• 대한원격탐사학회지
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• 제40권2호
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• pp.167-177
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• 2024

With advancements in satellite technology, interest in target detection and identification is increasing quantitatively and qualitatively. Synthetic Aperture Radar(SAR) images, which can be acquired regardless of weather conditions, have been applied to various areas combined with machine learning based detection algorithms. However, conventional studies primarily focused on the detection of stationary targets. In this study, we proposed a method to identify moving targets using an algorithm that integrates sub-aperture SAR images and cosine similarity calculations. Utilizing a transformer-based deep learning target detection model, we extracted the bounding box of each target, designated the area as a region of interest (ROI), estimated the similarity between sub-aperture SAR images, and determined movement based on a predefined similarity threshold. Through the proposed algorithm, the quantitative evaluation of target identification capability enhanced its accuracy compared to when training with the targets with two different classes. It signified the effectiveness of our approach in maintaining accuracy while reliably discerning whether a target is in motion.

• Nuclear Engineering and Technology
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• 제53권9호
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• pp.2899-2908
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• 2021

The laser transport system of the high power laser facility is mainly composed of large-aperture laser transport mirrors (TMs). Obtaining the high-resolution online damage images during the operation, which is of great significance for operating safely of the mirrors and the facility. Based on wavefront coding, pan-tilt scanning and image stitching technologies, an online laser-damage images detection system is designed, and it can achieve high-precision detection of surface characteristics of large-aperture laser transport mirrors. The preliminary simulation proves that the system can solve the depth of field matching problem caused by pan-tilt tilt imaging and achieve higher resolution.

• 전기학회논문지
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• 제60권5호
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• pp.1055-1061
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• 2011

In this study, main parameters: aperture, first bend and second bend which express a structure of ear canal are extracted in order to modeling and manufacture the ready-made ear shells of hearing aids. The proposed parameter extraction method consists of 2 important algorithms, aperture detection and feature detection. In the aperture detection algorithm, aperture of 3-D scanned virtual ear impression and parameters relating to ear shell of hearing aid are determined. The feature detection algorithm detects first bend, second bend, and related parameters. Through these two algorithms, parameters for aperture, first bend, and second bend are extracted to model the ready-made ear shell of hearing aid. The values of these extracted parameters from 36 people's right ear impression are analyzed and measured statistically. As a result of the analysis, it has been found that it is possible to classify ready-made ear shell parameters by age and size. The ready-made ear shell parameters are classified 3-size for 20 years old and 2-size for 60 years olde. Using 3D rhino program, virtual ready-made ear shell is reconstructed by parameters of every type, and simulated to model it. A final product was produced by transferring simulation result with rapid prototyping system. The modeled ready-made ear shell is evaluated with the objective and subjective method. Objective method is the comparison volume ratio and overlapped volume ratio of ear impression from randomly chosen 18 people and ready-made ear shell. And subjective method is that the final product of ready-made ear shell is used by users and the satisfaction number drawn from well fitting and comfortable testing was evaluated. In the result of the evaluation, it has been found that volume ration is 70%, big and middle size ready-made ear shell products are possible, and the satisfaction number is high.

• 한국전자통신학회논문지
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• 제7권3호
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• pp.579-583
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• 2012

환경적으로 발생하는 미세입자를 감지하는 시스템을 설계하고 제작하였다. 미세입자 감지시스템은 광산란 현상을 이용하였으며, 레이저다이오우드, 렌즈, aperture, 수광소자로 구성되어진다. 검출시스템의 성능을 좋게 하기 위해 aperture, 렌즈, 수광소자의 위치를 시뮬레이션을 통해 최적화하였다. 제작된 감지시스템으로 유입되는 미세입자에 의한 광산란을 감지하므로 빠른 응답특성를 가지는 미세입자 감지시스템을 제작하였다.

• 한국군사과학기술학회지
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• 제13권3호
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• pp.461-469
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• 2010

In this paper, we have proposed an improved fusion method of detection features which can enhance the detection probability under the given false alarm rate in the prescreening stage of SAR ATR(Synthetic Aperture Radar Automatic Target Recognition) system. Since the detection features have the positive correlation, the detection performance can be improved if the joint probability distribution of detection features is considered in the fusion process. The detection region is designed as a simple piecewise linear function which can be represented by few parameters. The parameters for the detection region can be derived by training the sample SAR images to maximize the detection probability with the given false alarm rate. Simulation result shows that the detection performance of the proposed method is improved for all combinations of detection features.

• 한국전자파학회논문지
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• 제21권2호
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• pp.164-169
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• 2010

최근 SAR(Synthetic Aperture Radar) 영상의 거리 및 도플러 해상도가 높아짐에 따라 표적의 탐지 정확도는 향상되고 있지만 처리할 데이터 용량이 급증하고 있다. 기존의 단일 셀 기반 CFAR 검출기는 전체 영상 내에서 모든 거리 셀 데이터를 검사하여야 하므로 CFAR 검출기의 속도 성능 저하를 가져온다. 본 논문에서는 다중셀 기반 CFAR 처리 방법을 2단으로 개선하여 1단계에서는 다중 셀 평균 기반 CFAR 검출을 이용하여 예상 표적 지역을 검출하고, 2단계에서는 예상 표적 지역에 대해서만 단일 셀 기반 CFAR 검출을 수행함으로써 처리 시간을 줄이고 표적의 탐지 성능을 획기적으로 향상시켰다. 제안된 기법에 대한 성능은 실제 SAR 영상을 통하여 기존의 단일 셀 기반 방식과 다중 셀 평균 기반 검출 방식을 비교 분석하였다.

• 대한원격탐사학회지
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• 제39권6_3호
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• pp.1791-1799
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• 2023

한국항공우주연구원은 위성정보활용협의체 소속기관을 대상으로 아리랑위성 시리즈 영상자료 보급 및 활용지원을 담당하고 있다. 협의체 소속기관 사용자들은 대부분 광학 영상 중심으로 위성영상을 활용하고 있으며, 상대적으로 Synthetic Aperture Radar (SAR) 영상에 대한 활용 방안은 미흡한 실정이다. 본 논문에서는 SAR 영상자료 활용을 지원하기 위한 일환으로 향후 개발할 SAR 강도 기반 변화탐지 기술의 결정을 위해 현재까지 연구되어진 SAR 강도 기반 변화탐지 기술과 그 활용사례들을 조사했다. 조사 결과 많은 연구자로부터 강도 차분, 상관계수, 히스토그램(Histogram) 또는 편파 정보를 활용하여 변화 픽셀을 탐지하고 분석하기 위한 다양한 알고리즘들과 도시, 홍수, 산불, 식생과 같은 다양한 분야에서 변화탐지 알고리즘의 활용방안이 연구되었음을 확인할 수 있었다. 본 연구는 위성정보활용협의체에 활용할 SAR 변화탐지 기술 개발에 활용할 예정이다.

• 대한원격탐사학회지
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• 제33권1호
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• pp.89-95
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• 2017

Ship detection in synthetic aperture radar(SAR)imagery has long been an active research topic and has many applications. In this paper,we propose an efficient method for detecting ships from SAR imagery using filtering. This method exploits ship masking using a median filter that considers maximum ship sizes and detects ships from the reference image, to which a Non-Local means (NL-means) filter is applied for speckle de-noising and a differential image created from the difference between the reference image and the median filtered image. As the pixels of the ship in the SAR imagery have sufficiently higher values than the surrounding sea, the ship detection process is composed primarily of filtering based on this characteristic. The performance test for this method is validated using KOMPSAT-5 (Korea Multi-Purpose Satellite-5) SAR imagery. According to the accuracy assessment, the overall accuracy of the region that does not include land is 76.79%, and user accuracy is 71.31%. It is demonstrated that the proposed detection method is suitable to detect ships in SAR imagery and enables us to detect ships more easily and efficiently.

• Current Optics and Photonics
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• 제6권2호
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• pp.171-182
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• 2022

A single-photon laser and mid-wave infrared (MWIR) common aperture optical system was designed and developed to detect and range a long-distance civil aviation aircraft. The secondary mirror of the Ritchey-Chretien (R-C) optical system was chosen as a dichroic lens to realize the design of a common aperture system for the laser and MWIR. Point spread function (PSF) ellipticity was introduced to evaluate the coupling efficiency of the laser receiving system. A small aperture stop and narrow filter were set in the secondary image plane and an afocal light path of the laser system, respectively, and the stray light suppression ability of the small aperture stop was verified by modeling and simulation. With high-precision manufacturing technology by single point diamond turning (SPDT) and a high-efficiency dichroic coating, the laser/MWIR common aperture optical system with a 𝜑300 mm aluminum alloy mirror obtained images of buildings at a distance of 5 km with great quality. A civil aviation aircraft detection experiment was conducted. The results show that the common aperture system could detect and track long-distance civil aviation aircraft effectively, and the coverage was more than 450 km (signal-to-noise ratio = 6.3). It satisfied the application requirements for earlier warning and ranging of long-range targets in the area of aviation, aerospace and ground detection systems.

• 한국군사과학기술학회지
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• 제24권4호
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• pp.392-400
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• 2021

Unlike optical equipment, SAR(Synthetic Aperture Radar) has the advantage of obtaining images in all weather, and object detection in SAR images is an important issue. Generally, deep learning-based object detection was mainly performed in real-valued network using only amplitude of SAR image. Since the SAR image is complex data consist of amplitude and phase data, a complex-valued network is required. In this paper, a complex-valued ResNet network is proposed. SAR image object detection was performed by combining the ROI transformer detector specialized for aerial image detection and the proposed complex-valued ResNet. It was confirmed that higher accuracy was obtained in complex-valued network than in existing real-valued network.