• Title/Summary/Keyword: Multiple Target

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Feature information fusion using multiple neural networks and target identification application of FLIR image (다중 신경회로망을 이용한 특징정보 융합과 적외선영상에서의 표적식별에의 응용)

  • 선선구;박현욱
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.40 no.4
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    • pp.266-274
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    • 2003
  • Distance Fourier descriptors of local target boundary and feature information fusion using multiple MLPs (Multilayer perceptrons) are proposed. They are used to identify nonoccluded and partially occluded targets in natural FLIR (forward-looking infrared) images. After segmenting a target, radial Fourier descriptors as global shape features are defined from the target boundary. A target boundary is partitioned into four local boundaries to extract local shape features. In a local boundary, a distance function is defined from boundary points and a line between two extreme points. Distance Fourier descriptors as local shape features are defined by using distance function. One global feature vector and four local feature vectors are used as input data for multiple MLPs to determine final identification result of the target. In the experiments, we show that the proposed method is superior to the traditional feature sets with respect to the identification performance.

A Design and Fabrication of Multiple Scattering Points Generator for High Range Resolution Radar (고해상도 레이더용 다중산란점 발생장치의 설계 및 제작)

  • Lee, Ho-Joon;Kim, Youn-Jin;Yoon, Seung-Gu;Jeong, Hae-Chang;Kong, Deok-Kyu;Yi, Jae-Woong;Byun, Young-Jin
    • Journal of the Korea Institute of Military Science and Technology
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    • v.19 no.5
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    • pp.590-597
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    • 2016
  • We designed the multiple scattering points generation system to simulate an actual situation of target signal for high range resolution radar system. This provides replicating the target signals and controlling the status of target signals for radar system. This is composed transmit antenna and multi target generator. Transmit antenna is waveguide array antenna and multi target generator has signal distribution module and control & power module. Multi target generator is able to provide the high isolation and variable output power. Moreover, in order to monitor all output signals of the multi target generator, the flows of signals are programed in control & power module. The performance is demonstrated using experimented results of high range resolution radar.

OSR CFAR Robust to Multiple Underwater Target Environments (다중 수중 표적 환경에 강인한 OSR CFAR 알고리듬)

  • Hong, Seong-Won;Han, Dong-Seog
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.48 no.4
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    • pp.47-52
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    • 2011
  • Constant false alarm rate (CFAR) is an automatic detection algorithm for active sonar system. Among several CFAR algorithms, ordered statistics (OS) CFAR has the best performance over cell averaging (CA), smallest of (SO), greatest of (GO) algorithms at non-homogeneous environments. However, OS CFAR has the disadvantage of bad detection performance in multiple target conditions. We suggest an ordered statistics ratio (OSR) CFAR algorithm that is robust to multiple target environments. The proposed and conventional schemes are compared with computer simulations.

Dimmable Spatial Intensity Modulation for Visible-light Communication: Capacity Analysis and Practical Design

  • Kim, Byung Wook;Jung, Sung-Yoon
    • Current Optics and Photonics
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    • v.2 no.6
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    • pp.532-539
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    • 2018
  • Multiple LED arrays can be utilized in visible-light communication (VLC) to improve communication efficiency, while maintaining smart illumination functionality through dimming control. This paper proposes a modulation scheme called "Spatial Intensity Modulation" (SIM), where the effective number of turned-on LEDs is employed for data modulation and dimming control in VLC systems. Unlike the conventional pulse-amplitude modulation (PAM), symbol intensity levels are not determined by the amplitude levels of a VLC signal from each LED, but by counting the number of turned-on LEDs, illuminating with a single amplitude level. Because the intensity of a SIM symbol and the target dimming level are determined solely in the spatial domain, the problems of conventional PAM-based VLC and related MIMO VLC schemes, such as unstable dimming control, non uniform illumination functionality, and burdens of channel prediction, can be solved. By varying the number and formation of turned-on LEDs around the target dimming level in time, the proposed SIM scheme guarantees homogeneous illumination over a target area. An analysis of the dimming capacity, which is the achievable communication rate under the target dimming level in VLC, is provided by deriving the turn-on probability to maximize the entropy of the SIM-based VLC system. In addition, a practical design of dimmable SIM scheme applying the multilevel inverse source coding (MISC) method is proposed. The simulation results under a range of parameters provide baseline data to verify the performance of the proposed dimmable SIM scheme and applications in real systems.

Robust Generalized Labeled Multi-Bernoulli Filter and Smoother for Multiple Target Tracking using Variational Bayesian

  • Li, Peng;Wang, Wenhui;Qiu, Junda;You, Congzhe;Shu, Zhenqiu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.3
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    • pp.908-928
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    • 2022
  • Multiple target tracking mainly focuses on tracking unknown number of targets in the complex environment of clutter and missed detection. The generalized labeled multi-Bernoulli (GLMB) filter has been shown to be an effective approach and attracted extensive attention. However, in the scenarios where the clutter rate is high or measurement-outliers often occur, the performance of the GLMB filter will significantly decline due to the Gaussian-based likelihood function is sensitive to clutter. To solve this problem, this paper presents a robust GLMB filter and smoother to improve the tracking performance in the scenarios with high clutter rate, low detection probability, and measurement-outliers. Firstly, a Student-T distribution variational Bayesian (TDVB) filtering technology is employed to update targets' states. Then, The likelihood weight in the tracking process is deduced again. Finally, a trajectory smoothing method is proposed to improve the integrative tracking performance. The proposed method are compared with recent multiple target tracking filters, and the simulation results show that the proposed method can effectively improve tracking accuracy in the scenarios with high clutter rate, low detection rate and measurement-outliers. Code is published on GitHub.

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.

Design of Target Tracking System Using a New Intelligent Algorithm

  • Noh, Sun-Young;Joo, Young-Hoon;Park, Jin-Bae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.15 no.6
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    • pp.748-753
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    • 2005
  • When the maneuver occurs, the performance of the standard Kalman filter has been degraded because mismatches between the modeled target dynamics and the actual target dynamics. To solve this problem, the unknown acceleration is determined by using the fuzzy logic based on genetic algorithm(GA) method. This algorithm is the method to estimate the increment of acceleration by a fuzzy system using th relation between maneuver filler residual and non-maneuvering one. To optimize this system, a GA is utilized. And then, the modified filter is corrected by the new update equation method which is a fuzzy system using the relation between the filter residual and its variation. To shows the feasibility of the suggested method with only one filter, the computer simulations system are provided, this method is compared with multiple model method.

Federated Variable Dimension Kalman Filters with Input Estimation for Maneuvering Target Tracking (기동하는 표적의 추적을 위한 연합형 가변차원 입력추정필터)

  • Hwang-bo, Seong-Wook;Hong, Keum-Shik;Choi, Sung-Lin;Choi, Jae-Won
    • Journal of Institute of Control, Robotics and Systems
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    • v.5 no.6
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    • pp.764-776
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    • 1999
  • In this paper, a tracking algorithm for a maneuvering single target in the presence of multiple data from multiple sensors is investigated. Allowing individual sensors to function by themselves, the estimates from individual sensors on the same target are fused for the purpose of improving the state estimate. The filtering method adopted in the local sensors is the variable dimensional filter with input estimatio technique, which consists of a constant velocity model and a constant acceleration model. A posteriori probability for the maneuvering hypothesis is newly derived. It is shown that the relation function of the a posteriori probability is a function of only the covariance of the fused estimates. Simulation results are provided.

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A DNA Coding-Based Interacting Multiple Model Method for Tracking a Maneuvering Target (기동 표적 추적을 위한 DNA 코딩 기반 상호작용 다중모델 기법)

  • Lee, Bum-Jik;Joo, Young-Hoon;Park, Jin-Bae
    • Proceedings of the KIEE Conference
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    • 2002.11c
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    • pp.87-91
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    • 2002
  • The problem of maneuvering target tracking has been studied in the field of the state estimation over decades. The Kalman filter has been widely used to estimate the state of the target, but in the presence of a maneuver, its performance may be seriously degraded. In this paper, to solve this problem and track a maneuvering target effectively, a DNA coding-based interacting multiple model (DNA coding-based IMM) method is proposed. The proposed method can overcome the mathematical limits of conventional methods by using the fuzzy logic based on DNA coding method. The tracking performance of the proposed method is compared with those of the adaptive IMM algorithm and the GA-based IMM method in computer simulations.

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Angle Estimation Error Reduction Method Using Weighted IMM (Weighted IMM 기법을 사용한 각도 추정 오차 감소 기법)

  • Choi, Seonghee;Song, Taeklyul
    • Journal of the Korea Institute of Military Science and Technology
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    • v.18 no.1
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    • pp.84-92
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    • 2015
  • This paper proposes a new approach to reduce the target estimation error of the measurement angle, especially applied to the medium and long range surveillance radar. If the target has no maneuver and no change in heading direction for a certain time interval, the predicted angle of interacting multiple model(IMM) from the previous track information can be used to reduce the angle estimation error. The proposed method is simulated in 2 scenarios, a scenario with a non-maneuvering target and a scenario with a maneuvering target. The result shows that the new fusion solution(weighted IMM) with the predicted azimuth and the measured azimuth is worked properly in the two scenarios.