A GNSS Anti-Spoofing Method Based on Matching Matrix Deviation for IMU-Equipped Vehicles

GNSS plays a crucial role in vehicular navigation due to its accuracy and convenience. Still, GNSS spoofing poses a great threat to navigation safety, which has attracted widespread attention in recent years. Spoofing identification, which can prevent misleading information carried by spoofing signals from affecting navigation results to a certain extent, ensures the robustness of vehicular navigation in the presence of spoofing attacks. However, existing spoofing identification algorithms grapple with limitations, particularly in terms of heightened computational complexity and compromised performance when confronted with intricate spoofing strategies. To improve the identification performance in vehicular navigation, by fully exploring the motion characteristics and the consistency between GNSS and plural sensors of vehicle navigation, the paper proposes a GNSS anti-spoofing method based on the Matching Matrix Deviation (MMD) between time-differential Doppler frequency and those measured by IMU and odometers under spoofing scenarios. The proposed method works through a two-step strategy: parameter estimation followed by the construction of a constant false alarm rate detector based on residuals. Monte Carlo simulations are conducted to verify the effectiveness of the derived distribution of test statistics. Influencing factors of performance are evaluated meticulously as well. Moreover, field experiments are carried out to exhibit the proposed method’s excellent ability of spoofing identification.