Spoofing profile estimation-based GNSS spoofing identification method for tightly coupled MEMS INS/GNSS integrated navigation system

Abstract

The integration of global navigation satellite system (GNSS) and micro-electro-mechanical system (MEMS) inertial navigation system (INS) is widely used and it is under the increasing threat of GNSS spoofing. The innovation and the residual from the Kalman filter in MEMS INS/GNSS integrated system are rapidly distorted under spoofing attack, making it difficult for spoofing identification and exclusion. In the study, the authors propose a novel spoofing identification method based on the tightly coupled MEMS INS/GNSS integrated navigation system. There are two main contributions of this study. The first is the spoofing identification method based on estimating the spoofing profile through the innovation and the propagation process of the Kalman filter. The second is the iterative implementation of the spoofing profile estimator reducing the computational overhead. The performance of the proposed method is compared against existing anti-spoofing methods using real driving data and the effectiveness of the method is verified through a field experiment.