Geomagnetic matching localization is an important research direction in navigation and positioning, with broad application prospects in indoor and other satellite-denied environments. However, extending from one-dimensional (1D) to two-dimensional (2D) scenarios incurs a sharp increase in the search space and computational burden. Moreover, the presence of similar features in 2D geomagnetic maps can lead to mismatches, thereby degrading positioning accuracy. To address these issues, this paper proposes a multi-feature-parameter-constrained 2D geomagnetic matching localization method. The approach adopts a geomagnetic sequence matching strategy that reduces the number of candidate fingerprint sequences to improve matching efficiency, and integrates vehicle motion constraints, periodic variation characteristics of the geomagnetic field, and the Dynamic Time Warping (DTW) algorithm to construct a path-matching–based localization mechanism. An magnetically non-magnetic test vehicle equipped with magnetometers is developed for experimental validation. Results show that the proposed method reduces the single-point localization time to 1.75 ms, and achieves an average positioning accuracy of 1.37 m in typical environments.