# Impacts of GPS Spoofing on Path Planning of Unmanned Surface Ships
## 1 Introduction  
Unmanned Surface Vehicles (USVs) are ships that operate on the water surface without a crew [1, 2]. USVs have great advantages, including efficiency, cost-effectiveness, environmental friendliness, work safety, and family friendliness [3]. USVs navigate in complex water areas, including islands, shoals, reefs, and other obstacles [4]. Path planning for USVs is an important guarantee for safe navigation of USVs [5]. There are some path planning algorithms for USVs, including Artificial Potential Field (APF), A\({}^{\star}\) algorithm, Ant Colony Algorithm (ACA), etc. [6, 7]. The APF method is a classical path planning algorithm, which can plan a smooth and safe path for vehicle travel on the sea where both static and dynamic obstacles exist. We believe that this paper's studies can also be applied to other methods in the field. Its core idea is to assume that an unmanned ship moves and is controlled by a resultant force under two virtual forces: a target point has \"gravity\" on the unmanned ship, and some obstacles have \"repulsive force\" on the unmanned ship [8, 9]. Since this method has the problem of local optimum, many researchers have improved it [10, 11, 12, 13, 14]. The traditional APF method usually needs to calculate the resultant force of gravitational and repulsive forces on the ship according to the speed of its own ship, real-time position, and goal position. The improved APF method calculates the steering angle and heading based on its own ship's position, target ship's position, ship's speed, target ships' speed, ship's heading, and target ships' heading to avoid collision with dynamic ships. These data are obtained by Automatic Identification System (AIS), Global Positioning System (GPS), speed log, compass, and radar. After data fusion and calculation, paths are finally planned for unmanned ships. The papers [15, 16] have introduced these data collection and path planning algorithms in detail. The path planning results of unmanned ships based on the APF method are affected by GPS position data [17]. Unfortunately, the structure of civil GPS signals is public, which brings hidden trouble to the application of the APF method in path planning for unmanned ships. If the signals' strength is weak, the attackers do not need to produce strong false signals to cover the authentic signals [18]. At present, the frequencies of GPS signals can be generated by existing commercial equipment. If the GPS receiver receives these fictitious GPS signals instead of the real GPS signals, it will harm the path planning and collision avoidance algorithm of unmanned ships, resulting in yaw, grounding, and even collision. Once hackers or attackers attack the GPS and AIS data received by unmanned ships, the use of inaccurate or even wrong data in the APF path planning algorithm will lead to ship collision, grounding, or deviation from the course, causing severe economic losses and significant security risks to other sailing ships. In a GPS spoofing attack system, an attacker induces a GPS receiver to lock and capture false GPS signals so that the GPS receiver calculates a wrong position. There are two main approaches to GPS spoofing attacks. The first one is that attackers interfere with GPS receivers to track authentic signals by transmitting jamming signals so that GPS receivers can track and capture false GPS signals. If the power of the spoofing signals is 4 dB stronger than the authentic signals, the normal tracking of the authentic signals can be interrupted within 50 min [19]. Meanwhile, GPS receivers are induced to recapture and track the spoofing signals. The second approach is that the signals generated by GPS spoofers are initially almost wholly aligned with the authentic signals and are kept below the noise with low power. Then the attackers gradually make the power of the spoofing signals slightly stronger than the power of the authentic signals, and finally, they make the GPS receivers track the false GPS signals. There are many papers in the literature studying the APF methods.