Anti-spoofing algorithm based on adaptive Kalman filter for high dynamic positioning

The global positioning system (GPS) is widely used for military and civil applications due to its strong abilities of precise three-dimensional positioning and measurements of velocity and time. However, the GPS receiver is easy to be jammed by spoofing since the power of the receiver signal is very weak. Generally, the spoofing signal can be detected by the GPS information using Kalman filter. Unfortunately, this method appears to have little effect in the case of high dynamic positioning. In this paper, we propose an anti-spoofing algorithm based on adaptive Kalman filter for high dynamic positioning. According to the orthogonality of innovation in the Kalman filtering, the proposed method firstly uses the threshold determination to detect whether the spoofing jamming existed in the process of positioning solution of GPS. If there exists spoofing jamming, the gain coefficient will be modified by using the M-estimation in statistics, and the error variance will be reduced to ensure that the filter estimate is as close as possible to the true state of the system, meanwhile guaranteeing the filtering accuracy of the results. At the same time, the introduction of the fading factor reduces the proportion of the previous state information and reuses current measurement information, which ensures liable convergence filter and improves stability and further achieves the target of anti-spoofing in the process of high dynamic positioning. The simulation results show that in high dynamic environment, if spoofing jamming exists, the proposed method can guarantee the accuracy and stability of the positioning results at the same time.