Tradeoff of Code Estimation Error Rate and Terminal Gain in SCER Attack

The current research on the global navigation satellite system (GNSS) has shifted to focus on providing secure and reliable services, rather than high-precision positioning services. Deception jamming has emerged as a major threat to GNSS security applications due to its advantages, such as concealment. For security signals not publicly available in the spread spectrum code sequence, simple deception methods do not suffice to implement effective deception. In response, the security code estimation and replay (SCER) attack was proposed. However, the impact of the spread spectrum code estimation error on the receiver and SCER attack effect is still unclear. This article is based on the SCER attack and deception signal receiving model, constructs a receiver tracking loop analysis model and carrier-to-noise ratio (CNR) estimation model based on spread spectrum code error, and analyzes the impact of spread spectrum code error on the receiver tracking loop and CNR. Based on the experimental results and discussion, some conclusions have been drawn. First, spread spectrum code error will cause correlation peak distortion and a decrease in CNR. Second, to achieve effective deception, the spread spectrum code error cannot be increased indefinitely and an upper bound exists, which ranges from about 41%, depending on the deceived receiver acquisition strategy. Third, when the spread spectrum code error rate is less than the upper bound, the mean square error of the code phase measurement is less than 0.02 chip, which is on the same order of magnitude as caused by thermal noise. As such, it can be approximately assumed that the code tracking deviation caused by spread spectrum code error has minimal impact on the SCER attack. Although reducing the receiving terminal gain of the SCER attack will lead to an increase in the spread spectrum code estimation error, it is possible to increase the transmitting terminal gain of the SCER attack to maintain the same CNR of the deception signal and deception effect, greatly reducing the cost of the deception.