Application of a Drone Magnetometer System to Military Mine Detection in the Demilitarized Zone

Yoo, Lee-Sun; Lee, Jung-Han; Yong-Kuk, Lee; Jung, Seom‐Kyu; Choi, Yosoon

doi:10.3390/s21093175

Cited by 34 publications

(18 citation statements)

References 46 publications

(52 reference statements)

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“…Yoo Lee-Sun et al [100] proposed a UAV-magnetometer system and a data-processing method for detecting metal antipersonnel landmines in the demilitarized zone in Korea. The eight-rotor UAV used a Pixhawk flight controller enabling accurate flight along a survey line, a fluxgate magnetometer was installed in a pendulum manner, hanging about 50 cm below the landing pole, which allows a reduced distance between the land surface and the magnetometer.…”

Section: Multi-rotor Uavs For Magnetic Surveysmentioning

confidence: 99%

“…The proposed UAV-based landmine detection system is expected to reduce risk to detection personnel and shorten the landmine-detection period by providing accurate scientific information about the detection area prior to military landmine-detection efforts. Yoo Lee-Sun et al [100] proposed a UAV-magnetometer system and a data-processing method for detecting metal antipersonnel landmines in the demilitarized zone in Korea. The eight-rotor UAV used a Pixhawk flight controller enabling accurate flight along a survey line, a fluxgate magnetometer was installed in a pendulum manner, hanging about 50 cm below the landing pole, which allows a reduced distance between the land surface and the magnetometer.…”

Section: Multi-rotor Uavs For Magnetic Surveysmentioning

confidence: 99%

“…Additionally, this method is not suitable for fixed-wing UAVs, considering their high flight speed and altitude. [84] Eight-rotor 1.1 Rigidly mounted at the front of the UAV with an aluminum bar Parshin et al [114] Six-rotor 3 Suspended below the UAV with a cable Malehmir et al [85] Eight-rotor 3 Tied below the UAV with a cable Cunningham et al [86] Eight-rotor 3.6 Rigidly mounted at the front of the UAV Cherkasov and Kapshtan [104] Quadrotor 20 Towed below the UAV with a long rope Walter et al [42] Six-rotor 3 Semi-rigid suspended below the UAV Schmidt et al [41] Eight-rotor 3 Attached to the UAV via long ropes de Smet et al [93] Six-rotor 4 Towed below the UAV with a long rope Yoo Lee-Sun et al [100] Eight-rotor 1.2 Towed below the landing pole with a cable Shahsavani [101] Quadrotor 3 Towed below the UAV with two ropes Kim et al [102] Eight-rotor 3 Towed below the UAV with four ropes Romero et al [95] Six-rotor 1.2 Rigidly attached to the UAV with a rigid boom Pisciotta et al [98] Quadrotor 4 Suspended below the UAV with a long wire Petzke et al [105] Airship~4 Towed below the UAV with a long boom Wang et al [106] Airship 3.5 Rigidly attached to the UAV frame with a carbon fiber rod…”

Section: Suppression Of Uav Magnetic Interferencementioning

confidence: 99%

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Unmanned Aerial Vehicles for Magnetic Surveys: A Review on Platform Selection and Interference Suppression

Zheng

Xing

et al. 2021

Drones

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In the past two decades, unmanned aerial vehicles (UAVs) have been used in many scientific research fields for various applications. In particular, the use of UAVs for magnetic surveys has become a hot spot and is expected to be actively applied in the future. A considerable amount of literature has been published on the use of UAVs for magnetic surveys, however, how to choose the platform and reduce the interference of UAV to the collected data have not been discussed systematically. There are two primary aims of this study: (1) To ascertain the basis of UAV platform selection and (2) to investigate the characteristics and suppression methods of UAV magnetic interference. Systematic reviews were performed to summarize the results of 70 academic studies (from 2005 to 2021) and outline the research tendencies for applying UAVs in magnetic surveys. This study found that multi-rotor UAVs have become the most widely used type of UAVs in recent years because of their advantages such as easiness to operate, low cost, and the ability of flying at a very low altitude, despite their late appearance. With the improvement of the payload capacity of UAVs, to use multiple magnetometers becomes popular since it can provide more abundant information. In addition, this study also found that the most commonly used method to reduce the effects of the UAV’s magnetic interference is to increase the distance between the sensors and the UAV, although this method will bring about other problems, e.g., the directional and positional errors of sensors caused by erratic movements, the increased risk of impact to the magnetometers. The pros and cons of different types of UAV, magnetic interference characteristics and suppression methods based on traditional aeromagnetic compensation and other methods are discussed in detail. This study contributes to the classification of current UAV applications as well as the data processing methods in magnetic surveys.

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Section: Multi-rotor Uavs For Magnetic Surveysmentioning

confidence: 99%

Section: Multi-rotor Uavs For Magnetic Surveysmentioning

confidence: 99%

Section: Suppression Of Uav Magnetic Interferencementioning

confidence: 99%

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Unmanned Aerial Vehicles for Magnetic Surveys: A Review on Platform Selection and Interference Suppression

Zheng

Xing

et al. 2021

Drones

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show abstract

“…Moving on to the military usage of UAVs, the latter are used in different application areas, including mines detection [53], combat efficiency [54,55], battlefield mapping [56], and many others. A relevant context in which the UAVs are utilized regards land monitoring.…”

Section: Introductionmentioning

confidence: 99%

Low-Altitude Aerial Video Surveillance via One-Class SVM Anomaly Detection from Textural Features in UAV Images

et al. 2021

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In recent years, small-scale Unmanned Aerial Vehicles (UAVs) have been used in many video surveillance applications, such as vehicle tracking, border control, dangerous object detection, and many others. Anomaly detection can represent a prerequisite of many of these applications thanks to its ability to identify areas and/or objects of interest without knowing them a priori. In this paper, a One-Class Support Vector Machine (OC-SVM) anomaly detector based on customized Haralick textural features for aerial video surveillance at low-altitude is presented. The use of a One-Class SVM, which is notoriously a lightweight and fast classifier, enables the implementation of real-time systems even when these are embedded in low-computational small-scale UAVs. At the same time, the use of textural features allows a vision-based system to detect micro and macro structures of an analyzed surface, thus allowing the identification of small and large anomalies, respectively. The latter aspect plays a key role in aerial video surveillance at low-altitude, i.e., 6 to 15 m, where the detection of common items, e.g., cars, is as important as the detection of little and undefined objects, e.g., Improvised Explosive Devices (IEDs). Experiments obtained on the UAV Mosaicking and Change Detection (UMCD) dataset show the effectiveness of the proposed system in terms of accuracy, precision, recall, and F1-score, where the model achieves a 100% precision, i.e., never misses an anomaly, but at the expense of a reasonable trade-off in its recall, which still manages to reach up to a 71.23% score. Moreover, when compared to classical Haralick textural features, the model obtains significantly higher performances, i.e., ≈20% on all metrics, further demonstrating the approach effectiveness.

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“…법(Stoll, 2013;Nikulin et al, 2020;Schmidt et al, 2020;Yoo et al, 2020;Yoo et al, 2021;Zheng et al, 2021) 2) 대상을 단순한 발생원으로 근사하는 방법(Accomando et al, 2021;Kolster and Døssing, 2020;Kolster et al, 2022;Mu et al, 2020;Mu et al, 2021; …”

mentioning

confidence: 99%

A Review on Multirotor UAV-based Magnetic Surveys for Near-Surface Targets

Sh¹,

Kim²

2022

J. Korean Soc. Miner. Energy Resour. Eng.

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The development of unmanned aerial vehicles (UAVs), has led to extensive investigations of the applicability of magnetic surveys using various UAV systems, such as a recent multirotor UAV-based magnetic survey. Herein, we analyzed studies that focused on the detection of near-surface targets. In particular, recent studies have examined the installation position and configuration of the magnetometer, and the usage of sensors to improve the positioning accuracy of the multirotor UAVs. We introduced data analysis and processing methods to consider noise generated by multirotor UAVs, and various interpretation methods. The cases presented here show that multirotor UAV-based magnetic surveys have strengths in small-scale target detection with close-to-surface flight and that high-resolution data can be acquired through precise flight for the survey area. This technology is expected to be particularly useful for the detection of man-made objects and subsurface infrastructures, and for archaeological prospection.

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Application of a Drone Magnetometer System to Military Mine Detection in the Demilitarized Zone

Cited by 34 publications

References 46 publications

Unmanned Aerial Vehicles for Magnetic Surveys: A Review on Platform Selection and Interference Suppression

Unmanned Aerial Vehicles for Magnetic Surveys: A Review on Platform Selection and Interference Suppression

Low-Altitude Aerial Video Surveillance via One-Class SVM Anomaly Detection from Textural Features in UAV Images

A Review on Multirotor UAV-based Magnetic Surveys for Near-Surface Targets

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