• Geophysics and Geophysical Exploration
• /
• v.27 no.2
• /
• pp.119-128
• /
• 2024

Marine magnetic surveys provide a rapid and cost-effective method for pioneer geophysical survey for many purposes. Sea-surface magnetometers offer high accuracy but are limited to measuring the scalar total magnetic field and require dedicated cruise missions. Shipboard three-component magnetometers, on the other hand, can collect vector three components and applicable to any cruise missions. However, correcting for the ship's magnetic field, particularly viscous magnetization, still remains a challenge. This study proposes a new additional correction method for ship's viscous magnetization effect in vector data acquired by shipboard three-component magnetometer. This method utilizes magnetic data collected simultaneously with a sea-surface magnetometer providing total magnetic field measurements. Our method significantly reduces deviations between the two datasets, resulting in corrected vector anomalies with errors as low as 7-25 nT. These tiny errors are possibly caused by the vector magnetic anomaly and its related viscous magnetization. This method is expected to significantly improve the accuracy of shipborne magnetic surveys by providing corrected vector components. This will enhance magnetic interpretations and might be useful for understanding plate tectonics, geological structures, hydrothermal deposits, and more.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
• /
• v.14 no.6
• /
• pp.491-498
• /
• 2001

The relationship between electrical properties of YBaCuO superconductor and externally applied magnetic field was studied to develop a magnetic field apolarity sensor. The electrical resistance of the superconductor was increased by applying external magnetic field and even after removal of the magnetic field. The behavior was related to the magnetic flux trapped in the superconductor, which penetrates through the materials by the external magnetic field. Some portion of the superconductor was changed to a normal state by the trapped magnetic flux. The appearance of the normal state yielded to enhance the electrical resistance. Electrical characteristics of the superconductor with trapped magnetic flux were extremely sensitive to the external magnetic field and showed different responses depending on the direction of the magnetic field. Considering the observed properties of the superconductor with trapped magnetic flux, a magnetic sensor was fabricated to detect simultaneously both the intensity and the direction of the magnetic field.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37B no.9
• /
• pp.778-786
• /
• 2012

Sensors that are used on wireless sensor networks can be divided into two types: directional sensors, such as PIR, image, and electromagnetic sensors; and non-directional sensors, such as seismic, acoustic and magnetic sensors. In order to guarantee the line-of-sight of a directional sensor, the installation location of the sensor must be higher than ground level. Among non-directional sensors, seismic sensors should be installed on the ground in order to ensure the maximal performance. As a result, seismic sensors may have network connectivity problems due to communication failure. In this paper, we propose a 3D node deployment method to maximize the coverage and the network connectivity considering the sensor-specific properties. The proposed method is for non-directional sensors to be placed on the ground, while the directional sensor is installed above the ground, using trees or poles, to maximize the coverage. As a result, through the topology that the detection data from non-directional sensors are transmitted to the directional sensor, we can maximize the network connectivity. Simulation results show that our strategy improves sensor coverage and network connectivity.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37 no.7C
• /
• pp.544-553
• /
• 2012

A vehicle localization technology is an essential component to support many smart-vehicle applications, e.g. collision warning, adaptive cruise control, and so on. In this paper, we present a new vehicle localization algorithm based on the fusion of the sensing estimates from the local sensors and the GPS estimates from the inter-vehicle communications. The proposed algorithm consists of the greedy location data mapping algorithm and the position refinement algorithm. The former maps a sensing estimate with a GPS estimate based on the distance between themselves, and then the latter refines the GPS estimate of the subject vehicle based on the law of large numbers. From the numerical results, we demonstrate that the accuracy of the proposed algorithm outperforms that of the existing GPS estimates by at least 30 % in the longitudinal direction and by at least 60% in the lateral direction.

• Journal of Korea Society of Industrial Information Systems
• /
• v.18 no.1
• /
• pp.37-45
• /
• 2013

Almost of stroke patients who experience aftereffects such as motor, sensory and cognitive disorders have to take some rehabilitation therapies. It is known that the consistent training for rehabilitation therapy in their home is more effective than rehabilitation therapy in hospital. A few home training programs were developed but these programs don't give any appropriate feedback messages to the client. Therefore, we developed a home training program which can provide appropriate feedback message to the clients using the Kinect sensor which can analyze user's 3-D dimensional motion. With this development, the client can obtain some feedback messages such as the knowledges of performance, results and self-controlled feedback. The program will be more effective than any existing programs.

• The Journal of Korean Institute of Next Generation Computing
• /
• v.14 no.6
• /
• pp.57-65
• /
• 2018

Conventional RF signal-based indoor localization techniques such as BLE or Wi-Fi based fingerprinting method show considerable localization errors even in small-scale indoor environments due to unstable received signal strength(RSS) of RF signals. Therefore, it is difficult to apply the existing RF-based fingerprinting techniques to large-scale indoor environments such as airports and department stores. In this paper, instead of RF signal we use the geomagnetic sensor signal for indoor localization, whose signal strength is more stable than RF RSS. Although similar geomagnetic field values exist in indoor space, an object movement would experience a unique sequence of the geomagnetic field signals as the movement continues. We use a deep neural network model called the recurrent neural network (RNN), which is effective in recognizing time-varying sequences of sensor data, to track the user's location and movement path. To evaluate the performance of the proposed geomagnetic field based indoor positioning system (IPS), we constructed a magnetic field map for a campus testbed of about $94m{\times}26$ dimension and trained RNN using various potential movement paths and their location data extracted from the magnetic field map. By adjusting various hyperparameters, we could achieve an average localization error of 1.20 meters in the testbed.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.14 no.12
• /
• pp.6420-6426
• /
• 2013

The indoor areas for the commercial use of automatic monitoring systems of mobile robot localization improves the cognitive abilities and the needs of the environment with this emerging and existing mobile robot localization, and object recognition methods commonly around its great sensor are leveraged. On the other hand, there is a difficulty with a problem-solving self-location estimation in indoor mobile robots using only the sensors of the robot. Therefore, in this paper, a self-position estimation method for an enhanced and effective mobile robot is proposed using a marker and CCTV video that is already installed in the building. In particular, after recognizing a square mobile robot and the object from the input image, and the vertices were confirmed, the feature points of the marker were found, and marker recognition was then performed. First, a self-position estimation of the mobile robot was performed according to the relationship of the image marker and a coordinate transformation was performed. In particular, the estimation was converted to an absolute coordinate value based on CCTV information, such as robots and obstacles. The study results can be used to make a convenient self-position estimation of the robot in the indoor areas to verify the self-position estimation method of the mobile robot. In addition, experimental operation was performed based on the actual robot system.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.38C no.1
• /
• pp.131-140
• /
• 2013

Due to the limitations of the existing indoor positioning system depending on the radio wave, at present, it is required to introduce a new method in order to improve the accuracy in indoor environment. Recently, bio-inspired technology has become the future core technology. Thus, this study examined the accurate positioning method applying the abilities that animals with homing instinct measure their position by searching geomagnetic field with the use of their biomagnets. In order to confirm the applicability of geomagnetic field, a new source for indoor positioning, this study separated the constituent materials and building structure and designed the structures that can carry the actual magnetic field sensor and the data collection module. Subsequently, this study investigated the applicability of geomagnetic field as a positioning source by establishing the positioning system of Fingerprint method. In performance evaluation of the positioning system, the geomagnetic strength-based positioning system was similar to or approximately 20 percent higher than the wireless LAN-based positioning system in the buildings with the existing wireless LAN. Thus, in the environment without infrastructure for indoor positioning, the geomagnetic, an independent earth resource, can make it possible to realize the indoor positioning.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.26 no.3
• /
• pp.169-175
• /
• 2016

There are many researches to develop robots that improve its mobility and task planning to adapt in various uneven environments. In this paper, we propose the design method and task planning of quadruped robot which can have top-bottom docking structure. The proposed quadruped robot is designed to adjust leg length using linear actuators and perform top-bottom docking and undocking using octagonal cone shaped docking module. Also, to stable walking and information gathering in the various environments, a geomagnetic sensor, PSD sensor, LRF sensor and camera. We propose an obstacle avoidance method and the topbottom docking algorithm of the two quadruped robots using linear actuator. The robot can overcome obstacles using adjusting leg length and activate the top-bottom docking function. The top-bottom docking robots of two quadruped robot can walk 4 legged walking and 6 legged walking, and use 4 arms or 2 arms the upper. We verified that the docking robots can carry objects using 4 leg of the upper robot.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.12B
• /
• pp.1435-1443
• /
• 2009

In this paper, an energy harvesting sensor network system is modeled and simulated by using the DEVS (Discrete Event System Specification) formalism. The system is composed of a sink (master) node, which is battery or mains powered, and a set of sensor (slave) nodes, each of which harvests ambient energy and converts it into electrical energy. For simulation, (i) the behavior of energy harvesting and storing circuits of the slave node is partitioned into a set of piecewise continuous segments and then each segment is represented as a discrete state; (ii) the interaction among the master node and components of the slave node is investigated preciously; and (iii) the investigated result is modeled and simulated by using the DEVS formalism.