• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.559-570
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• 2022

When a satellite image has low spatial resolution, it is difficult to detect small objects. In this research, we aim to check the effect of super resolution on object detection. Super resolution is a software method that increases the resolution of an image. Unpaired super resolution network is used to improve Sentinel-2's spatial resolution from 10 m to 3.2 m. Faster-RCNN, RetinaNet, FCOS, and S²ANet were used to detect vessels in the Sentinel-2 images. We experimented the change in vessel detection performance when super resolution is applied. As a result, the Average Precision (AP) improved by at least 12.3% and up to 33.3% in the ship detection models trained with the super-resolution image. False positive and false negative cases also decreased. This implies that super resolution can be an important pre-processing step in object detection, and it is expected to greatly contribute to improving the accuracy of other image-based deep learning technologies along with object detection.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.4
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• pp.365-373
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• 2019

An Image Infra-Red(IIR) seeker is widely used for precision guided munitions to provide intelligent and precise target detection in terms of high kill probability. However, there have been issues in determining the performance versus cost trade-offs due to high cost of seeker comparing to other units of the munitions. In this paper, performance/cost evaluations have been carried out to find the most cost-effective solution for developing the IIR seekers. The relationships between the critical parameters and cost are investigated to determine the optimal point which represents the low cost with high performance. It is expected that the presented approach will be able to be used for guidelines to select the appropriate IIR seeker for the given operating conditions and can be useful to estimate the cost effectiveness of the precision guided munitions at early design stage.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.709-712
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• 2020

영상 처리 응용을 위해 개발된 대부분의 CNN 기반 객체 탐지 기법은 mAP 를 올리기 위해 작은 객체 탐지에 더 주력하는 경향이 있다. 본 연구에서는 이미지 피라미드를 통한 서로 다른 해상도의 탐지 결과를 앙상블을 하여 작은 객체의 탐지 성능은 유지하면서 큰 객체의 탐지 성능을 향상시키고자 한다. 또한, 기존 NMS 방식의 문제점을 파악하고 새로운 NMS 방식인 G-NMS 를 제안한다. COCO 데이터로 실험 결과 서로 다른 해상도의 탐지 결과 앙상블을 통하여 30fps 이상의 실시간 탐지를 만족하면서 큰 객체에 대한 AP 가 0.5~1.5% 상승되었음을 확인하였다. 제안한 G-NMS 방식 적용시 큰 객체에 대한 AR 이 2.6~3.8% 상승되었으며, 작은 객체를 포함한 전체 mAP 가 0.7~0.9% 상승되었음을 확인하였다.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.4
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• pp.499-506
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• 2022

For autonomous ships to be commercialized and be able to navigate in coastal water, they must be able to detect maritime obstacles. One of the most common obstacles seen in coastal area are the farm buoys. In this study, a maritime object detection system was developed that detects buoys using the YOLO algorithm and visualizes the distance and bearing between buoys and the ship through geometric interpretation of camera images. After training the maritime object detection model with 1,224 pictures of buoys, the precision of the model was 89.0%, the recall was 95.0%, and the F1-score was 92.0%. Camera calibration had been conducted to calculate the distance and bearing of an object away from the camera using the obtained image coordinates and Experiment A and B were designed to verify the performance of the maritime object detection system. As a result of verifying the performance of the maritime object detection system, it can be seen that the maritime object detection system is superior to radar in its short-distance detection capability, so that it can be used as a navigational aid along with the radar.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.1
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• pp.23-29
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• 2014

The emergence of high resolution satellite images and the evolution of spatial resolution facilitate various studies using high resolution satellite images. Above all, target detection algorithms are effective for monitoring of traffic flow and military surveillance and reconnaissance because vehicles, airplanes, and ships on broad area could be detected easily using high resolution satellite images. Recently, many satellites are launched from global countries and the diversity of satellite images are also increased. On the contrary, studies on comparison about the spatial resolution or target detection, especially, are insufficient in domestic and foreign countries. Therefore, in this study, effects of spatial resolution on target detection are analyzed using the PSO target detection algorithm. The resampling techniques such as nearest neighbor, bilinear, and cubic convolution are adopted to resize the original image into 0.5m, 1m, 2m, 4m spatial resolutions. Then, accuracy of target detection is assessed according to not only spatial resolution but also resampling method. As a result of the study, the resolution of 0.5m and nearest neighbor among the resampling methods have the best accuracy. Additionally, it is necessary to satisfy the criteria of 2m and 4m resolution for the detection of airplane and ship, respectively. The detection of airplane need more high spatial resolution than ship because of their complexity of shape. This research suggests the appropriate spatial resolution for the plane and ship target detection and contributes to the criteria of satellite sensor design.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.6
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• pp.507-517
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• 2019

Multi-function radar(MFR) is a system that uses various functions such as detection, tracking, and classification. To operate the functions in real-time, the detection stage in MFR usually uses radar signals for short measurement time. We can utilize several conventional detectors in the MFR system to detect low radar cross section maritime targets in the sea-clutter; however, the detectors, which have been developed to be effective for radar signals measured for a longer time, may be inappropriate for MFR. In this study, we proposed a modelling technique of sea-clutter short measurement time. We combined the modeled sea-clutter signal with the maritime-target signal, which was obtained by the numerical analysis method. Using this combined model, we exploited four independent detectors and analyzed the detection performances.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.775-784
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• 2020

Recent global warming and anthropogenic activities have caused more frequent and massive wildfires with longer durations and more significant damages. MODIS has been monitoring global wildfires for almost 20 years, and GK2A and Himawari-8 are observing the wildfires in East Asia 144 times a day. However, the spatial resolution of 1 to 2 km is not sufficient for the detection of small and medium-size active fires, and therefore the studies on the active fire detection using high-resolution images are essential. However, there is no official product for the high-resolution active fire detection. Hence, we implemented the active fire detection algorithm of Landsat 8 and carried out a high-resolution-based detection of active fires in Australia in 2019, followed by the comparisons with the products of Himawari-8 and MODIS. Regarding the intense fires, the three satellites showed similar results, whereas the weak igniting and extinguishing fires or the fires in narrow areas were detected by only Landsat 8 with a 30m resolution. Small-sized fires, which are the majority in Korea, can be detected by the high-resolution satellites such as Landsat 8, Sentinel-2, Kompsat-3A, and the forthcoming Kompsat-7. Also, a comprehensive analysis together with the geostationary satellites in East Asia such as GK2A, Himawari-8, and Fengyun-3 will help the interoperability and the improvement of spatial and temporal resolutions.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.11a
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• pp.41-42
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• 2019

해양공간의 효율적인 활용과 해상사고 예방을 위하여 해상교통 현황 파악이 필요하다. 이를 위해서는 해상에서 운항하는 선박에 대한 면밀한 모니터링이 선행 되어야한다. 때문에 본 연구에서는 선박자동식별장치(Automatic Identification System, AIS)와 선박패스(V-Pass)를 활용하는 기존 모니터링 방법에서 나아가, 위성 자료를 활용한 연안 선박감시 방법을 해상교통관제(Vessel Traffic Service, VTS) 센터에서 활용하기 위한 방안을 제안한다. 위성 자료는 광범위한 영역에 대하여 다양한 정보를 획득할 수 있는 장점을 지니므로, 부산항 연안에서 수집한 AIS 데이터와 함께 딥 러닝 기반 선박 탐지 및 분류 모델에 활용함으로써, 보다 개선된 모니터링을 기대할 수 있다. 이를 활용하여 미식별 선박들의 출현 위치를 분석하고 나아가 선박의 종류를 예측함으로써, 상세한 해상교통 현황 파악 및 예측을 기대할 수 있다. 향후에는 선박의 종류 뿐 아니라 각 선박의 해상활동을 분석함으로써, 보다 체계적이고 실용적인 해양공간활용 계획수립에 도움이 될 수 있도록 개선할 계획이다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.186-186
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• 2022

과거에는 선박을 운용하기 위해서 많은 인원이 필요하였으나 최근 들어 선박 운용에 필요한 인원이 줄어들고 있으며, 더 나아가 자율적으로 운항하는 선박을 만들기 위한 연구가 활발히 수행되고 있다. 자율 운항 선박을 구성하는 여러 요소 중 인간의 시각을 대체하기 위한 자율 인지 시스템은 가장 선행되어야 하는 연구 분야 중 하나이다. RADAR (RAdio Detection And Ranging) 및 AIS (Automatic Identification System) 등의 전통적인 인지 센서를 활용한 연구가 진행 중이지만 사각지대나 탐지 주기 등의 한계가 있다. 따라서 본 연구에서는 다중 카메라 (광학, 열상, 파노라마)를 이용하여 전통적인 인지 센서의 한계를 보완하는 새로운 인지 시스템을 고안하였으며, 이를 기반으로 해상 장애물을 추적하여 동적 운동 정보를 얻었다. 먼저 실해역에서 수집한 이미지를 바탕으로 해상 장애물 탐지를 위한 데이터를 구성하고, 딥 러닝 기반의 탐지 모델을 학습시켰다. 탐지 모델을 이용하여 탐지한 결과는 직접 설계한 칼만 필터 기반의 적응형 추적 필터를 통과시켜 해상 장애물의운동 정보 (궤적, 속력, 방향)를 계산하는데 활용되었다. 또한 본 연구는 카메라를 센서로 활용했을 때의 한계를 보완하기 위하여 동 시간대에 다중 카메라에서 추적한 각각의 정보를 융합하였다. 그 결과 단일 카메라를 활용하는 경우, RADAR의 오차 범위 이내에 추적 결과가 수렴하는 양상을 보였으며, 다중 카메라를 활용하는 경우에는 단일 카메라보다 정확한 추적이 가능함을 확인하였다.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.5
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• pp.407-417
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• 2019

When a free-falling ballistic missile intercepts a maritime target in a sea clutter environment at high grazing angle, detection performance of the ballistic missile's seeker can be rapidly degraded by the effect of sea clutter. To solve this problem, it is necessary to verify the performance of maritime target detection via simulations based on various scenarios. We accomplish this by applying a two-dimensional cell -averaging constant false alarm rate detector to a two-dimensional radar image, which is generated by merging a sea clutter signal at high grazing angle with a maritime target signal corresponding to the signal-to-clutter ratio. Simulation results using a computer-aided design model and commercial numerical electromagnetic solver in various scenarios show that the performance of maritime target detection significantly depends on the grazing and azimuth angles.