A More Reliable Power-Compensated Iterative Downward extension of Geomagnetic Data via Gravity-Magnetic Filter Adaptation

To enhance the fidelity and reliability of downward-continued geomagnetic data, this paper proposes a power-compensated, enhanced Tikhonov iterative scheme that synergistically integrates a gravity-magnetic filter-based regularization operator. Comparative analysis demonstrates a marked increase in accuracy over the conventional extension operator. Comprehensive experiments on both synthetic and field datasets corroborate the method's efficacy, yielding a 28.4 % reduction in mean absolute error relative to the classical Tikhonov iteration and outperforming alternative approaches under optimized regularization parameters. Consequently, the proposed framework furnishes higher-precision and more reliable extension products, thereby substantially improving the robustness of geomagnetic navigation systems.