Development of Gps Spoofing and Anti-Spoofing Algorithms With Data Association and Target Tracking Frameworks

Abstract

This thesis deals with the spoofing and anti-spoofing techniques in global positioning system (GPS) receivers by using data association and target tracking algorithms. Novel and efficient algorithms have been proposed in this research investigation by using estimation theory and optimization techniques. Global navigation satellite system (GNSS) is generally used for providing the po- sition, velocity, and time (PVT) for many civilian and military applications. GNSS, such as GPS, Galileo, GLONASS, BeiDou, NavIC, uses a receiver to receive the sig- nals transmitted by the satellites. These received signals are processed to provide the receiver’s position with an accuracy of a few meters. However, the recent ad- vancements in radio frequency (RF) generation result in the simulation of various RF signals with inexpensive devices and leads to threats like jamming and spoofing. The primary objective of this research work is to develop a stealthy GPS spoofer, spoofing techniques, and strategies. The available spoofers in the literature are de- tected with the simple anti-spoofing algorithms like constellation check (e.g., number of satellites available and software-defined satellite positions), monitoring the power (e.g., absolute, relative, and across satellites), checking the accuracy of clock compo- nents, reference monitor (e.g., inertial navigation system (INS), optical sensor, range sensor, bearings sensor), vestigial peak correlation, and verifying code and phase rate consistency. In this research work, we proposed a novel spoofer design, in which the spoofer relies on a target tracker and fusion module to track the motion of the target and spoof effectively. A strategy for the spatial deployment of multiple spoofers is formulated as an optimization problem to combat direction of arrival (DOA) anti- spoofing algorithms. In addition to that, the target kinematic information is used to adaptively change the transmitting powers of the spoofers and effectively combated the anti-spoofing algorithms like monitoring reception of an individual satellite’s sig- nal, and power thresholding. Further, distributed fusion of local estimates to improve the effectiveness of GPS spoofing for low-observable targets is proposed. Furthermore, multi-spoofer multi-target (MSMT) based efficient spoofing technique is developed. In distributed spoofing scenario, the spoofers work independently to each other with i out any prior information about number of spoofers and targets within the given surveillance, which results in lower hit ratio. To address this spoofer-to-target as- sociation problem, three novel centralized networking-based spoofing techniques are proposed, namely global nearest neighbor (GNN) based centralized spoofing, spoofers of opportunity-based centralized spoofing, and tunable transmitting power-based cen- tralized spoofing. The proposed algorithms provide better hit ratio in comparison to the distributed spoofing. The second objective of the research is to develop anti-spoofing algorithms for sin- gle and multiple GPS receivers. Most of the research works assume that the spoofing signals and the authentic signal attributes are different, and accordingly developed the anti-spoofing algorithms. This research proposed to consider both the authen- tic GPS and spoofed GPS pseudo measurements into the positioning algorithm and performing the robust positioning with all possible combinations. Further, to effi- ciently represent the robust positioning algorithm, the M-best positioning algorithm is proposed, which provides only M-best positions at a given epoch. Besides, this work is extended to time-varying targets with the help of Kalman filter and nearest neighbor (NN) data association approaches. The track swapping (TS) is occurring in NN framework due to the hard decision on the track-to-measurement association. This track-to-measurement association problem is resolved with the probabilistic data association (PDA) and attained lesser TS. Furthermore, this problem is extended to multiple GPS receiver problem and proposed an anti-spoofing algorithm by localizing the spoofer. In a clean environment, all the DOA are distinguishable since they are from different satellites. Whereas in spoofing scenario, all the DOAs are from the same direction and hence declared a spoofing attack. This research work proposes to install multiple GNSS receivers (on a target or in the given surveillance) to detect and mitigate the spoofing attack. While installing multiple GNSS receivers, we assume that each GNSS receiver’s relative position vector (RPV) is assumed to be known precisely. The installed GNSS receivers use the extended Kalman filter (EKF) frame- work to estimate its PVT. We proposed to calculate the equivalent-measurement and equivalent-measurement covariance of each GNSS sensor in the Cartesian coordinates in tracklet framework. These tracklets are translated to the target platform center us- ing RPV to obtain translated-tracklets. The generalized likelihood ratio test (GLRT) ii based spoofing attack detection is derived at a given epoch using these translated- tracklets. In addition to that, these translated-tracklets are processed in a batch least square (LS) framework to obtain the platform’s position. Once the attack is detect- ing at a specific epoch, it quantifies that the position information is false. Moreover, another detection test is also formulated by using DOA of signals. Once both the tests confirms the spoofing attack, the spoofer localization is performed using pseudo- updated states of GNSS receivers and acquired bearings in the iterative least-squares (ILS) framework. Mitigation of spoofing attack is achieved either by projecting the null beam in the direction of the spoofer or by launching the counter counter-measure on spoofer. The results demonstrate that the proposed algorithm performs detection of spoofing attack and ensures the continuity in navigation track. The results obtained in this research investigation demonstrates superior perfor- mance in the spoofer design. Further, the anti-spoofing approaches proposed in this thesis work are novel and provides improved performance over existing techniques. Furthermore, the contributions made in this thesis incorporated significant domain knowledge in the area of spoofing and anti-spoofing algorithms based on target target and data association.