Performance Analysis of GNSS/INS Loosely Coupled Integration Systems under Spoofing Attacks

Area of Science:

• Navigation Systems Engineering
• Signal Processing
• Cybersecurity

Background:

• Loosely coupled Global Navigation Satellite System (GNSS) and Inertial Navigation System (INS) integration enhances navigation accuracy and robustness.
• These integrated systems are susceptible to spoofing attacks, where false signals compromise navigation accuracy.
• Existing integration algorithms lack effective spoofing detection, potentially leading to incorrect INS compensations.

Purpose of the Study:

• To analyze the performance of GNSS/INS loosely coupled systems under meaconing (MEAC) and lift-of-aligned (LOA) spoofing attacks.
• To investigate the impact of spoofing on Inertial Measurement Unit (IMU) error compensations.
• To evaluate a novel detection method based on IMU error compensations for identifying spoofing attacks.

Main Methods:

• Theoretical analysis of GNSS/INS loosely coupled integration under spoofing scenarios.
• Performance testing of position fusion and position/velocity fusion methods.
• Simulation and analysis of IMU error compensation variations during MEAC and LOA attacks.
• Implementation and testing of an IMU error compensation-based spoofing detection method.

Main Results:

• Spoofing attacks significantly increase IMU error compensations in GNSS/INS systems.
• MEAC attacks cause noticeable IMU error compensation increases in both position and position/velocity fusion systems.
• LOA attacks lead to unreasonable IMU error compensation increments specifically in position/velocity fusion systems.
• The proposed IMU error compensation-based detection method effectively identifies both MEAC and LOA attacks in position/velocity fusion systems.

Conclusions:

• IMU error compensations serve as a reliable indicator of spoofing in GNSS/INS loosely coupled systems.
• The position/velocity fusion approach, combined with IMU error monitoring, offers a robust defense against common spoofing tactics.
• The developed detection method demonstrates high probability in identifying MEAC and LOA spoofing attacks, enhancing navigation system security.