• 제목/요약/키워드: Multiple vehicle tracking

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Beam Tracking Technique for Communication with Multiple Unmanned Aircraft Vehicles(UAVs) (다중 무인 항공기 통신을 위한 빔 추적 기법)

  • Maeng, Sung Joon;Park, Haein;Cho, Yong-Soo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • 제41권11호
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    • pp.1539-1548
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    • 2016
  • Beamforming technique at the ground station is known to be effective in obtaining coverage extension or SNR gain for communication with unmanned aerial vehicle (UAV). When a UAV moves, periodic beam tracking is necessary to maintain beam gain. In order to track beams for multiple UAVs, the ground station needs to receive different preamble sequences from multiple UAVs. In this paper, a preamble sequence design technique is proposed for beam tracking in a GMSK-based communication system with multiple UAVs. Hadamard sequence is considered for the design of preamble sequence due to its ideal cross-correlation property. A preamble sequence appropriate for a GMSK communication system with multiple UAVs is proposed after analyzing the properties of received signal in a GMSK system with the input of Hadamard sequence.

Vehicle Tracking using Sequential Monte Carlo Filter (순차적인 몬테카를로 필터를 사용한 차량 추적)

  • Lee, Won-Ju;Yun, Chang-Yong;Kim, Eun-Tae;Park, Min-Yong
    • Proceedings of the KIEE Conference
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    • 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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    • pp.434-436
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    • 2006
  • In a visual driver-assistance system, separating moving objects from fixed objects are an important problem to maintain multiple hypothesis for the state. Color and edge-based tracker can often be "distracted" causing them to track the wrong object. Many researchers have dealt with this problem by using multiple features, as it is unlikely that all will be distracted at the same time. In this paper, we improve the accuracy and robustness of real-time tracking by combining a color histogram feature with a brightness of Optical Flow-based feature under a Sequential Monte Carlo framework. And it is also excepted from Tracking as time goes on, reducing density by Adaptive Particles Number in case of the fixed object. This new framework makes two main contributions. The one is about the prediction framework which separating moving objects from fixed objects and the other is about measurement framework to get a information from the visual data under a partial occlusion.

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Tracking Performance Enhancement of Space Launch Vehicle Based on Adaptive Kalman Filter (적응 칼만필터에 기반한 우주발사체 추적 성능 개선)

  • Han, Yoo Soo;Song, Ha Ryong;Lee, In Soo
    • Journal of Korea Society of Industrial Information Systems
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    • 제22권5호
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    • pp.39-49
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    • 2017
  • A Space Launch Vehicle (SLV) for Launching Satellites Consists of Multi-stage Rockets for the Purpose of Efficient Flight and Accomplishes the Launch Mission through Flight Events such as Stage Separation, Engine Start and Stop. In this Process, the SLV is Supposed to Undergo the Processes of the Powered Flight Section in which the Engine Generates Thrust and the Ballistic Flight Section in which there is no Thrust Repeatedly. Because it is Difficult to Express these Flight Characteristics of the SLV as a Single Dynamics Model, much Research on Tracking Algorithms using Multiple Models has been Undertaken. In case of using the Multiple Model Tracking Algorithm, it is Expected to Improve the Tracking Performance of the SLV. However, it is Difficult to Select Proper Dynamics Models to be used and the Calculation Amount Increases due to the use of Multiple Models. In this Paper, we Propose a Method to Track the SLV with Diverse Flight Characteristics Efficiently by only Two Kalman Filters using Constant Acceleration Model and Adaptive Singer Model.

Simultaneous Tracking of Multiple Construction Workers Using Stereo-Vision (다수의 건설인력 위치 추적을 위한 스테레오 비전의 활용)

  • Lee, Yong-Ju;Park, Man-Woo
    • Journal of KIBIM
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    • 제7권1호
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    • pp.45-53
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    • 2017
  • Continuous research efforts have been made on acquiring location data on construction sites. As a result, GPS and RFID are increasingly employed on the site to track the location of equipment and materials. However, these systems are based on radio frequency technologies which require attaching tags on every target entity. Implementing the systems incurs time and costs for attaching/detaching/managing the tags or sensors. For this reason, efforts are currently being made to track construction entities using only cameras. Vision-based 3D tracking has been presented in a previous research work in which the location of construction manpower, vehicle, and materials were successfully tracked. However, the proposed system is still in its infancy and yet to be implemented on practical applications for two reasons. First, it does not involve entity matching across two views, and thus cannot be used for tracking multiple entities, simultaneously. Second, the use of a checker board in the camera calibration process entails a focus-related problem when the baseline is long and the target entities are located far from the cameras. This paper proposes a vision-based method to track multiple workers simultaneously. An entity matching procedure is added to acquire the matching pairs of the same entities across two views which is necessary for tracking multiple entities. Also, the proposed method simplified the calibration process by avoiding the use of a checkerboard, making it more adequate to the realistic deployment on construction sites.

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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    • 제19권9호
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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.

Object Feature Extraction and Matching for Effective Multiple Vehicles Tracking (효과적인 다중 차량 추적을 위한 객체 특징 추출 및 매칭)

  • Cho, Du-Hyung;Lee, Seok-Lyong
    • KIPS Transactions on Software and Data Engineering
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    • 제2권11호
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    • pp.789-794
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    • 2013
  • A vehicle tracking system makes it possible to induce the vehicle movement path for avoiding traffic congestion and to prevent traffic accidents in advance by recognizing traffic flow, monitoring vehicles, and detecting road accidents. To track the vehicles effectively, those which appear in a sequence of video frames need to identified by extracting the features of each object in the frames. Next, the identical vehicles over the continuous frames need to be recognized through the matching among the objects' feature values. In this paper, we identify objects by binarizing the difference image between a target and a referential image, and the labelling technique. As feature values, we use the center coordinate of the minimum bounding rectangle(MBR) of the identified object and the averages of 1D FFT(fast Fourier transform) coefficients with respect to the horizontal and vertical direction of the MBR. A vehicle is tracked in such a way that the pair of objects that have the highest similarity among objects in two continuous images are regarded as an identical object. The experimental result shows that the proposed method outperforms the existing methods that use geometrical features in tracking accuracy.

The Design and Implementation of a Multi-Session Processing Between RMA and RCP within a Vehicle Tracking System (차량 추적 시스템에서 RMA와 RCP 사이의 다중세션 설계 및 구현)

  • Jang, Chung Ryong;Lee, Yong Kwon;Lee, Dae Sik
    • Journal of Korea Society of Digital Industry and Information Management
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    • 제10권3호
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    • pp.127-141
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    • 2014
  • A Vehicle Tracking System consists of GPS tracking device which fits into the vehicle and captures the GPS location information at regular intervals to a central GIS server, and GIS tracking server providing three major responsibilities: receiving data from the GPS tracking unit, securely storing it, and serving this information on demand of the user. GPS based tracking systems supporting a multi-session processing among RMA, RM, and RCP can make a quick response to various services including other vehicle information between RSU and OBU on demand of the user. In this paper we design RSU lower layers and RCP applications in OBU for a multisession processing simulation and test message processing transactions among RMA-RM and RM-RCP. Furthermore, we implement the additional functions of handling access commands simultaneously on multiple service resources which are appropriate for the experimental testing conditions. In order to make a multi-session processing test, it reads 30 resource data,0002/0001 ~ 0002/0030, in total and then occurs 30 session data transmissions simultaneously. We insert a sequence number field into a special header of dummy data as a corresponding response to check that the messages are received correctly. Thus, we find that GIS service system with a multi-session processing is able to provide additional 30 services in a same speed of screen presentation loading while identifying the number of session processing of Web GIS service, the number of OBU service, and the speed of screen presentation loading by comparing a single session and a multi-session of GIS service system.

Multiple Object Detection and Tracking System robust to various Environment (환경변화에 강인한 다중 객체 탐지 및 추적 시스템)

  • Lee, Wu-Ju;Lee, Bae-Ho
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • 제46권6호
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    • pp.88-94
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    • 2009
  • This paper proposes real time object detection and tracking algorithm that can be applied to security and supervisory system field. A proposed system is devide into object detection phase and object tracking phase. In object detection, we suggest Adaptive background subtraction method and Adaptive block based model which are advanced motion detecting methods to detect exact object motions. In object tracking, we design a multiple vehicle tracking system based on Kalman filtering. As a result of experiment, motion of moving object can be estimated. the result of tracking multipul object was not lost and object was tracked correctly. Also, we obtained improved result from long range detection and tracking.

Autonomous Unmanned Vehicle based Self-locomotion Network for Tracking Targets in Group Mobility (그룹이동타겟 추적을 위한 무인차량기반의 자가이동 네트워크)

  • Tham, Nguyen Thi;Yoon, Seok-Hoon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • 제37권7C호
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    • pp.527-537
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    • 2012
  • In this paper, we propose unmanned vehicle based tracking network (UVTN) architecture and algorithms which employ multiple autonomous unmanned ground vehicles (AUGV) to efficiently follow targets in a group. The goal of UVTN is to maximize the service coverage while tracking target nodes for monitoring or providing the network access. In order to achieve this goal, UVTN performs periodic expansion and contraction which results in optimized redistribution of AUGV's in the network. Also, enhanced algorithms such as fast contraction and longest first are also discussed to improve the performance of UVTN in terms of the average coverage ratio and traveled distance. Simulation results show that the proposed UVTN and enhanced algorithms can effectively track the moving target and provide the consistent coverage.