Session D6: Navigation Using Environmental Features

Magnetic Anomaly Navigation Using a Multi-vehicle Batch Processing Algorithm of Variable Map Fidelity
Shawn Whitney, Aaron Nielsen, Frank van Graas, Air Force Institute of Technology
Date/Time: Friday, Sep. 20, 3:20 p.m.

In the realm of navigation technology, the susceptibility of Global Positioning Systems (GPS) to jamming and spoofing poses significant challenges to reliability and accuracy. This vulnerability underscores the necessity for alternative navigation aids that can ensure continuity and precision. A promising approach to circumvent these limitations involves leveraging high-fidelity magnetometers in conjunction with the Earth's magnetic anomaly field. The research outlined in this document explores the development and application of sophisticated multi-vehicle algorithms aimed at enhancing the accuracy and reliability of navigation by utilizing the gradient of the Earth's magnetic anomaly field. This innovative strategy presents a viable alternative to traditional GPS-based systems, offering a potential solution to the challenges posed by GPS vulnerabilities.
The Earth's magnetic field exhibits unique variations, known as magnetic anomalies, which can be exploited for navigational purposes. However, the complexity of these anomalies, combined with the non-linear trajectory of vehicles, often complicates navigation. To address these challenges, this research introduces transect and batch processing strategies designed to refine navigation solutions. These methodologies leverage the distinct characteristics of magnetic anomalies to improve vehicle navigation accuracy.
One of the initial hurdles encountered in this research involves the high initial variance observed in Extended Kalman Filters (EKF) when processing magnetic anomaly data. To expedite the convergence of these filters, a novel batch processing algorithm was developed. This algorithm operates across multiple locations simultaneously and incorporates vehicle ranging to enhance the estimation of each vehicle's location. By analyzing transect measurements of the Earth's magnetic field, the algorithm seeks to optimize navigation solutions, demonstrating a significant advancement in the field of navigational technology.
The efficacy of the proposed algorithm is assessed through the evaluation of several magnetic anomaly maps. These include fully sampled simulation data, flight data collected near Ottawa, Ontario, Canada by Sander Geophysics Ltd. (SGL) as part of the DAF-MIT Artificial Intelligence Accelerator, and flight data compiled by the Office of Naval Research (ONR) for The Caribbean Alternative Navigation Reference Experiment (CANREx). The inclusion of real-world data sets is pivotal for validating the practical applicability of the algorithm, ensuring that the proposed solutions are not only theoretically sound but also effective in real-world scenarios.
The evaluation process encompasses a series of simulations designed to test the algorithm under various conditions, including different sampling periods, levels of measurement noise, and other pertinent factors. These simulations are instrumental in gauging the performance of the algorithm in realistic settings, allowing for a comprehensive analysis of its capabilities and limitations. By simulating a range of scenarios, the research aims to ascertain the robustness of the algorithm and identify areas where further improvements can be made.
A critical component of this research involves a comparative analysis between the newly developed algorithm and the current standard of navigation using Extended Kalman Filters (EKF). This comparison is expected to highlight the superior accuracy of the proposed algorithm in determining vehicle location within the Earth's magnetic field, especially in areas where navigation poses significant challenges. Furthermore, the analysis aims to provide valuable insights into the calibration of magnetometer sensors and the assessment of errors in magnetic anomaly maps.
In conclusion, this research represents a significant step forward in the quest for reliable and accurate navigation systems that are not reliant on GPS. By harnessing the Earth's magnetic anomalies and employing advanced algorithms, it offers a promising alternative for enhancing vehicle navigation. The development and application of these algorithms not only pave the way for improved navigational accuracy but also contribute to the broader understanding of magnetic anomaly-based navigation.