• Title/Summary/Keyword: Target detection

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Phase Error Decrease Method for Target Direction Detection Improvement (표적 방향 탐지 향상을 위한 위상 오차 감소 방법)

  • Lee, Min-Soo
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.14 no.1
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    • pp.7-13
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    • 2021
  • This paper proposes a method to minimize the target's direction detection error using RADAR. The radar system cannot accurately detect the target direction due to the phase error of he received signal. The proposed method of this study obtains a phase by applying an root mean square to each antenna incident signal, and reduces the phase error by using an optimal signal to noise ratio. In the simulation result, the probability of detecting the target direction is the best when the antenna spacing is half wavelength. The conventional method of direction detection probability 10-1.7 and the proposed method is 10-3.3. The target detection direction of the existing method represents [-8°,8°] with an error of 2 degrees. The target detection direction of the proposed method is shown in [-10°,10°], and all target directions are accurately detected. In the future, There is need for a method to reduce the phase error even though the resolution decrease.

Dual Detection-Guided Newborn Target Intensity Based on Probability Hypothesis Density for Multiple Target Tracking

  • Gao, Li;Ma, Yongjie
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.10
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    • pp.5095-5111
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    • 2016
  • The Probability Hypothesis Density (PHD) filter is a suboptimal approximation and tractable alternative to the multi-target Bayesian filter based on random finite sets. However, the PHD filter fails to track newborn targets when the target birth intensity is unknown prior to tracking. In this paper, a dual detection-guided newborn target intensity PHD algorithm is developed to solve the problem, where two schemes, namely, a newborn target intensity estimation scheme and improved measurement-driven scheme, are proposed. First, the newborn target intensity estimation scheme, consisting of the Dirichlet distribution with the negative exponent parameter and target velocity feature, is used to recursively estimate the target birth intensity. Then, an improved measurement-driven scheme is introduced to reduce the errors of the estimated number of targets and computational load. Simulation results demonstrate that the proposed algorithm can achieve good performance in terms of target states, target number and computational load when the newborn target intensity is not predefined in multi-target tracking systems.

Comparison of Detection Probability for Conventional and Time-Reversal (TR) Radar Systems

  • Yoo, Hyung-Ha;Koh, Il-Suek
    • Journal of electromagnetic engineering and science
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    • v.12 no.1
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    • pp.70-76
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    • 2012
  • We compare the detection probabilities of the time-reversal(TR) detection system and the conventional radar system. The target is assumed to be hidden inside a random medium such as a forest. We propose a TR detection system based on the SAR(Synthetic Aperture Radar) algorithm. Unlike the conventional SAR images, the proposed TR-SAR system has an interesting property. Specifically, the target-related signal components due to the time-reversal refocusing characteristics, as well as some of clutter-related signal components are concentrated at the time-reversal reference point. The remaining clutter-related signal components are scattered around that reference point. In this paper, we model the random media as a collection of point scatterers to avoid unnecessary complexities. We calculate the detection probability of the TR radar system based on the proposed simple random media model.

Development of Torpedo Target Detection Section Interface Simulation System based on DEVS Integrated Development Environment (DEVS 통합개발환경 기반 모의 어뢰 표적탐지부 연동장비 개발)

  • Lee, Min Kyu;Hwang, Kun Chul;Lee, Dong Hoon;Nah, Young In;Kim, Woo Shik
    • Journal of the Korea Society for Simulation
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    • v.24 no.1
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    • pp.25-34
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    • 2015
  • It is necessary for us to undergo trial and error for eliciting the rational requirement of the acquisition of weapon systems, but the M&S is general approach due to costs and risk of the development. In addition to the acquisition of weapon systems, M&S is extensively employed in the analysis and the training of developed weapon systems. The ADD (Agency for Defense Development) has developed DEVS integrated development environment (QUEST) that provides M&S general ground technique composed of simulation model implementation services, simulation result analysis services, and simulation interface services. This paper describes the interface architecture and the implementation of torpedo target detection section interface simulation system using QUEST. The torpedo target detection section interface simulation system is composed of torpedo target detection section which calculates a result of target detection and the QUEST scenario generator which provides simulation scenario for performance test of the torpedo target detection section. The interface architecture of torpedo target detection section interface simulation system is designed to verify the interface and performance of the torpedo target detection section by linking with the QUEST scenario generator.

Effects of Spatial Resolution on PSO Target Detection Results of Airplane and Ship (항공기와 선박의 PSO 표적탐지 결과에 공간해상도가 미치는 영향)

  • Yeom, Jun Ho;Kim, Byeong Hee;Kim, Yong Il
    • 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.

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
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    • v.33 no.5_1
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    • pp.547-557
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    • 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.

Track-Before-Detect Algorithm for Multiple Target Detection (다수 표적 탐지를 위한 Track-Before-Detect 알고리듬 연구)

  • Won, Dae-Yeon;Shim, Sang-Wook;Kim, Keum-Seong;Tahk, Min-Jea;Seong, Kie-Jeong;Kim, Eung-Tai
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.39 no.9
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    • pp.848-857
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    • 2011
  • Vision-based collision avoidance system for air traffic management requires a excellent multiple target detection algorithm under low signal-to-noise ratio (SNR) levels. The track-before-detect (TBD) approaches have significant applications such as detection of small and dim targets from an image sequence. In this paper, two detection algorithms with the TBD approaches are proposed to satisfy the multiple target detection requirements. The first algorithm, based on a dynamic programming approach, is designed to classify multiple targets by using a k-means clustering algorithm. In the second approach, a hidden Markov model (HMM) is slightly modified for detecting multiple targets sequentially. Both of the proposed approaches are used in numerical simulations with variations in target appearance properties to provide satisfactory performance as multiple target detection methods.

A novel hybrid method for robust infrared target detection

  • Wang, Xin;Xu, Lingling;Zhang, Yuzhen;Ning, Chen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.10
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    • pp.5006-5022
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    • 2017
  • Effect and robust detection of targets in infrared images has crucial meaning for many applications, such as infrared guidance, early warning, and video surveillance. However, it is not an easy task due to the special characteristics of the infrared images, in which the background clutters are severe and the targets are weak. The recent literature demonstrates that sparse representation can help handle the detection problem, however, the detection performance should be improved. To this end, in this text, a hybrid method based on local sparse representation and contrast is proposed, which can effectively and robustly detect the infrared targets. First, a residual image is calculated based on local sparse representation for the original image, in which the target can be effectively highlighted. Then, a local contrast based method is adopted to compute the target prediction image, in which the background clutters can be highly suppressed. Subsequently, the residual image and the target prediction image are combined together adaptively so as to accurately and robustly locate the targets. Based on a set of comprehensive experiments, our algorithm has demonstrated better performance than other existing alternatives.

Optimal search plan for multiple moving targets with search priorities incorporated

  • Sung C. S.;Kim M. H.;Lee I. S.
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2004.10a
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    • pp.13-16
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    • 2004
  • This paper deals with a one-searcher multi-target search problem where targets with different detection priorities move in Markov processes in each discrete time over a given space search area, and the total number of search time intervals is fixed. A limited search resource is available in each search time interval and an exponential detection function is assumed. The searcher can obtain a target detection award, if detected, which represents the detection priority of target and is non-increasing with time. The objective is to establish the optimal search plan which allocates the search resource effort over the search areas in each time interval in order to maximize the total detection award. In the analysis, the given problem is decomposed into intervalwise individual search problems each being treated as a single stationary target problem for each time interval. An associated iterative procedure is derived to solve a sequence of stationary target problems. The computational results show that the proposed algorithm guarantees optimality.

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IR and SAR Sensor Fusion based Target Detection using BMVT-M (BMVT-M을 이용한 IR 및 SAR 융합기반 지상표적 탐지)

  • Lim, Yunji;Kim, Taehun;Kim, Sungho;Song, WooJin;Kim, Kyung-Tae;Kim, Sohyeon
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.11
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    • pp.1017-1026
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    • 2015
  • Infrared (IR) target detection is one of the key technologies in Automatic Target Detection/Recognition (ATD/R) for military applications. However, IR sensors have limitations due to the weather sensitivity and atmospheric effects. In recent years, sensor information fusion study is an active research topic to overcome these limitations. SAR sensor is adopted to sensor fusion, because SAR is robust to various weather conditions. In this paper, a Boolean Map Visual Theory-Morphology (BMVT-M) method is proposed to detect targets in SAR and IR images. Moreover, we suggest the IR and SAR image registration and decision level fusion algorithm. The experimental results using OKTAL-SE synthetic images validate the feasibility of sensor fusion-based target detection.