• Title/Summary/Keyword: Target Tracking

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Track Initiation and Target Tracking Filter Using LiDAR for Ship Tracking in Marine Environment (해양환경에서 선박 추적을 위한 라이다를 이용한 궤적 초기화 및 표적 추적 필터)

  • Fang, Tae Hyun;Han, Jungwook;Son, Nam-Sun;Kim, Sun Young
    • Journal of Institute of Control, Robotics and Systems
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    • v.22 no.2
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    • pp.133-138
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    • 2016
  • This paper describes the track initiation and target-tracking filter for ship tracking in a marine environment by using Light Detection And Ranging (LiDAR). LiDAR with three-dimensional scanning capability is more useful for target tracking in the short to medium range compared to RADAR. LiDAR has rotating multi-beams that return point clouds reflected from targets. Through preprocessing the cluster of the point cloud, the center point can be obtained from the cloud. Target tracking is carried out by using the center points of targets. The track of the target is initiated by investigating the normalized distance between the center points and connecting the points. The regular track obtained from the track initiation can be maintained by the target-tracking filter, which is commonly used in radar target tracking. The target-tracking filter is constructed to track a maneuvering target in a cluttered environment. The target-tracking algorithm including track initiation is experimentally evaluated in a sea-trial test with several boats.

A Study on Target Tracking Filter Architecture in Underwater Environment using Active and Passive Sensors (능, 수동센서를 이용한 수중환경에서의 표적추적필터 구조 연구)

  • Lim, Youngtaek;Suh, Taeil
    • Journal of the Korea Institute of Military Science and Technology
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    • v.18 no.5
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    • pp.517-524
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    • 2015
  • In this paper, we propose a new target tracking filter architecture using active and passive sensors in underwater environment. A passive sensor for target tracking needs a bearing measurement of target. And target tracking filter for using passive sensor has the observability problem. On the other hand, an active sensor does not have the problem associated with system observability problem because an active sensor uses bearing and range measurement. In this paper, the tracking filter algorithm that could be used in the active and passive sensor system is proposed to analyze maneuvering target and to improve target tracking performance. The proposed tracking filter algorithm is tested by a series of computer simulation runs and the results are analyzed and compared with existing algorithm.

Compressed Sensing-based Multiple-target Tracking Algorithm for Ad Hoc Camera Sensor Networks

  • Lu, Xu;Cheng, Lianglun;Liu, Jun;Chen, Rongjun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.3
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    • pp.1287-1300
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    • 2018
  • Target-tracking algorithm based on ad hoc camera sensor networks (ACSNs) utilizes the distributed observation capability of nodes to achieve accurate target tracking. A compressed sensing-based multiple-target tracking algorithm (CSMTTA) for ACSNs is proposed in this work based on the study of camera node observation projection model and compressed sensing model. The proposed algorithm includes reconfiguration of observed signals and evaluation of target locations. It reconfigures observed signals by solving the convex optimization of L1-norm least and forecasts node group to evaluate a target location by the motion features of the target. Simulation results show that CSMTTA can recover the subtracted observation information accurately under the condition of sparse sampling to a high target-tracking accuracy and accomplish the distributed tracking task of multiple mobile targets.

Multi-target Tracking Filters and Data Association: A Survey (다중표적 추적필터와 자료연관 기법동향)

  • Song, Taek Lyul
    • Journal of Institute of Control, Robotics and Systems
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    • v.20 no.3
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    • pp.313-322
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    • 2014
  • This paper is to survey and put in perspective the working methods of multi-target tracking in clutter. This paper includes theories and practices for data association and related filter structures and is motivated by increasing interest in the area of target tracking, security, surveillance, and multi-sensor data fusion. It is hoped that it will be useful in view of taking into consideration a full understanding of existing techniques before using them in practice.

Linear Robust Target Tracking Filter Using the Range Differences Measured By Formation Flying Multiple UAVs (다중 UAV에서 측정된 거리차 정보를 이용한 선형 강인 표적추적 필터 설계)

  • Lee, Hye-Kyung;Han, Seul-Ki;Ra, Won-Sang
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.61 no.2
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    • pp.284-290
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    • 2012
  • This paper addresses a new passive target tracking problem using the range differences measured by cooperative UAVs. In order to solve the range difference based passive target tracking problem within the framework of linear robust state estimation, the uncertain linear measurement model which contains the stochastic parameter uncertainty is derived by using the noisy range difference measurements. To cope with the performance degradation due to the stochastic parameter uncertainty, the recently developed non-conservative robust Kalman filtering technique [1] is applied. For the cruciform formation flying UAVs, the relationship between the target tracking performance and the measurement errors is quantitatively analyzed. The proposed filter has practical advantages over the classical nonlinear filters because, for its recursive linear structure, it can provide satisfactory convergence properties and is suitable for real-time multiple UAVs applications. Through the simulations, the usefulness of the proposed method is demonstrated.

Disjoint Particle Filter to Track Multiple Objects in Real-time

  • Chai, YoungJoon;Hong, Hyunki;Kim, TaeYong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.5
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    • pp.1711-1725
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    • 2014
  • Multi-target tracking is the main purpose of many video surveillance applications. Recently, multi-target tracking based on the particle filter method has achieved robust results by using the data association process. However, this method requires many calculations and it is inadequate for real time applications, because the number of associations exponentially increases with the number of measurements and targets. In this paper, to reduce the computational cost of the data association process, we propose a novel multi-target tracking method that excludes particle samples in the overlapped predictive region between the target to track and marginal targets. Moreover, to resolve the occlusion problem, we define an occlusion mode with the normal dynamic mode. When the targets are occluded, the mode is switched to the occlusion mode and the samples are propagated by Gaussian noise without the sampling process of the particle filter. Experimental results demonstrate the robustness of the proposed multi-target tracking method even in occlusion.

Multiple Target Tracking using Normalized Rayleigh Likelihood of Amplitude Information of Target (Normalized Rayleigh Likelihood를 활용한 표적신호세기정보 적용 다중표적추적 기술)

  • Kim, Sujin;Jung, Younghun;Kim, Seongjoon
    • Journal of the Korea Institute of Military Science and Technology
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    • v.20 no.4
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    • pp.474-481
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    • 2017
  • This paper presents a multiple target tracking system using Normalized Rayleigh likelihood of amplitude information of target. Although many studies of Radar systems using amplitude information have been studied, they are focused on single target tracking. This paper proposes the multiple target tracking using amplitude information as well as kinematic information from Radar sensor. The amplitude information are applied in generating the association probability of joint probabilistic data association(JPDA) algorithm through the normalized Rayleigh likelihood. It is verified that the proposed system can enhance the track maintenance and tracking accuracy, especially, in the target crossing case.

Linear Distributed Passive Target Tracking Filter for Cooperative Multiple UAVs (다중 UAV 협업을 위한 선형 분산 피동 표적추적 필터 설계)

  • Lee, Yunha;Kim, Chan-Young;Ra, Won-Sang;Whang, Ick-Ho
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.67 no.2
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    • pp.314-324
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    • 2018
  • This paper proposes a linear distributed target tracking filter for multiple unmanned aerial vehicles(UAVs) sharing their passive sensor measurements through communication channels. Different from the conventional nonlinear filtering schemes, the distributed passive target tracking problem is newly formulated within the framework of a linear robust state estimation theory incorporated with a linear uncertain measurement equation including the coordinate transform uncertainty. To effectively cope with the performance degradation due to the coordinate transform uncertainty, a linear consistent robust Kalman filter(CRKF) theory is devised and applied for designing a distributed passive target tracking filter. Through the simulations for typical UAV surveillance mission, the superior performance of the proposed method over the existing schemes of distributed passive target tracking are demonstrated.

Performance analysis of automatic target tracking algorithms based on analysis of sea trial data in diver detection sonar (수영자 탐지 소나에서의 해상실험 데이터 분석 기반 자동 표적 추적 알고리즘 성능 분석)

  • Lee, Hae-Ho;Kwon, Sung-Chur;Oh, Won-Tcheon;Shin, Kee-Cheol
    • The Journal of the Acoustical Society of Korea
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    • v.38 no.4
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    • pp.415-426
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    • 2019
  • In this paper, we discussed automatic target tracking algorithms for diver detection sonar that observes penetration forces of coastal military installations and major infrastructures. First of all, we analyzed sea trial data in diver detection sonar and composed automatic target tracking algorithms based on track existence probability as track quality measure in clutter environment. In particular, these are presented track management algorithms which include track initiation, confirmation, termination, merging and target tracking algorithms which include single target tracking IPDAF (Integrated Probabilistic Data Association Filter) and multitarget tracking LMIPDAF (Linear Multi-target Integrated Probabilistic Data Association Filter). And we analyzed performances of automatic target tracking algorithms using sea trial data and monte carlo simulation data.

Study on the Improved Target Tracking for the Collaborative Control of the UAV-UGV (UAV-UGV의 협업제어를 위한 향상된 Target Tracking에 관한 연구)

  • Choi, Jae-Young;Kim, Sung-Gaun
    • Journal of Institute of Control, Robotics and Systems
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    • v.19 no.5
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    • pp.450-456
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    • 2013
  • This paper suggests the target tracking method improved for the collaboration of the quad rotor type UAV (Unmanned Aerial Vehicle) and omnidirectional Unmanned Ground Vehicle. If UAV shakes or UGV moves rapidly, the existing method generates a phenomenon that the tracking object loses the tracking target. To solve the problems, we propose an algorithm that can track continually when they lose the target. The proposed algorithm stores the vector of the landmark. And if the target was lost, the control signal was inputted so that the landmark could move continuously to the direction running out. Prior to the experiment, Proportional and integral control were used in 4 motors in order to calibrate the Heading value of the omnidirectional mobile robot. The landmark of UGV was recognized as the camera adhered to UAV and the target was traced through the proportional-integral-derivative control. Finally, the performance of the target tracking controller and proposed algorithm was evaluated through the experiment.