Airborne vector magnetics mapping of remanently magnetised banded iron-formations at Rocklea, Western Australia

Dransfield, Mark; Christensen, Asbjørn Nørlund

doi:10.1071/aseg2003ab041

Cited by 2 publications

(2 citation statements)

References 5 publications

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“…For current purposes, the target is assumed stationary and at a fixed depth, thereby rendering the magnetic signature static. Assuming that the magnetic signature of the target simply adds to the total magnetic intensity of the local region in a linear fashion, 9 anomalies can easily be identified by simply subtracting the magnetometer reading from the local reference map which is stored on the ground station. Magnetic signature of target.…”

Section: B Total Magnetic Intensity Mapsmentioning

confidence: 99%

Feature Extraction of Low Dimensional Sensor Returns for Autonomous Target Identification

Lum

Rysdyk

2008

AIAA Guidance, Navigation and Control Conference and Exhibit

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This work considers algorithms for maritime search and surveillance missions. During these type of missions, an agent searches for a target using its various sensors. Performing target identification and classification of sensor returns is a crucial component of the mission. This paper investigates a system to process returns from a low dimensional sensor and automatically classify the data. This system uses an algorithm that employs the sensor and motion model of the agent to augment the limited data from the sensor. Several differentiating features are then extracted and used to train various classifiers and machine learning algorithms.

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Section: B Total Magnetic Intensity Mapsmentioning

confidence: 99%

Feature Extraction of Low Dimensional Sensor Returns for Autonomous Target Identification

Lum

Rysdyk

2008

AIAA Guidance, Navigation and Control Conference and Exhibit

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“…An ideal absolute three-axis vector magnetometer, on the other hand, also allows the calculation of the TMI while offering diverse additional benefits: It provides full vector information, required for the compensation of magn etic sources associated with the aircraft [9] as well as the detection of remanent magnetization [10]. In contrast to the TMI, the magnetic vector components are furthermore true potential fields, allowing for post processing operations like field continuation [11,12] or inversion [13].…”

Section: Introductionmentioning

confidence: 99%

Absolute calibration of a three-axis SQUID-cascade vector magnetometer

Schönau

Zakosarenko²,

Schmelz

et al. 2016

Meas. Sci. Technol.

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We report on the absolute calibration of a three-axis SQUID-cascade vector magnetometer suited for mobile operation in the Earth’s magnetic field. It is based on low temperature superconductor (LTS) dc SQUIDs with sub-micrometer sized cross-type Josephson junctions and exhibits a white noise level of about 10 fT Hz−1/2. Due to the cascaded operation principle, the huge dynamic range required to resolve a measurement range of more than 50 µT with sub-pT resolution is split onto several electronic channels of less demanding precision. As a result, the measurement accuracy is less vulnerable to parameter drifts. Furthermore, the intrinsic redundancy of the setup can be used to check for systematic errors of measurement. The offset as well as scaling and directional errors of the magnetometer have been obtained by the method of scalar calibration in our laboratory, resulting in a residuum with a standard deviation of less than 0.64 nT.

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Airborne vector magnetics mapping of remanently magnetised banded iron-formations at Rocklea, Western Australia

Cited by 2 publications

References 5 publications

Feature Extraction of Low Dimensional Sensor Returns for Autonomous Target Identification

Feature Extraction of Low Dimensional Sensor Returns for Autonomous Target Identification

Absolute calibration of a three-axis SQUID-cascade vector magnetometer

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