• Title/Summary/Keyword: 표적탐지

Search Result 467, Processing Time 0.026 seconds

Small Target Detection Method under Complex FLIR Imagery (복잡한 FLIR 영상에서의 소형 표적 탐지 기법)

  • Lee, Seung-Ik;Kim, Ju-Young;Kim, Ki-Hong;Koo, Bon-Ho
    • Journal of Korea Multimedia Society
    • /
    • v.10 no.4
    • /
    • pp.432-440
    • /
    • 2007
  • In this paper, we propose a small target detection algorithm for FLIR image with complex background. First, we compute the motion information of target from the difference between the current frame and the created background image. However, the slow speed of target cause that it has the very low gray level value in the difference image. To improve the gray level value, we perform the local gamma correction for difference image. So, the detection index is computed by using statistical characteristics in the improved image and then we chose the lowest detection index a true target. Experimental results show that the proposed method has significantly the good detection performance.

  • PDF

Tonal Signal Detection for Acoustic Targets using ASM Neural Network (ASM 신경망을 이용한 음향 표적의 토날 신호 탐지)

  • 이성은
    • Proceedings of the Acoustical Society of Korea Conference
    • /
    • 1996.06a
    • /
    • pp.22-28
    • /
    • 1996
  • 수동 소나 시스템에서 표적을 탐지, 식별하는데 가장 중요한 인자는 표적에서 발생되는 토날 신호 성분이다. 수중의 주변잡음과 표적소음이 복합된 환경하에서 표적의 토날 신호성분을 정확히 추출하는데는 신호 탐지 준위 설정이나 주변 잡음의 변화에 의해 어려움이 있다. 본 논문에서는 ASM 신경망을 이용하여 신호 탐지 준위 설정이나 주변잡음의 변화에 강인한 음향 표적의 토날 신호 탐지 방식을 제안한다. 모의 시뮬레이션 및 실제 표적 신호에 적용하여 우수한 토날 신호 탐지 성능을 보인다.

  • PDF

Comparative Analysis of Target Detection Algorithms in Hyperspectral Image (초분광영상에 대한 표적탐지 알고리즘의 적용성 분석)

  • Shin, Jung-Il;Lee, Kyu-Sung
    • Korean Journal of Remote Sensing
    • /
    • v.28 no.4
    • /
    • pp.369-392
    • /
    • 2012
  • Recently, many target detection algorithms were developed for hyperspectral image. However, almost of these studies focused only accuracy from 1 or 2 data sets to validate and compare the algorithms although they give limited information to users. This study aimed to compare usability of target detection algorithms with various parameters. Five parameters were proposed to compare sensitivity in aspect of detection accuracy which are related with radiometric and spectral characteristics of target, background and image. Six target detection algorithms were compared in aspect of accuracy and efficiency (processing time) by variation of the parameters and image size, respectively. The results shown different usability of each algorithm by each parameter in aspect of accuracy. Second order statistics based algorithms needed relatively long processing time. Integrated usabilities of accuracy and efficiency were various by characteristics of target, background and image. Consequently, users would consider appropriate target detection algorithms by characteristics of data and purpose of detection.

SAR-IR 융합 기반 표적 탐지 기술 동향 분석

  • Im, Yun-Ji;Won, Jin-Ju;Kim, Seong-Ho;Kim, So-Hyeon
    • ICROS
    • /
    • v.21 no.4
    • /
    • pp.27-33
    • /
    • 2015
  • 단일 센서 기반의 표적 탐지 문제에서 센서의 한계 요소에 의해 탐지 성능이 제한된다. 따라서, 최근 단일 센서 기반의 표적 탐지 성능을 향상시키기 위한 방안으로 각 센서의 강점을 효과적으로 융합하는 다중 센서 정보 융합 기반의 표적 탐지 기법에 대한 연구가 활발히 진행되고 있다. 센서 정보 융합을 위해서는 각 센서별 영상 획득, 각 영상의 기하학적 정합, 센서 정보 융합 기반의 표적 탐지 기술이 필요하며, 본 논문에서는 이에 대한 기술 및 개발 동향을 소개한다.

  • PDF

The Surface Sidelobe Clutter and the False Alarm Probability of Target Detection for the HPRF Waveform of the Microwave Seeker (마이크로파 탐색기의 HPRF 파형에 대한 지표면 부엽클러터와 표적탐지 오류 확률)

  • Kim, Tae-Hyung;Yi, Jae-Woong;Byun, Young-Jin
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.34 no.4C
    • /
    • pp.476-483
    • /
    • 2009
  • Tracking and detecting targets by the microwave seeker is affected by the clutter reflecting from the earth's surface. In order to detect retreating targets in look-down scenario, which appear in the sidelobe clutter (SLC) region, in the microwave seeker of high pulse repetition frequency (HPRF) mode, it is necessary to understand statistical characteristics of the surface SLC. Statistical analysis of SLC has been conducted for several kinds of the surface using data obtained by the captive flight test of the microwave seeker in the HPRF mode. The probability density function (PDF) fitting is conducted for several kinds and conditions of the surface. PDFs and PDF parameters, which best describe statistical distribution of the SLC power, are estimated. By using the estimated PDFs and PDF parameters, analyses for setting the target-detection thresholds, which give a desired level of target-detection false alarm probability, are made. These analysis materials for statistical characteristics of SLC power and the target-detection threshold can be used in various fields, such as development of a target-detection method, the constant false alarm rate processing.

Hyperspectral Target Detection by Iterative Error Analysis based Spectral Unmixing (Iterative Error Analysis 기반 분광혼합분석에 의한 초분광 영상의 표적물질 탐지 기법)

  • Kim, Kwang-Eun
    • Korean Journal of Remote Sensing
    • /
    • v.33 no.5_1
    • /
    • pp.547-557
    • /
    • 2017
  • In this paper, a new spectral unmixing based target detection algorithm is proposed which adopted Iterative Error Analysis as a tool for extraction of background endmembers by using the target spectrum to be detected as initial endmember. In the presented method, the number of background endmembers is automatically decided during the IEA by stopping the iteration when the maximum change in abundance of the target is less than a given threshold value. The proposed algorithm does not have the dependence on the selection of image endmembers in the model-based approaches such as Orthogonal Subspace Projection and the target influence on the background statistics in the stochastic approaches such as Matched Filter. The experimental result with hyperspectral image data where various real and simulated targets are implanted shows that the proposed method is very effective for the detection of both rare and non-rare targets. It is expected that the proposed method can be effectively used for mineral detection and mapping as well as target object detection.

Study on Improving Hyperspectral Target Detection by Target Signal Exclusion in Matched Filtering (초분광 영상의 표적신호 분리에 의한 Matched Filter의 표적물질 탐지 성능 향상 연구)

  • Kim, Kwang-Eun
    • Korean Journal of Remote Sensing
    • /
    • v.31 no.5
    • /
    • pp.433-440
    • /
    • 2015
  • In stochastic hyperspectral target detection algorithms, the target signal components may be included in the background characterization if targets are not rare in the image, causing target leakage. In this paper, the effect of target leakage is analysed and an improved hyperspectral target detection method is proposed by excluding the pixels which have similar reflectance spectrum with the target in the process of background characterization. Experimental results using the AISA airborne hyperspectral data and simulated data with artificial targets show that the proposed method can dramatically improve the target detection performance of matched filter and adaptive cosine estimator. More studies on the various metrics for measuring spectral similarity and adaptive method to decide the appropriate amount of exclusion are expected to increase the performance and usability of this method.

Automatic target detection and tacking for a passive sonar system (수동소나에 적합한 자동탐지 및 추적기법 개발)

  • Seo Ik-Su;Yang In-Sic;Oh Wontchon
    • Proceedings of the Acoustical Society of Korea Conference
    • /
    • autumn
    • /
    • pp.467-470
    • /
    • 2004
  • 잠수함 정숙화 추세와 복잡한 해양 환경으로 대잠수함전에서 미약한 표적신호를 지속적으로 탐지하기 매우 어려워지고 있어 소나 운용자가 장시간 지속적으로 전방위 표적 탐색하는 부담이 매우 크므로 표적 자동탐지 추적 기능이 필수적이다. 본 논문에서는 장거리 예인 수동소나에 적합한 표적의 자동 탐지 및 추적기법을 제안하고 시뮬레이션과 실제 해상 환경에서 수중 표적신호로 성능을 검증하였다.

  • PDF

Smart Target Detection System Using Artificial Intelligence (인공지능을 이용한 스마트 표적탐지 시스템)

  • Lee, Sung-nam
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
    • /
    • 2021.05a
    • /
    • pp.538-540
    • /
    • 2021
  • In this paper, we proposed a smart target detection system that detects and recognizes a designated target to provide relative motion information when performing a target detection mission of a drone. The proposed system focused on developing an algorithm that can secure adequate accuracy (i.e. mAP, IoU) and high real-time at the same time. The proposed system showed an accuracy of close to 1.0 after 100k learning of the Google Inception V2 deep learning model, and the inference speed was about 60-80[Hz] when using a high-performance laptop based on the real-time performance Nvidia GTX 2070 Max-Q. The proposed smart target detection system will be operated like a drone and will be helpful in successfully performing surveillance and reconnaissance missions by automatically recognizing the target using computer image processing and following the target.

  • PDF

Target Localization Using Geometry of Detected Sensors in Distributed Sensor Network (분산센서망에서 표적을 탐지한 센서의 기하학적 구조를 이용한 표적위치 추정)

  • Ryu, Chang Soo
    • Journal of the Institute of Electronics and Information Engineers
    • /
    • v.53 no.2
    • /
    • pp.133-140
    • /
    • 2016
  • In active sonar field, a target detection and localization based on a distributed sensor network has been much studied for the underwater surveillance of the coast. Zhou et al. proposed a target localization method utilizing the positions of target-detected sensors in distributed sensor network which consists of detection-only sensors. In contrast with a conventional method, Zhou's method dose not require to estimate the propagation model parameters of detection signal. Also it needs the lower computational complexity, and to transmit less data between network nodes. However, it has large target localization error. So it has been modified for reducing localization error by Ryu. Modified Zhou's method has better estimation performance than Zhou's method, but still relatively large estimation error. In this paper, a target localization method based on modified Zhou's method is proposed for reducing the localization error. The proposed method utilizes the geometry of the positions of target-detected sensors and a line that represents the bearing of target, a line can be found by modified Zhou's method. This paper shows that the proposed method has better target position estimation performance than Zhou's and modified Zhou's method by computer simulations.