• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2012.05a
• /
• pp.557-559
• /
• 2012

The fire distress detection and rescue user terminal, which rescue the survivor by using the direction finding of distress place and sensing techniques, was design and implemented. The user terminal provides the rescue function in the place of evil surroundings that can not be available the communication facilities. The rescue user terminal provides the portable configuration, which consists of a RF board with radio frequency of 2.45 GHz and inner antenna, and a control board. The inner antenna with $60^{\circ}$ or $120^{\circ}$ directivity, which use the triangulation, detects the rescue signal from survivor. The rescue was managed by allotment of user ID and can use the bidirectional audio channel using radio frequency of 5.8 GHz.

• Journal of Advanced Navigation Technology
• /
• v.10 no.4
• /
• pp.377-384
• /
• 2006

In this paper the detection time of the distress signal for the satellite-based search and rescue (SAR) system is evaluated. Present LEOSAR system in operation employs a few Low-altitude Earth Orbit (LEO) satellites and hence provides poor and local coverage availability. This results in a considerably long waiting time for a distress beacon to be detected by a rescue mission control center. One can expect that the detection time of the distress signal will be significantly reduced if the proposed MEOSAR system, which is based on the Medium-altitude Earth Orbit (MEO) satellites, is implemented. Taking into account the influence of the obstacles on the beacon signal, simulations are carried out to evaluate the detection time of distress signals for the LEOSAR and MEOSAR systems and the corresponding results are analyzed.

• Korean Journal of Remote Sensing
• /
• v.39 no.6_1
• /
• pp.1451-1466
• /
• 2023

In the context of maritime emergencies, the utilization of drones has rapidly increased, with a particular focus on their application in search and rescue operations. Deep learning models utilizing drone images for the rapid detection of distressed vessels and other maritime drift objects are gaining attention. However, effective training of such models necessitates a substantial amount of diverse training data that considers various weather conditions and vessel states. The lack of such data can lead to a degradation in the performance of trained models. This study aims to enhance the performance of deep learning models for distress ship detection by developing a maritime environment simulator to augment the dataset. The simulator allows for the configuration of various weather conditions, vessel states such as sinking or capsizing, and specifications and characteristics of drones and sensors. Training the deep learning model with the dataset generated through simulation resulted in improved detection performance, including accuracy and recall, when compared to models trained solely on actual drone image datasets. In particular, the accuracy of distress ship detection in adverse weather conditions, such as rain or fog, increased by approximately 2-5%, with a significant reduction in the rate of undetected instances. These results demonstrate the practical and effective contribution of the developed simulator in simulating diverse scenarios for model training. Furthermore, the distress ship detection deep learning model based on this approach is expected to be efficiently applied in maritime search and rescue operations.

• Journal of the Korea Convergence Society
• /
• v.10 no.1
• /
• pp.1-6
• /
• 2019

In this paper, we have studied a direction finding method of the radio signal by comparing the phase difference and its pattern from the uniform circular array antenna. In the phase comparison direction finding, if the length of the antenna baseline is longer than 0.5 wavelength of the incident signal, azimuth ambiguity occurs in which two or more azimuth angles are calculated in the same phase difference. The azimuthal ambiguity is removed by fusing the phase difference of the 5 antennas. The developed ambiguity elimination technology reduces the azimuth error where the antenna baseline is shorter than 1.236 wavelength in the uniform circular array with five antennas. This algorithm is very useful for the design of direction finder of an electronic information system.

• Journal of Navigation and Port Research
• /
• v.26 no.1
• /
• pp.28-34
• /
• 2002

Irregular reflected signals on a sea surface make clutters to a ship's radar image. Clutters are similar to Gaussian white noises which are very harmful for detecting objecting at sea by a ship's radar. To remove the clutter effects, many papers show the algorithms by antenna, filters, and so on. This paper shows a new algorithm which uwes Wavelet and Morphology median filter conceps for removing clutter and enhancing image in order to detect well a distressed of being rescued ship in a rough weather condition at sea.