Extrinsic spatiotemporal calibration is the prerequisite and foundation for the fusion of ground-penetrating radar (GPR) and camera data. However, existing calibration methods suffer from difficult target observation, large error accumulation, and time synchronization issues. To address these problems, this paper proposes a method for the spatiotemporal calibration of ground-penetrating radar-camera external parameters based on mirror reflection targets and distance constraints. This method effectively integrates common targets, mirror coordination, and distance constraint functions, enabling spatiotemporal calibration of GPR-camera external parameters without requiring prior information about the scene. Specifically, firstly, a set of GPR-camera external parameter spatiotemporal calibration device is designed, which indirectly achieves simultaneous observation of the common target sphere by the GPR and camera through the introduction of mirror reflection transformation. Secondly, a global joint optimization method combining Huber kernel function constraints and weighted least squares method is proposed to effectively suppress error accumulation during the calibration process. Finally, a distance constraint function is utilized to synchronize two types of data streams: Camera image information with uniform temporal distribution and GPR/wheel encoder distance information with uniform spatial distribution, achieving precise alignment of timestamps between the GPR and the camera. The experimental results show that, compared with the traditional step-by-step calibration method, the Euclidean error mean value of the method proposed in this paper is reduced by 67.73%, demonstrating better performance in extrinsic spatial calibration. Compared with the GPR-wheel encoder and wheel encoder-camera methods, the proposed method reduces the mean value of cumulative distance drift error by 92.81% and 97.64% respectively, effectively suppressing trajectory drift caused by temporal misalignment. The proposed method successfully achieves spatial calibration and time synchronization of GPR and camera external parameters, while improving the overall accuracy and stability of data fusion between the two heterogeneous sensors.