• Title/Summary/Keyword: Multi-Sensor Single-Target tracking

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On using Bayes Risk for Data Association to Improve Single-Target Multi-Sensor Tracking in Clutter (Bayes Risk를 이용한 False Alarm이 존재하는 환경에서의 단일 표적-다중센서 추적 알고리즘)

  • 김경택;최대범;안병하;고한석
    • Proceedings of the IEEK Conference
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    • 2001.06d
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    • pp.159-162
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    • 2001
  • In this Paper, a new multi-sensor single-target tracking method in cluttered environment is proposed. Unlike the established methods such as probabilistic data association filter (PDAF), the proposed method intends to reflect the information in detection phase into parameters in tracking so as to reduce uncertainty due to clutter. This is achieved by first modifying the Bayes risk in Bayesian detection criterion to incorporate the likelihood of measurements from multiple sensors. The final estimate is then computed by taking a linear combination of the likelihood and the estimate of measurements. We develop the procedure and discuss the results from representative simulations.

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Multi-sensor Single Maneuvering Target Tracking in Clutter using AMMPF (클러터를 고려한 다중 센서 환경에서의 AMMPF를 이용한 기동 표적 추적 알고리즘 연구)

  • Kim Da-Sol;Song Taek-Lyul;Oh Won-Chun
    • Proceedings of the Acoustical Society of Korea Conference
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    • autumn
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    • pp.479-482
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    • 2004
  • In this article we consider a single maneuvering target Tracking algorithm in the presence of missing measurements and high clutter environments for multi-sensor target tracking problem. The tracking algorithm is based on the Particle filtering method to predict and update target states. Proposed is the AMM-PF(Auxiliary Multiple Model Particle Filter)[2] method for maneuvering target tracking to improve performance in track estimate and maintenance with a high level of uncertainty. The algorithm we propose is compared to the Extended Kalman Filter(EKF). A simulation study is included.

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Experimental Verification of Multi-Sensor Geolocation Algorithm using Sequential Kalman Filter (순차적 칼만 필터를 적용한 다중센서 위치추정 알고리즘 실험적 검증)

  • Lee, Seongheon;Kim, Youngjoo;Bang, Hyochoong
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.1
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    • pp.7-13
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    • 2015
  • Unmanned air vehicles (UAVs) are getting popular not only as a private usage for the aerial photograph but military usage for the surveillance, reconnaissance and supply missions. For an UAV to successfully achieve these kind of missions, geolocation (localization) must be implied to track an interested target or fly by reference. In this research, we adopted multi-sensor fusion (MSF) algorithm to increase the accuracy of the geolocation and verified the algorithm using two multicopter UAVs. One UAV is equipped with an optical camera, and another UAV is equipped with an optical camera and a laser range finder. Throughout the experiment, we have obtained measurements about a fixed ground target and estimated the target position by a series of coordinate transformations and sequential Kalman filter. The result showed that the MSF has better performance in estimating target location than the case of using single sensor. Moreover, the experimental result implied that multi-sensor geolocation algorithm is able to have further improvements in localization accuracy and feasibility of other complicated applications such as moving target tracking and multiple target tracking.

Visual Tracking using Weighted Discriminative Correlation Filter

  • Song, Tae-Eun;Jang, Kyung-Hyun
    • Journal of the Korea Society of Computer and Information
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    • v.21 no.11
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    • pp.49-57
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    • 2016
  • In this paper, we propose the novel tracking method which uses the weighted discriminative correlation filter (DCF). We also propose the PSPR instead of conventional PSR as tracker performance evaluation method. The proposed tracking method uses multiple DCF to estimates the target position. In addition, our proposed method reflects more weights on the correlation response of the tracker which is expected to have more performance using PSPR. While existing multi-DCF-based tracker calculates the final correlation response by directly summing correlation responses from each tracker, the proposed method acquires the final correlation response by weighted combining of correlation responses from the selected trackers robust to given environment. Accordingly, the proposed method can provide high performance tracking in various and complex background compared to multi-DCF based tracker. Through a series of tracking experiments for various video data, the presented method showed better performance than a single feature-based tracker and also than a multi-DCF based tracker.

A Multi-target Tracking Algorithm for Application to Adaptive Cruise Control

  • Moon Il-ki;Yi Kyongsu;Cavency Derek;Hedrick J. Karl
    • Journal of Mechanical Science and Technology
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    • v.19 no.9
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    • pp.1742-1752
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    • 2005
  • This paper presents a Multiple Target Tracking (MTT) Adaptive Cruise Control (ACC) system which consists of three parts; a multi-model-based multi-target state estimator, a primary vehicular target determination algorithm, and a single-target adaptive cruise control algorithm. Three motion models, which are validated using simulated and experimental data, are adopted to distinguish large lateral motions from longitudinally excited motions. The improvement in the state estimation performance when using three models is verified in target tracking simulations. However, the performance and safety benefits of a multi-model-based MTT-ACC system is investigated via simulations using real driving radar sensor data. The MTT-ACC system is tested under lane changing situations to examine how much the system performance is improved when multiple models are incorporated. Simulation results show system response that is more realistic and reflective of actual human driving behavior.

Multi-Vehicle Tracking Adaptive Cruise Control (다차량 추종 적응순항제어)

  • Moon Il ki;Yi Kyongsu
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.29 no.1 s.232
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    • pp.139-144
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    • 2005
  • A vehicle cruise control algorithm using an Interacting Multiple Model (IMM)-based Multi-Target Tracking (MTT) method has been presented in this paper. The vehicle cruise control algorithm consists of three parts; track estimator using IMM-Probabilistic Data Association Filter (PDAF), a primary target vehicle determination algorithm and a single-target adaptive cruise control algorithm. Three motion models; uniform motion, lane-change motion and acceleration motion. have been adopted to distinguish large lateral motions from longitudinal motions. The models have been validated using simulated and experimental data. The improvement in the state estimation performance when using three models is verified in target tracking simulations. The performance and safety benefits of a multi-model-based MTT-ACC system is investigated via simulations using real driving radar sensor data. These simulations show system response that is more realistic and reflective of actual human driving behavior.

Vehicle Cruise Control with a Multi-model Multi-target Tracking Algorithm (복합모델 다차량 추종 기법을 이용한 차량 주행 제어)

  • Moon, Il-Ki;Yi, Kyong-Su
    • Proceedings of the KSME Conference
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    • 2004.11a
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    • pp.696-701
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    • 2004
  • A vehicle cruise control algorithm using an Interacting Multiple Model (IMM)-based Multi-Target Tracking (MTT) method has been presented in this paper. The vehicle cruise control algorithm consists of three parts; track estimator using IMM-Probabilistic Data Association Filter (PDAF), a primary target vehicle determination algorithm and a single-target adaptive cruise control algorithm. Three motion models; uniform motion, lane-change motion and acceleration motion, have been adopted to distinguish large lateral motions from longitudinal motions. The models have been validated using simulated and experimental data. The improvement in the state estimation performance when using three models is verified in target tracking simulations. The performance and safety benefits of a multi-model-based MTT-ACC system is investigated via simulations using real driving radar sensor data. These simulations show system response that is more realistic and reflective of actual human driving behavior.

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The Performance Analysis of IMM-MPDA Filter in Multi-lag Out of Sequence Measurement Environment (Multi-lag Out of Sequence Measurement 환경에서의 IMM-MPDA 필터 성능 분석)

  • Seo, Il-Hwan;Song, Taek-Lyul
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.56 no.8
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    • pp.1476-1483
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    • 2007
  • In a multi-sensor target tracking systems, the local sensors have the role of tracking the target and transferring the measurements to the fusion center. The measurements from the same target can arrive out of sequence called, the out-of-sequence measurements(OOSMs). The OOSM can arise in a form of single-lag or multi-lag throughout the transfer at the fusion center. The recursive retrodiction step was proposed to update the current state estimates with the multi-lag OOSM from the several previous papers. The real world has the possible situations that the maneuvering target informations can arrive at the fusion center with the random clutter in the possible OOSMs. In this paper, we incorporate the IMM-MPDA(Interacting Multiple Model - Most Probable Data Association) into the multi-lag OOSM update. The performance of the IMM-MPDA filter with multi-lag OOSM update is analyzed for the various clutter densities, OOSM lag numbers, and target maneuvering indexes. Simulation results show that IMM-MPDA is sufficient to be used in out of sequence environment and it is necessary to correct the current state estimates with OOSM except a very old OOSM.

A Study of Image Target Tracking Using ITS in an Occluding Environment (표적이 일시적으로 가려지는 환경에서 ITS 기법을 이용한 영상 표적 추적 알고리듬 연구)

  • Kim, Yong;Song, Taek-Lyul
    • Journal of Institute of Control, Robotics and Systems
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    • v.19 no.4
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    • pp.306-314
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    • 2013
  • Automatic tracking in cluttered environment requires the initiation and maintenance of tracks, and track existence probability of true track is kept by Markov Chain Two model of target existence propagation. Unlike Markov Chain One model for target existence propagation, Markov Chain Two model is made up three hypotheses about target existence event which are that the target exist and is detectable, the target exists and is non-detectable through occlusion, and the target does not exist and is non-detectable according to non-existing target. In this paper we present multi-scan single target tracking algorithm based on the target existence, which call the Integrated Track Splitting algorithm with Markov Chain Two model in imaging sensor.

A Survey on Communication Protocols for Wireless Sensor Networks

  • Jang, Ingook;Pyeon, Dohoo;Kim, Sunwoo;Yoon, Hyunsoo
    • Journal of Computing Science and Engineering
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    • v.7 no.4
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    • pp.231-241
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    • 2013
  • Improvements in wireless sensor network (WSN) technology have resulted in a large number of applications. WSNs have been mainly used for monitoring applications, but they are also applicable to target tracking, health care, and monitoring with multimedia data. Nodes are generally deployed in environments where the exhausted batteries of sensor nodes are difficult to charge or replace. The primary goal of communication protocols in WSNs is to maximize energy efficiency in order to prolong network lifetime. In this paper, various medium access control (MAC) protocols for synchronous/asynchronous and single/multi-channel WSNs are investigated. Single-channel MAC protocols are categorized into synchronous and asynchronous approaches, and the advantages and disadvantages of each protocol are presented. The different features required in multi-channel WSNs compared to single-channel WSNs are also investigated, and surveys on multi-channel MAC protocols proposed for WSNs are provided. Then, existing broadcast schemes in such MAC protocols and efficient multi-hop broadcast protocols proposed for WSNs are provided. The limitations and challenges in many communication protocols according to this survey are pointed out, which will help future researches on the design of communication protocols for WSNs.