Absolute Positioning Using the Earth's Magnetic Anomaly Field

Canciani, Aaron

doi:10.1002/navi.138

Cited by 68 publications

(52 citation statements)

References 18 publications

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“…The second was a looping flight pattern. These flights originally demonstrated map‐based aerial magnetic navigation achieving 13‐m distance root mean squared (DRMS) error over a 1‐hour flight. The second flight's many loops and path crossings made it a viable dataset to apply SLAM techniques.…”

Section: Flight Testmentioning

confidence: 99%

MagSLAM: Aerial simultaneous localization and mapping using Earth's magnetic anomaly field

Lee

Canciani

2020

NAVIGATION

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Instances of spoofing and jamming of global navigation satellite systems (GNSSs) have emphasized the need for alternative navigation methods. Aerial navigation by magnetic map matching has been demonstrated as a viable GNSS‐alternative navigation technique. Flight test demonstrations have achieved accuracies of tens of meters over hour‐long flights, but these flights required accurate magnetic maps which are not always available. Magnetic map availability and resolution vary widely around the globe. Removing the dependency on prior survey maps extends the benefits of aerial magnetic navigation methods to small unmanned aerial systems (sUAS) at lower altitudes where magnetic maps are especially undersampled or unavailable. In this paper, a simultaneous localization and mapping (SLAM) algorithm known as FastSLAM was modified to use scalar magnetic measurements to constrain a drifting inertial navigation system (INS). The algorithm was then demonstrated on real magnetic navigation flight test data. Similar in performance to the map‐based approach, MagSLAM achieved tens of meters accuracy in a 100‐minute flight without the use of a prior magnetic map. Aerial SLAM using Earth's magnetic anomaly field provides a GNSS‐alternative navigation method that is globally persistent, impervious to jamming or spoofing, stealthy, and locally accurate to tens of meters without the need for a magnetic map.

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Section: Flight Testmentioning

confidence: 99%

MagSLAM: Aerial simultaneous localization and mapping using Earth's magnetic anomaly field

Lee

Canciani

2020

NAVIGATION

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“…14, for each particle, there are N different predicted observations corresponding to the N UAVs' predicted positions. In this study, the magnetic anomaly measurement noise is assumed as a Gaussian white noise [26], and the likelihood function can be calculated as a Gaussian distribution. Meanwhile, the magnetic anomaly measurements from different UAVs are assumed to be conditionally independent.…”

Section: Cooperative Magnetic Localizationmentioning

confidence: 99%

“…The Earth's magnetic anomaly information offers another alternative data source for estimating vehicles' global positions [25,26]. The Earth's magnetic anomalies present the high spatial frequency content of the Earth magnetic field.…”

mentioning

confidence: 99%

Cooperative UAV Navigation using Inter-Vehicle Ranging and Magnetic Anomaly Measurements

Yang

Strader

et al. 2018

2018 AIAA Guidance, Navigation, and Control Conference

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The problem of cooperative localization for a small group of unmanned aerial vehicles (UAVs) in a Global Navigation Satellite System-denied environment is addressed in this paper. The presented approach containstwo sequential steps: first, an algorithm called cooperative ranging localization, formulated as an extended Kalman filter, estimates each UAV's relative pose inside the group using intervehicle ranging measurements; second, an algorithm named cooperative magnetic localization, formulated as a particle filter, estimates each UAV's global pose through matching the group's magnetic anomaly measurements to a given magnetic anomaly map. In this study, each UAV is assumed to only perform a ranging measurement and data exchange with one other UAV at any point in time. A simulator is developed to evaluate the algorithms with magnetic anomaly maps acquired from airborne geophysical survey. The simulation results show that the average estimated position error of a group of 16 UAVs is approximately 20 m after flying about 180 km in 1 h. Sensitivity analysis shows that the algorithms can tolerate large variations of velocity, yaw rate, and magnetic anomaly measurement noises. Additionally, the UAV group shows improved position estimation robustness with both high-and low-resolution maps as more UAVs are added into the group.

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“…The concept behind magnetic field navigation is that if there is a map of the magnetic field variations in a particular area, then we can compare magnetic field measurements against a map to determine position information. This concept has been successfully demonstrated for indoor navigation [13], for navigation of vehicles driving on roads [14], and for aircraft [15,16].…”

Section: Pnt Sensors and Techniquesmentioning

confidence: 99%

Multisensor Navigation Systems: A Remedy for GNSS Vulnerabilities?

et al. 2016

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Abstract-Space-based positioning, navigation and timing (PNT) technologies, such as the Global Navigation Satellite Systems (GNSS) provide position, velocity, and timing information to an unlimited number of users around the world. In recent years PNT information has become increasingly critical to the security, safety and prosperity of the World's population, and is now widely recognized as an essential element of the global information infrastructure.Due to its vulnerabilities and line-of-sight requirements GNSS alone is unable to provide PNT with the required levels of integrity, accuracy, continuity and reliability. A multi-sensor navigation approach offers an effective augmentation in GNSSchallenged environments that holds a promise of delivering robust and resilient PNT. Traditionally, sensors such as inertial measurement units (IMUs), barometers, magnetometers, odometers and digital compasses, have been used. However, recent trends have largely focused on image-based, terrain-based and collaborative navigation to recover the user location. This paper offers a review of the technological advances that have taken place in PNT over the last two decades, and discusses various hybridizations of multi-sensory systems, building upon the fundamental GNSS/IMU integration. The most important conclusion of this study is that in order to meet the challenging goals of delivering continuous, accurate and robust PNT to the ever-growing numbers of users, the hybridization of a suite of different PNT solutions is required.

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Absolute Positioning Using the Earth's Magnetic Anomaly Field

Cited by 68 publications

References 18 publications

MagSLAM: Aerial simultaneous localization and mapping using Earth's magnetic anomaly field

MagSLAM: Aerial simultaneous localization and mapping using Earth's magnetic anomaly field

Cooperative UAV Navigation using Inter-Vehicle Ranging and Magnetic Anomaly Measurements

Multisensor Navigation Systems: A Remedy for GNSS Vulnerabilities?

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