additionally, because standard RAIM is able to detect only one fault each time, it is not well suited for working in urban environments, where this assumption is usually not valid. Advanced RAIM (ARAIM), Relative RAIM (R-RAIM) and Extended ARAIM (ERAIM) algorithms are still under development, aiming to improve integrity monitoring and fault detection performance, and the existing issues in urban applications are not solved yet [30]. SAIM systems specifically focus on satellite-based faults. Its efficiency in detecting orbital errors is much better than both RAIM and GIC. However, its capability to detect user segment errors, which are caused by local environments, stays behind RAIM. Orbital parameter errors are hard to detect at the later stages when they are masked by other error sources, and if they cannot be detected, a persistent error in positioning and timing may occur at the receiver [31]. Hence, the trustworthiness of the ephemeris message should be checked at the user segment again. The validity check of ephemeris data can be made at the receiver by using Issue of Data Ephemeris (IODE) [32], which is broadcasted in sub-frames 2 and 3 separately. Unlike RAIM and SAIM, GIC is an externally supported method; it relies on reference data from control and monitoring stations for integrity analysis. GIC provides a direct and efficient integrity monitoring, but it is a complex and slow technique because of the infrastructural requirements. Its coverage area is also limited by the range of monitoring stations. Satellite-Based Augmentation System (SBAS) and Ground-Based Augmentation System (GBAS) can be mentioned as recent examples of the GIC approach.