Navigation in GNSS-Denied Environments Using MEMS-Grade Sensors and Geophysical Anomalies: A UKF Approach

James Brodovsky, Philip Dames

Peer Reviewed

Abstract:	This work explores the integration of open-source gravity and magnetic anomaly data into a strapdown Inertial Navigation System (INS) to improve navigation performance during degraded or intermittent Global Navigation Satellite System (GNSS) availability. The primary objective is to demonstrate that a geophysical-aided INS, utilizing only low-cost micro electromechanical system (MEMS) grade sensors and publicly available geophysical maps, could achieve lower drift rates than a standard INS without geophysical aiding. A comprehensive, long-term trajectory dataset (MEMS-Nav) was collected using a smartphone’s internal MEMS-grade inertial measurement unit (IMU) and GNSS receiver. The GNSS data was systematically degraded using the a toolbox developed by the authors to simulate GNSS interference scenarios. An INS was developed that incorporated gravity and magnetic anomaly measurements as additional aiding sources, utilizing the Institute of Geophysics and Planetary Physics (IGPP) Earth free-air anomaly map and World Digital Magnetic Anomaly Map as reference. The geophysical-aided INS demonstrated improved navigation accuracy compared to the standard INS when operating under GNSS interference, with performance gains ranging from several meters to tens of meters on certain trajectories. Even when unable to exceed standard INS performance, the geophysical approach exhibited trends toward superior accuracy. Results showed that despite inherent MEMS-grade IMU noise and limited resolution of open-source geophysical maps, this approach demonstrates feasibility of constraining INS drift.
Published in:	Proceedings of the 2026 International Technical Meeting of The Institute of Navigation January 26 - 29, 2026 Hyatt Regency Orange County Anaheim, California
Pages:	155 - 164
Cite this article:	Brodovsky, James, Dames, Philip, "Navigation in GNSS-Denied Environments Using MEMS-Grade Sensors and Geophysical Anomalies: A UKF Approach," Proceedings of the 2026 International Technical Meeting of The Institute of Navigation, Anaheim, California, January 2026, pp. 155-164. https://doi.org/10.33012/2026.20508
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