An Innovation-Bounded Kalman Filtering Approach Securing GNSS Timing in Industrial Networks

In this article, an innovation-bounded Kalman filter (IBKF) is proposed to address the delay problem in detecting the time synchronization attack (TSA), one serious concern for various Global Navigation Satellite Systems (GNSS) timing users in modern industrial networks. The IBKF can improve the weakness of traditional timing methods, such as the regular Kalman Filter, by bounding the influences of unauthenticated signals during a detection window range. So, when TSA begins, even if detection that requires a certain observation window is not finished, timing errors can still be limited. The IBKF algorithm and its application in securing GNSS timing are theoretically introduced, together with performance analyses. Moreover, both simulations and real-world experiments are conducted to show that the IBKF can effectively limit the timing error in actual TSA conditions and also provide similar timing accuracy and stability in normal conditions compared with traditional methods.