A smoothing localization method for Global Navigation Satellite System (GNSS) and visual Simultaneous Localization and Mapping (SLAM) system is proposed to identify GNSS spoofing, optimize the cumulative error of the GNSS/visual SLAM system, and obtain smoothing localization results. The proposed method analyzes the joint error distribution of the GNSS/visual SLAM system, uses the visual frame to invert the relative error offset of the GNSS from the dimensions of time and localization, performs error analysis and mutual verification based on the verification threshold. According to the mutual verification results, the GNSS spoofing is identified, and the corresponding back-end optimization strategy is selected to obtain a smoothing localization result. Through simulation, the time verification threshold and localization verification threshold of the proposed method are obtained under the condition that the sensors frequency and accuracy are set. The KITTI datasets in rural and urban scenes are used for verification. The simulation results show that our method can identify GNSS spoofing and provide credible and smoothing localization results in the case of GNSS spoofing occurs.

In order to effectively reduce the impact of Global Navigation Satellite System (GNSS) attacks while providing mobile terminals with credible navigation and positioning results, this paper proposes a credible navigation algorithm for GNSS attack detection using an auxiliary sensor system. Based on a credible Kalman filter and measurement information provided by the auxiliary sensor system on mobile terminals, the proposed algorithm can verify the credibility of the GNSS positioning result and determine whether it has suffered from a GNSS attack using the credible verification window and the credible verification threshold. According to the verification results, the algorithm can adaptively select an updated model for measurement correction and achieve a credible navigation result. The algorithm proposed in this paper has been verified on a self-developed mobile terminal, and the experimental results show that the algorithm can provide credible navigation and positioning services for mobile terminals in the context of GNSS attacks.