Real-time continuous positioning represents a pivotal technology for the advancement of autonomous systems. Conventional positioning technologies, such as RTK and LiDAR SLAM, are subject to limitations in various operational contexts. These include signal blockage in urban environments, a lack of positioning feature points in open areas, and the necessity for frequent updates to base maps. These issues are inadequate to address the challenges posed by adverse weather conditions. Virtual Track Autonomous Driving Technology addresses these shortcomings by detecting ground magnetic signals and electronic tags, enhancing the accuracy and robustness of the positioning system, and avoiding the risks of positioning errors in rainy weather, backlighting, or obstructed environments. This further expands the operational areas for autonomous vehicles.