• Title, Summary, Keyword: gunnery

Search Result 9, Processing Time 0.044 seconds

Gunnery Classification Method using Shape Feature of Profile and GMM (Profile 형태 특징과 GMM을 이용한 Gunnery 분류 기법)

  • Kim, Jae-Hyup;Park, Gyu-Hee;Jeong, Jun-Ho;Moon, Young-Shik
    • Journal of the Institute of Electronics Engineers of Korea CI
    • /
    • v.48 no.5
    • /
    • pp.16-23
    • /
    • 2011
  • Muzzle flash based on gunnery is the target that has huge energy. So, gunnery target in a long range over xx km is distinguishable in the IR(infrared) images, on the other hand, is not distinguishable in the CCD images. In this paper, we propose the classification method of gunnery targets in a infrared images and in a long range. The energy from gunnery have an effect on varous pixel values in infrared images as a property of infrared image sensor, distance, and atmosphere, etc. For this reason, it is difficult to classify gunnery targets using pixel values in infrared images. In proposed method, we take the profile of pixel values using high performance infrared sensor, and classify gunnery targets using modeling GMM and shape of profile. we experiment on the proposed method with infrared images in the ground and aviation. In experimental result, the proposed method provides about 93% classification rate.

Gunnery Classification Method Using Profile Feature Extraction in Infrared Images (적외선 영상에서의 시계열 특징 추출을 이용한 Gunnery 분류 기법 연구)

  • Kim, Jae-Hyup;Cho, Tae-Wook;Chun, Seung-Woo;Lee, Jong-Min;Moon, Young-Shik
    • Journal of the Korea Society of Computer and Information
    • /
    • v.19 no.10
    • /
    • pp.43-53
    • /
    • 2014
  • Gunnery has been used to detect and classify artilleries. In this paper, we used electro-optical data to get the information of muzzle flash from the artilleries. Feature based approach was applied; we first defined features and sub-features. The number of sub-features was 38~40 generic sub-features, and 2 model-based sub-features. To classify multiclass data, we introduced tree structure with clustering the classes according to the similarity of them. SVM was used for each non-leaf nodes in the tree, as a sub-classifier. From the data, we extracted features and sub-features and classified them by the tree structure SVM classifier. The results showed that the performance of our classifier was good for our muzzle flash classification problem.

Gunnery Detection Method Using Reference Frame Modeling and Frame Difference (참조 프레임 모델링과 차영상을 이용한 포격 탐지 기법)

  • Kim, Jae-Hyup;Song, Tae-Eun;Ko, Jin-Shin;Moon, Young-Shik
    • Journal of the Institute of Electronics Engineers of Korea CI
    • /
    • v.49 no.4
    • /
    • pp.62-70
    • /
    • 2012
  • In this paper, we propose the gunnery detection method based on reference frame modeling and frame difference method. The frame difference method is basic method in target detection, and it's applicable to the detection of moving targets. The goal of proposed method is the detection of gunnery target which has huge variation of energy and size in the time domain. So, proposed method is based on frame difference, and it guarantee real-time processing and high detection performance. In the method of frame difference, it's important to generate reference frame. In the proposed method, reference frame is modeled and updated in real time processing using statistical values for each pixels. We performed the simulation on 73 IR video data that has gunnery targets, and the experimental results showed that the proposed method has 95.7% detection ratio under condition that false alarm is 1 per hour.

Prediction of Potential Risk Posed by a Military Gunnery Range after Flood Control Reservoir Construction (홍수조절지 건설 후 사격장 주변지역의 위해성예측 사례연구)

  • Ryu, Hye-Rim;Han, Joon-Kyoung;Nam, Kyoung-Phile;Bae, Bum-Han
    • Journal of Soil and Groundwater Environment
    • /
    • v.12 no.1
    • /
    • pp.87-96
    • /
    • 2007
  • Risk assessment was carried out in order to improve the remediation and management strategy on a contaminated gunnery site, where a flood control reservoir is under construction nearby. Six chemicals, including explosive chemicals and heavy metals, which were suspected to possess risk to humans by leaching events from the site were the target pollutants for the assessment. A site-specific conceptual site model was constructed based on effective, reasonable exposure pathways to avoid any overestimation of the risk. Also, conservative default values were adapted to prevent underestimation of the risk when site-specific values were not available. The risks of the six contaminants were calculated by API's Decision Support System for Exposure and Risk Assessment with several assumptions. In the crater-formed-area(Ac), the non-carcinogenic risks(i.e., HI values) of TNT(Tri-Nitro-Toluene) and Cd were slightly larger than 1, and for RDX(Royal Demolition Explosives), over 50. The total non-carcinogenic risk of the whole gunnery range calculated to a significantly high value of 62.5. Carcinogenicity of Cd was estimated to be about $10^{-3}$, while that of Pb was about $5\;{\times}\;10^{-4}$, which greatly exceeded the generally acceptable carcinogenic risk level of $10^{-4}{\sim}10^{-6}$. The risk assessment results suggest that an immediate remediation practice for both carcinogens and non-carcinogens are required before the reservoir construction. However, for more accurate risk assessment, more specific estimations on condition shifts due to the construction of the reservoir are required, and more over, the effects of the pollutants to the ecosystem is also necessary to be evaluated.

Development of Network Based Tank Combat Training Model (네트워크 기반의 전차 교전 훈련 모델 개발)

  • Roh, Keun Lae;Kim, Eui Whan
    • Journal of the Korea Society of Systems Engineering
    • /
    • v.4 no.2
    • /
    • pp.27-33
    • /
    • 2008
  • As a part of development of Korean K2 main battle tank, embedded training computer to be operated in the main equipment, which makes it possible to train without a special-purposed training simulator, was adopted for tank combat training. The category of embedded training of Korean K2 main battle tank includes driving training, gunnery training, single tank combat training, platoon level combat training, and command and platoon leaders combat training. For realization unit level tank embedded training system, the virtual reality was utilized for real time image rendering, and network based real time communication system of K2 tank was utilized for sharing status information between tanks. As a result, it is possible to train themselves on their own tank for enhancing the operational skills and harmonized task with members.

  • PDF

A Study of the Korean Historical Development of Explosives Technology(Korean Traditional Explosive Technology) (화약기술발전의 사적고찰에 관한 연구 (한국의 고대 화약기술))

  • 나윤호;손선관
    • Journal of the Korean Professional Engineers Association
    • /
    • v.12 no.1
    • /
    • pp.12-20
    • /
    • 1979
  • The early history of gun powder (black powder) and explosives was closely connected with the discovery of methods of preparing and purifing salpetre (potassium nitrate KNO$_3$). The Chineses apparently became acquainted with salpetre firstly on about 11th century, and they were possibly the original discoverers of salpetre for raw material of gun powder. The Egyptians called it “Chinese snow”, and it is significant that Chingis-Khan, the Mongol conqueror, took the Chinese eenginees with him in 1218 to use it for attacking the fortifications of the Persian cities. The black powder was invented by chance by Chinese alchemists during the Song dynasty (11th century) in the process of manufacturing medicine, and the powder was introduced to Europe by Mongol army. The manufacturing method of salpetre and gun powder was introduced to Korea from China in 1374, and the powder alld gunnery manufacturing project was developed by Mu Sun Choe(崔茂宣), the first Korean engineer late in Koryo dynasty. Coming in to Yi dynasty the explosive technic, extractive method of salpetre, and gunnery manufacturing process were developed greatly by Mu Sun Choe and Hai Sin Choe (崔海臣). However, confronting with the Japanes invasion at Imjin War (1597) with more powerful western style rifles which had been introduced from the Portuguese, on the contrary Korean army with the traditional guns couldn't compete with them. The Chochong(烏銃, the western rifle introduced in Japane) were much superior to the Chinese style traditional guns in the shooting power and striking efficiency. On the other hand, the Japanese battle ships armed only with the Chochong, when confronted with the Korean turtle shaped ships under the commanding of Admiral Yi Sun-Sin(李舞臣), were defeated by the Korean canons on the ships. The technical development of the modern powder industry in Korea. with the construction of four big explosive plants from 1930 to 1945, has resulted the mass-production of explosives. This study was purposed to investigate to the process with regard to the details of introduction to the explosive technology in Korea, and intended to give a help to the engineers who are engaged in study of the explosive technics by means of giving a spot light data on the early process of the designs, and making suggestion to the researchers for further study and invent a new and modern explosive.

  • PDF

A Study on the Armor Optimization of Military Vehicle (군용차량 방탄재 최적화에 관한 연구)

  • Lee, Hyun-Jin;Choi, Jae-Shik;Kim, Geun-Won;Shin, Ki-Su
    • Journal of the Korea Institute of Military Science and Technology
    • /
    • v.16 no.4
    • /
    • pp.405-413
    • /
    • 2013
  • During the land operations, the enemy's gunnery is the primary threat. For the military vehicle, the bulletproof effect is the one of the important issues regarding the safety of soldiers on duty. Recently, the advanced military vehicles have planned to install armor plates. However, due to the budget problem, it is difficult to equip the protection systems. Hence, the optimum approach to increase bulletproof capability is essential. In this paper, the optimum thickness and component of the armor of military vehicles were evaluated by using finite element analysis for bullet impact effects. To achieve this aim, 7.62mm NATO bullet, 1.6mm steel and Kevlar-29 composite have been modeled and the simulations were conducted with various thickness cases by using MSC Nastran sol 700. Consequently, it was revealed that Kevlar-29 45 Layer is appropriate thickness for 7.62 bulletproof. Furthermore, Kevlar-29 in front of steel was effective by comparison with the back of steel for bulletproof.

Development of Lane and Vehicle Headway Direction Recognition System for Military Heavy Equipment's Safe Transport - Based on Kalman Filter and Neural Network - (안전한 군용 중장비 수송을 위한 차선 및 차량 진행 방향 인식 시스템 개발 - 칼만 필터와 신경망을 기반으로 -)

  • Choi, Yeong-Yoon;Choi, Kwang-Mo;Moon, Ho-Seok
    • Journal of the Korea Institute of Military Science and Technology
    • /
    • v.10 no.3
    • /
    • pp.139-147
    • /
    • 2007
  • In military transportation, the use of wide trailer for transporting the large and heavy weight equipments such as tank, armoured vehicle, and mobile gunnery is quite common. So, the vulnerability of causing traffic accidents for these wide military trailer to bump or collide with another car in adjacent lane is very high due to its broad width in excess of its own lane's width. Also, the possibility of these strayed accidents can be increased especially by the careless driver. In this paper, the recognition system of lane and vehicle headway direction is developed to detect the possible collision and warn the driver to prevent the fatal accident. In the system development, Kalman filtering is used first to extract the border of driving lane from the video images supplied by the CCD camera attached to the vehicle and the driving lane detection is completed with regression analysis. Next, the vehicle headway direction is recognized by using neural network scheme with the extracted parameters of the detected driving lane feature. The practical experiments for the developed system are also carried out in the real traffic road of Seoul city area and the results show us the more than 90% accuracy in recognizing the driving lane and vehicle headway direction.