One‐dimensional traversal receiver autonomous integrity monitoring method based on maximum likelihood estimation for GNSS anti‐spoofing applications

Abstract

By forging global navigation satellite system (GNSS) signals similar to authentic ones, a spoofer can make receivers track forged signals (spoofing signals) and generate wrong position, velocity and time results. Receiver autonomous integrity monitoring (RAIM) can be extended to the field of spoofing detection and exclusion (SDE). However, it is well known that when there are six or more signals and only one spoofing signal among them, RAIM can effectively exclude the spoofing signal. In this study, based on maximum likelihood estimation (MLE) theory and the idea of the traverse, one-dimensional traversal MLE-RAIM (TMRAIM) is proposed, which can exclude multiple spoofing signals. Theoretically, the influence of spoofing biases will be reflected in pseudorange residuals, and then affect the probability distribution of the parity vector. Through MLE deduction, the authors can find corresponding spoofing signals which are relevant with the maximum probability of the parity vector only once under the supposed number of spoofing signals. By just traversing the number of spoofing signals, TMRAIM can run effectively on real-time GNSS receivers with low complexity. The SDE ability and time complexity are analysed in detail and two field experiments are constructed. Experimental results demonstrate the method is feasible and effective for anti-spoofing applications.