Maxwell-Consistent 3-D Magnetic Field Camera using Scalar-Potential-Based Reconstruction
Various applications require accurate 3-D characterization of magnetic fields with high spatial and temporal resolution. Building on our previously introduced spherical magnetic field camera employing 86 three-axis Hall sensors arranged on a spherical surface, we present a novel magnetic-field reconstruction approach based on the magnetic scalar potential and its spherical harmonic expansion. Unlike the previous reconstruction method that expands each vector component separately, our scalar-potential-based formulation is inherently consistent with Maxwell's equations for source-free fields by design, yielding curl-free and divergence-free field models. Using a simulated magnetic gradient field generated by two permanent magnets, we demonstrate that the proposed method achieves higher reconstruction accuracy, improved robustness to sensor noise and failure, and substantially reduced non-physical divergence and curl compared to the component-wise baseline. Furthermore, the scalar-potential approach attains superior performance with fewer coefficients, indicating a more efficient use of measurement data allowing higher-degree polynomial representations.