Anomaly Detection in Ground Moving Target Trajectories via Chan-Taylor Collaborative Localization

To address the limitations in positioning accuracy and environmental adaptability of vibration-aware target monitoring systems, an enhanced TDOA acoustic source localization method based on Chan-Taylor collaborative algorithm is proposed in this study. A two-phase collaborative localization model is constructed by integrating the high-precision characteristics of Chan's algorithm with the strong robustness of Taylor series expansion method. A virtual-real mapped simulation monitoring platform is established through digital twin technology, achieving dynamic interactive verification between physical and virtual spaces. Experimental results demonstrate that the improved algorithm attains 92.7% positioning accuracy in target trajectory reconstruction. Under virtual-real fusion testing conditions, the system achieves continuous target tracking within an 80-100 meter radius monitoring range in complex terrains.