# Integrity Analysis for GPS-Based Navigation of UAVs in Urban Environment
## 2 Integrity Monitoring
However, they cannot detect local GNSS errors, such as multipath and obscuration, in urban environments [33]. Overall, the usage of classical integrity monitoring approaches is challenging in urban environments due to local error sources. Integrity monitoring systems in use have limited availability in urban environments and cannot provide required integrity monitoring performance. Since availability issues of integrity monitoring systems mostly depend on satellite visibility and satellite geometry issues, DOP coefficients, cut-off elevations and number of visible satellites should be investigated in order to improve integrity monitoring performance for local and urban applications. The Stanford-ESA Integrity Diagram [34] is one of the useful tools that have been proposed in order to identify and assess integrity risks and integrity failures. This diagram illustrates the integrity risks based on a comparison between position error (PE), protection level (PL) and alert limit (AL). Integrity events are defined through misleading operations, and hazardously operations with respect to the specific areas of the Stanford-ESA Diagram as it is seen in Figure 3. During normal operations, measurements are expected to appear in the white triangular zone, which represents the nominal operating conditions. Although the Stanford diagram illustrates the integrity risks, TTA should be additionally assessed in order to understand whether a limit exceeding is an integrity failure or not. A time-integrity plot is usually employed in this case; it provides the time history of position errors that can be used to separate integrity failures and sudden changes. Total receiver positioning error consists of two components: User Equivalent Range Error (UERE) and DOP. The standard deviation of the receiver positioning error \(\sigma_{P}\) is defined in [36] as follows:  
\[\sigma_{P}=DOP\times\sigma_{UERE} \tag{1}\]  
where \(\sigma_{UERE}\) denotes standard deviation of UERE, which is based on estimate of positioning inaccuracy from a single satellite and is calculated for every satellite independently. Typical UERE budget for an L1 frequency C/A code receiver is given in Table 1[36]. The UERE budget estimation is made under ideal satellite geometry condition (DOP = 1). Position error increases with an increase in DOP according to Equation (1). Considering that the impact of UERE elements on the accuracy of the receiver remains approximately the same unless the condition of the transmission line and quality of receiver significantly changes, this study is focused on the analysis of DOP variation and assessment of the most critical environmental parameters, which affect DOP in urban environments and the corresponding positioning integrity. DOP is presented by non-dimensional measurements (i.e., coefficients) representing the relative positioning of the satellite and receiver to each other in terms of their effect on the positioning solution quality. According to different sort of accuracy metrics, there are seven DOP coefficients. These are Geometric DOP (GDOP), Time DOP (TDOP), Position DOP (PDOP), Horizontal DOP (HDOP), \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Error** & **Broadcast** & **Group** & **Broadcast** & **Ionospheric** & **Tropospheric** & **Receiver** & **Multipath** \\
**Source** & **Clock** & **Delay** & **Ephemeris** & **Delay** & **Delay** & **Noise** & **Multipath** \\ \hline \(\sigma\)**error** & & & & & & & & \\
**(m)** & 1.1 & 0.3 & 0.8 & 7.0 & 0.2 & 0.1 & 0.2 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Global Navigation Satellite Systems (GNSS) User Equivalent Range Error (UERE) Budget for L1 C/A Receiver. Figure 3: The Stanford–ESA Diagram [35]. Vertical DOP (VDOP), East DOP (EDOP) and North DOP (NDOP). The relationship between DOP coefficients is presented in Equation (2). \[ \begin{split}\text{GDOP}=\sqrt{\text{PDOP}^{2}+\text{TDOP}^{2}} \text{,}\quad\text{PDOP}=\sqrt{\text{HDOP}^{2}+\text{VDOP}^{2}}\text{,}\\ \text{HDOP}=\sqrt{\text{EDOP}^{2}+\text{NDOP}^{2}}\end{split}