# Detecting and Mitigating Attacks on GPS Devices
## 6 Countermeasures and Their Comparison
### Countermeasures for GPS-Denied Environment--Alternate Positioning
#### 6.3.2 Landmark-Based Approaches  
Many techniques for positioning and navigation in the literature are based on the idea of detecting known objects within the environment, such as landmarks. These approaches utilize the known position of landmark objects so that the UAS knows its location when that object is encountered. The logic behind this concept can be best explained with this illustration: I know where that thing is located. I see that thing. By extension, I know where I am. We have already seen variations of these approaches in the IMU approach discussions. Other sensorsare used to locate recognizable objects in the multi-sensor fusion IMU approach, establishing a ground-truth position estimate that can be used to reset IMU accuracy. The landmark concept is identical, except an IMU is not necessarily present. Instead, position and navigation may be achieved solely through landmark recognition. Landmark recognition may also be used intermittently in conjunction with other sensors, such as an IMU. Landmark-based positioning requires the UAS to maintain knowledge of known object locations so that when that object is encountered, it can be mapped to a location. The \"object\" can be any phenomenon that can be observed via a UAS sensor. The existing ones commonly fall into one of two categories: (1) RF landmarks and (2) visual landmarks. RF landmark-based approaches use existing communications infrastructure for position calculation, which could take the form of signal emitters pre-placed along the UAS flight path. This approach requires a priori knowledge of the flight path and the installation of ground-based infrastructure. These types of approaches have been effective in the case of visual landmarks [127] and also perform well in the case of RF landmarks [128]. This pre-placement approach may prove valuable in applications where a UAS always performs a fixed flight path; however, it may not be practical for generalized UAS operations. A more flexible approach is utilizing existing commercial communications infrastructure for position calculation. In this case, existing commercial signals are viewed as Signals of Opportunity (SOPs) that are received by the UAS platform. The locations of many types of commercial RF emitters are publicly known; therefore, it would be possible to build an onboard emitter location database that could be used to detect SOPs and estimate the receiver's position. There are many papers in the literature where commercial SOPs are used for navigation purposes, including IEEE 802.11-based Wi-Fi [129], Bluetooth [130], AM Radio [131], FM Radio [132; 133], Digital Television (DTV) [134], and cellular communications [135]. The authors of [136] implemented an SDR-based system onboard a small quadcopter UAS using FM radio, DTV, cellular, and Wi-Fi SOPs for positioning, demonstrating good position accuracy performance. It is unclear how SOPs such as Wi-Fi and Bluetooth could be incorporated into a generalized positioning system since Wi-Fi and Bluetooth locations are not always publicly known; however, many of the other SOPs, including AM radio, FM radio, DTV, and cellular infrastructure, lend themselves to a generalized approach since their emitter locations are well known and publicly available. Many technical attributes of these emitters, such as transmit power and antenna type, are also publicly available. One limitation of this approach is that it will not necessarily be applicable across all geographic locations. Many papers in the literature focus on urban and suburban regions; however, there will be a less dense communications infrastructure for many of these signal types, such as DTV, in rural and less populated regions. A promising approach for positioning is using signals from the commercial cellular communications infrastructure as SOPs. Previous studies have revealed that good accuracy can be obtained; however, accuracy depends on the environment, and position accuracy is sensitive to interference [135].