# Spoofing Detection Using GNSS/INS/Odometer Coupling for Vehicular Navigation
## 5 Spoofing Detection Performance
### Results of Data Set 1 (Suburban Environment)  
Figure 4 shows trajectories in a suburban residential environment. To emulate a spoofing attack, the red trajectory, driven first with only a GPS receiver, is assumed to be the spoofed one. The GPS measurements of that trajectory are then used when driving the authentic green trajectory with the tactical and MEMS IMUs and use of vehicle odometer. Both trajectories started at the same location and reached the same destination from the two paths shown. The two trajectories overlapped in some parts of the initial path and then separated and joined again at destination. The two IMUs, odometer and GPS receiver logged data simultaneously. A spoofing attack is detected when the GPS red spoofed trajectory does not match that of the RIO trajectory on the green authentic trajectory during the detection observation intervals and threshold selected as described below. The first step to assess the performance of the method is to evaluate its characteristics under a null-hypothesis (absence of spoofing attack). This means evaluating the performance of the RIO for each IMU configuration. Figure 5 shows the authentic trajectory in green as obtained by spoof-free GPS and each of the RIO trajectories over the 350 s duration of the test. The GPS-free RIO trajectories were initialized with correct position and heading information. The RIO solutions generally follow the authentic trajectory pattern, however, the errors in the trajectory estimation differ for the two IMUs as expected. Figure 6 shows their growing horizontal errors as a function of time and obtained through a comparison with the spoof-free GPS trajectory. As expected, the RIO solution using the tactical grade IMU results in better performance and maintains a horizontal accuracy better than 50 m. The performance of the cell phone MEMS IMU-based RIO is comparable to that of the tactical one only for the initial 150 s of data. The spoofing detection threshold of 10 m selected is arbitrary and can be adjusted as required by the application. The update interval should be tuned to avoid false spoofing detection caused by the IMU sensor errors observed under the nominal operation conditions shown in Figure 5. The error pattern is a function of the IMU drift rate. Assuming correct initial RIO heading and position values, Figure 5 shows that both solutions meet the stated performance (horizontal errors below 10 m) during the first 30 s. Hence, one may compare the two solutions and correct the RIO errors every 30 s during the detection process. Figure 7 shows the MEMS IMU-based RIO errors for different update intervals (\(t_{u}\)). The errors are the differences between authentic GPS and RIO solutions. Figure 4: Data collection scenario in suburban environment. Green and red lines are the authentic and spoofed trajectories. Figure 5: Standalone RIO mechanization for the two different IMUs used (350 s of data). Figure 6: RIO mechanization errors for the two different IMUs shown in Figure 4.  
Figure 7: RIO (Cell phone IMU and vehicle odometer) horizontal errors for various update intervals (\(t_{u}\)). As expected, increasing the update interval increases the errors due to IMU drift. For \(t_{u}\) = 20 s, the error values exceed 10 m at a few epochs. However, a longer observation period results in better detection performance as will be shown later. The above process is now implemented using the spoofed GPS red trajectory of Figure 4 by driving the green trajectory with the RIOs to assess spoofing detection effectiveness. Figure 8 shows the spoofed GPS trajectory, the spoofed GPS/RIO conventional integration trajectory in which case the RIO solutions are continuously corrected, and RIO solutions with correction intervals of \(t_{u}\) = 20 s using the cellphone MEMS IMU and vehicle odometer. The actual authentic trajectory is also shown. The GPS/RIO trajectory remains spoofed and its trajectory matches the spoofed GPS one.