Initial Buried Minehunting Demonstration of the Laser Scalar Gradiometer Operating Onboard REMUS 600

Clem, T.R.; Bono, J.; Davis, P.S.; Overway, D.; Vaizer, L.; King, David A.; Torres, A.; Austin, Thomas; Stokey, R.; Packard, G.

doi:10.1109/oceans.2006.306828

Cited by 4 publications

(4 citation statements)

References 6 publications

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“…Magnetometers have been towed behind surface ships, incorporated in large Remote Operated vehicles (ROVs) and Autonomous Underwater Vehicles (AUVs), and are used for purposes ranging from geophysical and biological research to anthropogenic undersea target detection [ 2 , 3 , 4 , 5 , 6 , 7 , 8 ]. For example, anthropogenic targets are strongly suspected if an object is detected in sonar/visual-based methods and has a strong magnetic signal.…”

Section: Introductionmentioning

confidence: 99%

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Compact Quantum Magnetometer System on an Agile Underwater Glider

Page

Lambert

Mahmoudian

et al. 2021

Sensors

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This paper presents results from the integration of a compact quantum magnetometer system and an agile underwater glider for magnetic survey. A highly maneuverable underwater glider, ROUGHIE, was customized to carry an increased payload and reduce the vehicle’s magnetic signature. A sensor suite composed of a vector and scalar magnetometer was mounted in an external boom at the rear of the vehicle. The combined system was deployed in a constrained pool environment to detect seeded magnetic targets and create a magnetic map of the test area. Presented is a systematic magnetic disturbance reduction process, test procedure for anomaly mapping, and results from constrained operation featuring underwater motion capture system for ground truth localization. Validation in the noisy and constrained pool environment creates a trajectory towards affordable littoral magnetic anomaly mapping infrastructure. Such a marine sensor technology will be capable of extended operation in challenging areas while providing high-resolution, timely magnetic data to operators for automated detection and classification of marine objects.

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Section: Introductionmentioning

confidence: 99%

“…Industry standard magnetic survey systems of the early 21st century [ 6 , 24 ] have dimensions on the order of a meter, and even the smallest systems weigh nearly 2 kg per sensor. Such instruments are limited in range by the vehicle which provides locomotion.…”

Section: Introductionmentioning

confidence: 99%

Compact Quantum Magnetometer System on an Agile Underwater Glider

Page

Lambert

Mahmoudian

et al. 2021

Sensors

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show abstract

“…Marine magnetometers have seen widespread use for geophysical studies, archeology, unexploded ordinance (UXO) and mine detection, and navigation. Although they are often deployed as ship‐towed instruments, some deployments have been have been conducted with a variety of AUVs, such as the REMUS 600 (Clem et al, 2005, 2006), Bluefin 12 (Kumar et al, 2005; Sulzberger et al, 2009), Iver2 (Graham Chandler, 2013), Gavia (Anon, 2018; Steigerwalt, 2015; Steigerwalt et al, 2012), Sentry (Dana & Kinsey, 2010), and the Autonomous Benthic Explorer (Shah et al, 2003; Tivey, Johnson, Bradley, & Yoerger, 1998). In several AUV deployments, the magnetometer package was towed to physically separate the sensor from the AUV (Anon, 2018; Graham Chandler, 2013; Teixeira, Quintas, & Pascoal, 2016).…”

Section: Introductionmentioning

confidence: 99%

Magnetic survey and autonomous target reacquisition with a scalar magnetometer on a small AUV

Gallimore

Terrill

Pietruszka

et al. 2020

Journal of Field Robotics

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A scalar magnetometer payload has been developed and integrated into a two‐man portable autonomous underwater vehicle (AUV) for geophysical and archeological surveys. The compact system collects data from a Geometrics microfabricated atomic magnetometer, a total‐field atomic magnetometer. Data from the sensor is both stored for post‐processing and made available to an onboard autonomy engine for real‐time sense and react behaviors. This system has been characterized both in controlled laboratory conditions and at sea to determine its performance limits. Methodologies for processing the magnetometer data to correct for interference and error introduced by the AUV platform were developed to improve sensing performance. When conducting seabed surveys, detection and characterization of targets of interest are performed in real‐time aboard the AUV. This system is used to drive both single‐ and multiple‐vehicle autonomous target reacquisition behaviors. The combination of on‐board target detection and autonomous reacquire capability is found to increase the effective survey coverage rate of the AUV‐based magnetic sensing system.

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“…Autonomous underwater vehicles (AUVs) that complement the ROVs, have been growing in popularity due to their unmanned and untethered design which makes them suited for large scale exploratory surveys with minimal human intervention and surface support. Also with the advent of new hardware technologies and powerful processors, these underwater vehicles have shown the potential to revolutionize our access to the oceans to address critical problems facing the marine community such as underwater search and mapping [100], climate change assessment, under ice exploration [20], geological mapping [84], marine habitat monitoring, man-made structure maintenance [17] and shallow water mine countermeasures [28], [47]. Accurate navigation is a crucial aspect of each of these missions.…”

Section: Motivationmentioning

confidence: 99%

Unified random finite set theoretic approach to autonomous underwater vehicle navigation

Kalyan¹

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LIST OF FIGURES 3.4 Illustration of the evolution of landmarks from state M*_i to M*. caused due to change in the state of the vehicle from x k _j to x^.. Some landmarks evolve (m^,.. .ni(, in this case), while some fall out from the FOV (m-[,m2, in this case) and some new landmarks (1117,171%, in this case) appear in the FOV of the sensor 51 3.5 Possible scenarios involved in sensor measurement modeling 55 3.6 Illustration of optimal Bayes filter recursion compressed as PHD filter recursion 59 4.1 Acoustic image of the swimming pool as obtained from a blazed array sonar. (Inset: An Optical image of the swimming pool environment) 69 4.2 Range-intensity spectra from a blazed array sonar is depicted for two different scenarios. The SNR is large, and landmark has a significant size and reflectivity in (a). The landmark can be deduced by applying a suitable threshold D t to the returns. Case (b) illustrates the intensity returns with a low SNR. In such a scenario any value of D t small enough to detect a landmark will also detect a large number of false detections, as in the case of detection threshold 2. Setting it high enough as in detection threshold 1 will result in miss detections. ... 74 4.3 Block diagram of order statistics constant false alarm rate detector.. . 75 4.4 Adaptive detection threshold (dotted lines) using OS-CFAR detector for a constant pp/\ = lxlO 6 for a range-intensity spectra of a blazed array sonar 76 4.5 Range and Bearing measurements containing actual landmark generated measurements (in green asterisk) immersed in a Poisson clutter (in gray crosses) with a density of A c = 5 83 4.6 Illustration of simulated sonar scan image with the actual locations of the landmarks (green asterisk) and the estimated landmarks (pink circles) along with its corresponding PHD local maxima from the Particle-PHD clutter filter 84 4.7 Illustration of simulated sonar scan image with the actual locations of the landmarks (green asterisk) and the estimated landmarks (pink circles) along with its corresponding PHD local maxima from the Particle-PHD clutter filter. Illustrates miss detection due to error in estimation of number of landmarks by the PHD clutter filter 85 4.8 Performance of the clutter filter based on the number of landmarks.. 86 4.9 Estimates of the range and bearing measurements from the PHD clutter filter (pink circles) superimposed with the actual landmark generated measurements (green asterisk) 87 xi ATTENTION: The Singapore Copyright Act applies to the use of this document. Nanyang Technological University Library LIST OF FIGURES 4.10 Integration of the PHD clutter filter with the conventional EKF navigation filter 88 4.11 Representation of the global and vehicle coordinate system. Vehicle is equipped with a blazed array sonar that provides a range r and a bearing 9 measurement to a detected landmark 89 4.12 Target setup: Five sonar reflectors tied in-line are suspended from the sea bed 95 4.13 Vehicle orientation estimates from the fiber optic gyroscope during the experimental run 95 4.14 Feature...

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Initial Buried Minehunting Demonstration of the Laser Scalar Gradiometer Operating Onboard REMUS 600

Cited by 4 publications

References 6 publications

Compact Quantum Magnetometer System on an Agile Underwater Glider

Compact Quantum Magnetometer System on an Agile Underwater Glider

Magnetic survey and autonomous target reacquisition with a scalar magnetometer on a small AUV

Unified random finite set theoretic approach to autonomous underwater vehicle navigation

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