Experimental Validation of GNSS Spoofing Detection by Decomposition of the Complex Cross Ambiguity Function

In this paper we present experimental results from a method for detecting spoofed GNSS signals by decomposing the Complex Cross Ambiguity Function into its components. Then, the authentic and spoofed signals are distinguished using ‘inverse’ Receiver Autonomous Integrity Monitoring (RAIM). In previous work, we successfully demonstrated the methodology using simulated data. In this paper we test it in a more realistic environment, validating its effectiveness under controlled conditions. This will involve considering factors such as real-world multipath effects and noise, allowing for a more convincing assessment of its robustness and practical applicability. This method is applicable to spoofing scenarios that may lead to Hazardous Misleading Information (HMI) and are difficult to detect using other techniques. It can identify spoofing in the presence of multipath and when the spoofing signal is power matched and offsets in code delay and Doppler frequency are relatively close to the true signal. Spoofing can be identified at an early stage within the receiver and is applicable even for dynamic users.