Accounting for Magnetic Anomaly Map Artifacts in Magnetic Navigators

Abstract

Magnetic anomaly navigation relies on high-quality magnetic anomaly maps in order to achieve accurate position information. High-quality has traditionally been defined from a geophysics perspective rather than from a navigation standpoint and this has driven the requirements for most Earth magnetic anomaly data collection. Because of the great expense required to collect magnetic anomaly data it is desirable to use existing magnetic anomaly maps for navigation. The research outlined here begins developing a framework for understanding these magnetic anomaly map errors and artifacts in terms of navigation filter performance using real-world flight data. Existing maps, such as the North American Magnetic Anomaly Database (NAMAD), are often under-sampled, aliasing high spatial-frequency components into the navigation band. In addition, much existing data collection occurred prior to the GNSS-era resulting in systematic georegistration errors within and between data sets. Map products often merge data from several collections over many years. Merging these data sets requires a good understanding of the space weather at each collection’s point in time as well as a leveling algorithm that accounts for the space weather as well at sensor positioning errors. Existing magnetic anomaly map products do not quantify these errors, and current ongoing research in investigating how to properly quantify these errors. In this work we quantify magnetic navigator performance using magnetic anomaly maps of varying quality and real collected magnetic data in several realistic navigation scenarios, and we propose map-based metrics to use to estimating magnetic navigator performance. In addition, we propose a method to estimate a map-derived first order Gauss-Markov (FOGM) process into the navigator.