Enhancement and Defense of GPS Navigation Using Signal Processing Techniques
Type of DegreeMaster's Thesis
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In this thesis methods of spoofing prevention are developed to detect, identify, and mitigate an attack against both networked and standalone GPS receivers. A network based detection algorithm is introduced which combines existing network data and GPS receiver outputs to create a dynamic threshold used as an indication of a spoofing attack. Attack mitigation is accomplished in the development of an interference cancellation algorithm. In the event of an attack, correlators are designated to track the attacking signal and extract critical parameters describing its power, phase, and frequency. These parameters are used to create a replica of the incoming signal which is then subtracted from the buffered raw data. This process removes the interfering signal allowing recovery of the authentic signal and computation of true receiver position. The anti-spoofing routines evaluated in this thesis have an advantage over other methods due to their robustness in a wide variety of situations and their ability to mitigate an attack without any prior knowledge of the spoofer or the spoofed signal characteristics. Testing of the algorithms developed in this thesis is accomplished using various types of simulated GPS data since live-sky testing in the GPS frequency band is restricted by the Federal Communications Commission. Actual GPS measurements are collected and modified to simulate spoofing in tests of the detection algorithms. Sets of simulated GPS data files are combined in software to simulate spoofing at the signal level. These data sets are used to test the interference cancellation algorithm's effectiveness at removing a spoofed signal in the intermediate frequency (IF) stage. The detection and suppression algorithms are demonstrated to effectively alert the user to an attack and mitigate its effect in IF stage generating a cleaned data set for acquisition and tracking of the authentic GPS signal.