• Title/Summary/Keyword: target acquisition

Search Result 350, Processing Time 0.028 seconds

A Study on Performance Improvement for Acquiring Time of Ship Target through Defining and Analysing the Main Affecting Factors of Tracking Radar (추적레이더의 주요영향인자 정의 및 분석을 통한 대함표적획득시간 성능향상에 관한 연구)

  • Kim, Seung-Woo;Cho, Heung-Gi
    • Journal of the Institute of Electronics Engineers of Korea SC
    • /
    • v.44 no.3
    • /
    • pp.22-28
    • /
    • 2007
  • The STIR(Signal Tracking & Illumination Radar) in KDX(Korean Destroyer Experimental) combat system acquires target from designating 3-D target information of surveillance radar (MW-08), and The performance of radar is decided by target acquisition time and accuracy of tracking loop because the STIR tracks automatically in accordance with tracking algorithm. In the view of ship, elements related with target acquisition time of the STIR can be various. In this paper the target acquisition time of the STIR is reduced by identifying the elements and suggesting the performance improvement method. The way of performance improvement is suggested through analysing main affecting factors. First, tracking algorism is required for analysis. Second, fitness of parameters that control elements related with acquisition distance is analyzed. And the third, accuracy of ship based sensors is analyzed. In conclusion, acquisition time against ship target can be advanced to 3 seconds from 10 seconds.

Estimating Characteristic Data of Target Acquisition Systems for Simulation Analysis (모의 분석을 위한 표적 획득 체계의 특성 데이터 산출)

  • Tae Yoon Kim;Sang Woo Han;Seung Man Kwon
    • Journal of the Korea Society for Simulation
    • /
    • v.32 no.1
    • /
    • pp.45-54
    • /
    • 2023
  • Under combat simulation environment when inputting the detection performance data of the real system into the simulated object the given data affects the simulation analysis result. ACQUIRE-Target Task Performance Metric (TTPM)-Target Angular Size (TAS) model is used as a target acquisition model to simulate the detection ability of entities in the main combat simulation tool. This model estimates the decomposition curve of the object sensor and output the detection distance according to the target type. However, it is not easy to apply the performance of the new detection object that the user wants to input to the target acquisition model. Users want to input the detection distance into the target acquisition model, but the target acquisition model requires sensor decomposition curve data according to encounter conditions. In this paper, we propose a method of inversely deriving the sensor decomposition curve data of the target acquisition model by taking the detection distance to the target as an input. Here, the sensor decomposition curve data simultaneously satisfies each detection distance for three types of targets: personnel, ground vehicles, and aircraft. Finally, the detection distance of various reconnaissance equipment is applied to the detection object, and the detection effect according to the reconnaissance equipment is analyzed.

Acquisition Modeling of an Airborne Target for IR Target Tracking Simulation (적외선 표적 추적 시뮬레이션을 위한 공중 표적 포착 모델링)

  • 오정수;두경수;장성갑;서동선;최종수
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.24 no.8B
    • /
    • pp.1593-1600
    • /
    • 1999
  • This paper describes the acquisition modeling of an airborne target for target tracking simulation of infrared homing missiles. The modeling, of which key technologies are the sub-modeling for target infrared signature, atmospheric transmission, and receiver characteristics, shows the acquisition process of an airborne target under various tracking conditions determined by line-of-sight, distance, and atmospheric conditions. We confirm the validity of the modeling by applying it to simulations concerned with target tracking. The modeling gives a guideline to determine an optimum detector and a defection band for effective discrimination of the target among false targets.

  • PDF

Target Acquisition and Tracking of Tracking Radar (추적레이다의 표적 탐지 및 추적 기술 동향)

  • Shin, Han-Seop;Choi, Jee-Hwan;Kim, Dae-Oh;Kim, Tae-Hyung
    • Current Industrial and Technological Trends in Aerospace
    • /
    • v.7 no.1
    • /
    • pp.113-118
    • /
    • 2009
  • In this paper, we described the model of noise, target for tracking radar and range tracking, angle tracking, and Doppler frequency tracking for target acquisition and tracking. Target signal as well as the noise signal is modeled as random process varying with elapsed time. This paper addresses three areas of radar target tracking: range tracking, angle tracking, and Doppler frequency tracking. In general, range tracking is prerequisite to and inherent in both angle and Doppler frequency tracking systems. First, we introduced the several range tracking and described techniques for achieving range tracking. Second, we described the radar angle tracking techniques including conical scan, sequential lobing, and monopulse. Finally, we presented concepts and techniques for Doppler frequency tracking for several radar types.

  • PDF

A Study on Target Acquisition and Tracking to Develop ARPA Radar (ARPA 레이더 개발을 위한 물표 획득 및 추적 기술 연구)

  • Lee, Hee-Yong;Shin, Il-Sik;Lee, Kwang-Il
    • Journal of Navigation and Port Research
    • /
    • v.39 no.4
    • /
    • pp.307-312
    • /
    • 2015
  • ARPA(Automatic Radar Plotting Aid) is a device to calculate CPA(closest point of approach)/TCPA(time of CPA), true course and speed of targets by vector operation of relative courses and speeds. The purpose of this study is to develop target acquisition and tracking technology for ARPA Radar implementation. After examining the previous studies, applicable algorithms and technologies were developed to be combined and basic ARPA functions were developed as a result. As for main research contents, the sequential image processing technology such as combination of grayscale conversion, gaussian smoothing, binary image conversion and labeling was deviced to achieve a proper target acquisition, and the NNS(Nearest Neighbor Search) algorithm was appllied to identify which target came from the previous image and finally Kalman Filter was used to calculate true course and speed of targets as an analysis of target behavior. Also all technologies stated above were implemented as a SW program and installed onboard, and verified the basic ARPA functions to be operable in practical use through onboard test.

Performance Improvement Technique of Long-range Target Information Acquisition for Airborne IR Camera

  • Yang, Hyun-Jin
    • Journal of the Korea Society of Computer and Information
    • /
    • v.22 no.7
    • /
    • pp.39-45
    • /
    • 2017
  • In this paper, we propose three compensation methods to solve problems in high-resolution airborne infrared camera and to improve long-range target information acquisition performance. First, image motion and temporal noise reduction technique which is caused by atmospheric turbulence. Second, thermal blurring image correction technique by imperfect performance of NUC(Non Uniformity Correction) or raising the internal temperature of the camera. Finally, DRC(Dynamic Range Compression) and flicker removing technique of 14bits HDR(High Dynamic Range) infrared image. Through this study, we designed techniques to improve the acquisition performance of long-range target information of high-resolution airborne infrared camera, and compared and analyzed the performance improvement result with implemented images.

How Do Advisors Influence Mergers and Acquisitions?: An Analysis of Acquisitions in Japan

  • KOO, Ja Seung
    • The Journal of Asian Finance, Economics and Business
    • /
    • v.7 no.7
    • /
    • pp.123-129
    • /
    • 2020
  • The objective of this study is to examine the differentiated influence of sell-side advisors and buy-side advisors on mergers and acquisitions (M&A). Unlike prior studies on M&A advisors, the study addresses different roles of target and acquirer advisors, and explores their influences on the cumulative abnormal returns (CAR) and acquisition premiums with an empirical analysis of longitudinal data of M&As conducted by Japanese listed firms except financial companies from 1995 to 2012. M&A data were obtained from the Securities Data Corporation's (SDC) database, and the individual firm data were collected from the Nikkei Economic Electronic Databank System (NEEDS), which provides a wide range of corporate information including financial status, operational performance, and strategy. Using a sample of 452 cases for the CAR and 498 cases for the analysis of acquisition premiums, the empirical results support the hypotheses of the target advisor's positive association with CAR and acquirer advisor's positive association with acquisition premiums. The findings of this study indicate the target advisor's positive contribution to the success of acquisition process and performance, and acquirer advisor's negative influence on the deal progress. The study provides theoretical implications on M&A research and practical insights into the investment banking industry.

A Comparative Study of Second Language Acquisition Models: Focusing on Vowel Acquisition by Chinese Learners of Korean (중국인 학습자의 한국어 모음 습득에 대한 제2언어 습득 모델 비교 연구)

  • Kim, Jooyeon
    • Phonetics and Speech Sciences
    • /
    • v.6 no.4
    • /
    • pp.27-36
    • /
    • 2014
  • This study provided longitudinal examination of the Chinese learners' acquisition of Korean vowels. Specifically, I examined the Chinese learners' Korean monophthongs /i, e, ɨ, ${\Lambda}$, a, u, o/ that were created at the time of 1 month and 12 months, tried to verify empirically how they learn by dealing with their mother tongue, and Korean vowels through dealing with pattern of the Perceptual Assimilation Model (henceforth PAM) of Best (Best, 1993; 1994; Best & Tyler, 2007) and the Speech Learning Model (henceforth SLM) of Flege (Flege, 1987; Bohn & Flege, 1992, Flege, 1995). As a result, most of the present results are shown to be similarly explained by the PAM and SLM, and the only discrepancy between these two models is found in the 'similar' category of sounds between the learners' native language and the target language. Specifically, the acquisition pattern of /u/ and /o/ in Korean is well accounted for the PAM, but not in the SLM. The SLM did not explain why the Chinese learners had difficulty in acquiring the Korean vowel /u/, because according to the SLM, the vowel /u/ in Chinese (the native language) is matched either to the vowel /u/ or /o/ in Korean (the target language). Namely, there is only a one-to-one matching relationship between the native language and the target language. In contrast, the Chinese learners' difficulty for the Korean vowel /u/ is well accounted for in the PAM in that the Chinese vowel /u/ is matched to the vowel pair /o, u/ in Korean, not the single vowel, /o/ or /u/.

Study for Improving Target Coordinate Acquisition Accuracy from Long Distance by VRS RTK (VRS RTK를 이용한 원거리 표적좌표획득의 정확도 향상에 대한 연구)

  • Lee, Dongnyok;Yoon, Keunsig
    • Journal of the Korea Institute of Military Science and Technology
    • /
    • v.21 no.4
    • /
    • pp.471-480
    • /
    • 2018
  • Accurate target coordinate is very important in military operations especially field artillery's ground-to-ground attack and air-force's air-to-ground attack. DOS(or TAS) is used to acquire target coordinates from long distance. DOS is comprised of LRF and goniometer. LRF measures distance between DOS and target. Goniometer is comprised of azimuth and vertical angular sensors, DMC and internal GPS receiver. DOS must set the position and orientation(finding grid north) before measurement step(target coordinate acquisition). To improve accuracy of target coordinate, VRS RTK and reference point method are proposed in DOS setup step. VRS RTK provides accurate location coordinate with small deviations, providing high accuracy and precision in positioning and orientation. As a result, horizontal coordinate(easting and northing) accuracy is improved from 2.68 mil(C.L. = 0.95) mil to 0.58 mil(C.L. = 0.95).