The ground current field characterized by field strength is widely applied in fields such as geophysical exploration, seismic monitoring, and through-earth communication. However, due to the variability of regional ground current field strength, it is challenging to establish a regional fingerprint database for ground current field strength. This paper proposes a method for constructing a regional fingerprint database of ground current field strength based on RBFNN. By employing time-division cross-injection to construct a regional ground current field and using orthogonal electrodes to detect ground current field signals at different detection points, fingerprint features of the ground current field strength are extracted. RBFNN is used to fit the field strength variation function model in Kriging interpolation, and Kriging interpolation is then employed to estimate fine-grained fingerprint features of the ground current field strength. Based on the estimation results, a regional fingerprint database of ground current field strength is constructed. An experiment to construct the fingerprint database was conducted in a natural environment of 150 m×50 m. The results show that the constructed fine-grained (0.1 m×0.1 m) regional fingerprint database of ground current field strength achieves an average construction accuracy of 89.84%, with the highest accuracy reaching 95.46%.