Literatura académica sobre el tema "Multiple target tracking algorithms"
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Artículos de revistas sobre el tema "Multiple target tracking algorithms"
Wu, Jin, Changqing Cao, Yuedong Zhou, Xiaodong Zeng, Zhejun Feng, Qifan Wu y Ziqiang Huang. "Multiple Ship Tracking in Remote Sensing Images Using Deep Learning". Remote Sensing 13, n.º 18 (9 de septiembre de 2021): 3601. http://dx.doi.org/10.3390/rs13183601.
Texto completoDing, Ma. "Tracking Target Identification Model Based on Multiple Algorithms". Applied Mechanics and Materials 539 (julio de 2014): 106–12. http://dx.doi.org/10.4028/www.scientific.net/amm.539.106.
Texto completoLing, Jiankun. "Target Tracking Using Kalman Filter Based Algorithms". Journal of Physics: Conference Series 2078, n.º 1 (1 de noviembre de 2021): 012020. http://dx.doi.org/10.1088/1742-6596/2078/1/012020.
Texto completoHoang, Le Minh, Aleksandr A. Konovalov y Dao Van Luc. "Tracking of Maneuvering Targets Using a Variable Structure Multiple Model Algorithm". Journal of the Russian Universities. Radioelectronics 26, n.º 3 (6 de julio de 2023): 77–89. http://dx.doi.org/10.32603/1993-8985-2023-26-3-77-89.
Texto completoYuan, Xianghui, Feng Lian y Chongzhao Han. "Models and Algorithms for Tracking Target with Coordinated Turn Motion". Mathematical Problems in Engineering 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/649276.
Texto completoLei Shundong. "Tracking Target Identification Model Based on Multiple Algorithms". International Journal of Digital Content Technology and its Applications 7, n.º 3 (15 de febrero de 2013): 274–83. http://dx.doi.org/10.4156/jdcta.vol7.issue3.35.
Texto completoMemon, Sufyan, Myungun Kim y Hungsun Son. "Tracking and Estimation of Multiple Cross-Over Targets in Clutter". Sensors 19, n.º 3 (12 de febrero de 2019): 741. http://dx.doi.org/10.3390/s19030741.
Texto completoMemon, Sufyan Ali, Hungsun Son, Wan-Gu Kim, Abdul Manan Khan, Mohsin Shahzad y Uzair Khan. "Tracking Multiple Unmanned Aerial Vehicles through Occlusion in Low-Altitude Airspace". Drones 7, n.º 4 (30 de marzo de 2023): 241. http://dx.doi.org/10.3390/drones7040241.
Texto completoChen, Yuntao, Bin Wu, guangzhi Luo, xiaoyan Chen y junlin Liu. "Multi-target tracking algorithm based on YOLO+DeepSORT". Journal of Physics: Conference Series 2414, n.º 1 (1 de diciembre de 2022): 012018. http://dx.doi.org/10.1088/1742-6596/2414/1/012018.
Texto completoSong, Xiyu, Nae Zheng y Ting Bai. "Resource Allocation Schemes for Multiple Targets Tracking in Distributed MIMO Radar Systems". International Journal of Antennas and Propagation 2017 (2017): 1–12. http://dx.doi.org/10.1155/2017/7241281.
Texto completoTesis sobre el tema "Multiple target tracking algorithms"
Pitre, Ryan. "A Comparison of Multiple-Model Target Tracking Algorithms". ScholarWorks@UNO, 2004. http://louisdl.louislibraries.org/u?/NOD,168.
Texto completoTitle from electronic submission form. "A thesis ... in partial fulfillment of the requirements for the degree of Master of Science in the Department of Electrical Engineering."--Thesis t.p. Vita. Includes bibliographical references.
Vestin, Albin y Gustav Strandberg. "Evaluation of Target Tracking Using Multiple Sensors and Non-Causal Algorithms". Thesis, Linköpings universitet, Reglerteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-160020.
Texto completoNaeem, Asad. "Single and multiple target tracking via hybrid mean shift/particle filter algorithms". Thesis, University of Nottingham, 2010. http://eprints.nottingham.ac.uk/12699/.
Texto completoHadzagic, Melita. "Comparative analysis of the IMM-JVC and the IMM-JPDA algorithms for multiple-target tracking". Thesis, McGill University, 2001. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=32959.
Texto completoThis thesis presents a comparative study of two assignment alternatives, namely the NC (unique association of a measurement to an existing track) and JPDA (nonunique association of a measurement to an existing track) algorithms. These assignment strategies were combined with an Interacting Multiple Model (IMM) positional estimator, which superiority over the other single scan algorithms has been largely documented. The respective tracking performance of the IMM-JVC and EV1M-JPDAF algorithms for multiple target tracking has been evaluated. After a detailed description of the IMM-JVC and IMM-JPDAF formalisms, and the IMM-JPDAF implementation issues, an analysis of the results of NC association compared to JPDA association is presented. Simulation results obtained on two scenarios involving two closely maneuvering aircraft confirm the superiority of the IMM-JVC.
Munir, Arshed. "Manoeuvring target tracking using different forms of the interacting multiple model algorithm". Thesis, University of Sussex, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.240430.
Texto completoAlat, Gokcen. "A Variable Structure - Autonomous - Interacting Multiple Model Ground Target Tracking Algorithm In Dense Clutter". Phd thesis, METU, 2013. http://etd.lib.metu.edu.tr/upload/12615512/index.pdf.
Texto completoincorporate a priori information such as topographic constraints, road maps as much as possible
use enhanced gating techniques to minimize the eect of clutter
develop methods against stop-move motion and hide motion of the target
tackle on-road/o-road transitions and junction crossings
establish measures against non-detections caused by environment. The tracker structure is derived using a composite state estimation set-up that incorporate multi models and MAP and MMSE estimations. The root mean square position and velocity error performances of the VS-A-IMM algorithm are compared with respect to the baseline IMM and the VS-IMM methods found in the literature. It is observed that the newly developed VS-A-IMM algorithm performs better than the baseline methods in realistic conditions such as on-road/o-road transitions, tunnels, stops, junction crossings, non-detections.
Ege, Emre. "A Comparative Study Of Tracking Algorithms In Underwater Environment Using Sonar Simulation". Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/2/12608866/index.pdf.
Texto completos true state based on a time history of noisy sensor observations. In real life, the sensor data may include substantial noise. This noise can render the raw sensor data unsuitable to be used directly. Instead, we must filter the noise, preferably in an optimal manner. For land, air and surface marine vehicles, very successful filtering methods are developed. However, because of the significant differences in the underwater propagation environment and the associated differences in the corresponding sensors, the successful use of similar principles and techniques in an underwater scenario is still an active topic of research. A comparative study of the effects of the underwater environment on a number of tracking algorithms is the focus of the present thesis. The tracking algorithms inspected are: the Kalman Filter, the Extended Kalman Filter and the Particle Filter. We also investigate in particular the IMM extension to KF and EKF filters. These algorithms are tested under several underwater environment scenarios.
Niedfeldt, Peter C. "Recursive-RANSAC: A Novel Algorithm for Tracking Multiple Targets in Clutter". BYU ScholarsArchive, 2014. https://scholarsarchive.byu.edu/etd/4195.
Texto completoDay, Nathalie Anna. "Significant measurements of a multiple target tracking system utilizing munkre's algorithm as a correlation scheme". Master's thesis, University of Central Florida, 1988. http://digital.library.ucf.edu/cdm/ref/collection/RTD/id/72470.
Texto completoThis thesis presents and discusses the principles of multiple target tracking. A simulation written in Turbo Pascal provides the results of using a modified version of Munkre's algorithm for correlating targets with observations. The number and types of measurments necessary to obtain acceptable results are examined. The measurements under scrutiny are range, range rate, azimuth angle and elevation angle. A track-while-scan system is assumed and the nearest neighbor correlation scheme as well as rectangular gating are used for association.
M.S.
Masters
Engineering
Engineering
79 p.
vi, 79 leaves, bound : ill. ; 28 cm.
Sahin, Mehmet Alper. "Performance Optimization Of Monopulse Tracking Radar". Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/2/12605364/index.pdf.
Texto completoLibros sobre el tema "Multiple target tracking algorithms"
Multiple-target tracking with radar applications. Dedham, MA: Artech House, 1986.
Buscar texto completoNassimizadeh, Hamid. Data association and multiple target tracking. Birmingham: University of Birmingham, 1992.
Buscar texto completoDunham, Darin T. Tracking multiple targets in cluttered environments with the probabilistic multi-hypothesis tracking filter. Monterey, Calif: Naval Postgraduate School, 1997.
Buscar texto completoIEE Seminar on Target Tracking: Algorithms and Applications (2006 Birmingham, England). The IEE seminar on target tracking: algorithms and applications: 7-8 March 2006. London: Institution of Electrical Engineers, 2006.
Buscar texto completoEngineers, Institution of Electrical y IEE Control & Automation Professional Network., eds. Target tracking 2004: Algorithms and applications, 23-24 March 2004, the University of Sussex, Brighton, UK. London: Institution of Electrical Engineers, 2004.
Buscar texto completoIEE Professional Network on Concepts for Automation & Control. International seminar: Target tracking, algorithms & applications : Tuesday, 16 October-Wednesday, 17 October 2001 : Conferentiehotel Drienerburght, University of Twente, Enschede, The Netherlands. London?]: Thales, 2001.
Buscar texto completoNicklas, Richard B. An application of a Kalman Filter Fixed Interval Smoothing Algorithm to underwater target tracking. Monterey, Calif: Naval Postgraduate School, 1989.
Buscar texto completoDubanov, Aleksandr. Computer simulation in pursuit problems. ru: Publishing Center RIOR, 2022. http://dx.doi.org/10.29039/02102-6.
Texto completoBayesian Multiple Target Tracking. Artech House Publishers, 2014.
Buscar texto completoStone, Lawrence D., Carl A. Barlow y Thomas L. Corwin. Bayesian Multiple Target Tracking (Artech House Radar Library). Artech House Publishers, 1999.
Buscar texto completoCapítulos de libros sobre el tema "Multiple target tracking algorithms"
Liu, Weifeng, Zhong Chai y Chenglin Wen. "A Multiple Shape-Target Tracking Algorithm by Using MCMC Sampling". En Lecture Notes in Computer Science, 563–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31020-1_67.
Texto completoSong, Liping y Hongbing Ji. "Least Squares Interacting Multiple Model Algorithm for Passive Multi-sensor Maneuvering Target Tracking". En Lecture Notes in Computer Science, 479–82. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11881070_66.
Texto completoHoh, Baik y Marco Gruteser. "Multiple Target Tracking". En Encyclopedia of GIS, 764. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-35973-1_850.
Texto completoHoh, Baik y Marco Gruteser. "Multiple Target Tracking". En Encyclopedia of GIS, 1–2. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-23519-6_850-2.
Texto completoPhalke, Kiran y Ravindra Hegadi. "Multiple Target Tracking". En Advances in Intelligent Systems and Computing, 579–85. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8633-5_58.
Texto completoHoh, Baik y Marco Gruteser. "Multiple Target Tracking". En Encyclopedia of GIS, 1412–13. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-17885-1_850.
Texto completoStreit, Roy L. "Multiple Target Tracking". En Poisson Point Processes, 147–78. Boston, MA: Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-6923-1_6.
Texto completoKyriakides, Ioannis, Darryl Morrell y Antonia Papandreou-Suppappola. "Multiple Target Tracking". En Adaptive High-Resolution Sensor Waveform Design for Tracking, 41–62. Cham: Springer International Publishing, 2011. http://dx.doi.org/10.1007/978-3-031-01515-1_5.
Texto completoWu, Weihua, Hemin Sun, Mao Zheng y Weiping Huang. "Single Target Tracking Algorithms". En Target Tracking with Random Finite Sets, 41–59. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-9815-7_2.
Texto completoWang, Xiaoyu, Gang Hua y Tony X. Han. "Discriminative Multiple Target Tracking". En Machine Learning for Vision-Based Motion Analysis, 145–58. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-057-1_6.
Texto completoActas de conferencias sobre el tema "Multiple target tracking algorithms"
Noyes, S. P. "Control of false track rate using multiple hypothesis confirmation". En Target Tracking 2004: Algorithms and Applications. IEE, 2004. http://dx.doi.org/10.1049/ic:20040062.
Texto completoArj, M. "Problems of multiple-target tracking in vision-based applications". En Target Tracking 2004: Algorithms and Applications. IEE, 2004. http://dx.doi.org/10.1049/ic:20040064.
Texto completoHue, C. "Tracking multiple targets with particle filtering using multiple receivers". En IEE International Seminar Target Tracking: Algorithms and Applications. IEE, 2001. http://dx.doi.org/10.1049/ic:20010232.
Texto completoAllam, S. "Multiple model tracking with intermittent mode observations". En IEE Colloquium. Target Tracking: Algorithms and Applications. IEE, 1999. http://dx.doi.org/10.1049/ic:19990511.
Texto completoVahdati-khajeh, E. "Tracking the maneuvering targets using multiple scan joint probabilistic data association algorithm". En Target Tracking 2004: Algorithms and Applications. IEE, 2004. http://dx.doi.org/10.1049/ic:20040049.
Texto completoKarlsson, R. "Monte Carlo data association for multiple target tracking". En IEE International Seminar Target Tracking: Algorithms and Applications. IEE, 2001. http://dx.doi.org/10.1049/ic:20010239.
Texto completoClark, D., I. T. Ruiz, Y. Petillot y J. Bell. "Multiple target tracking and data association in sonar images". En IEE Seminar on Target Tracking: Algorithms and Applications. IEE, 2006. http://dx.doi.org/10.1049/ic:20060567.
Texto completoJudge, I. "RADIX - a solution to multiple sensor data fusion". En IEE International Seminar Target Tracking: Algorithms and Applications. IEE, 2001. http://dx.doi.org/10.1049/ic:20010231.
Texto completoBoers, Y. "Multiple model filters for systems with possibly erroneous measurements". En IEE International Seminar Target Tracking: Algorithms and Applications. IEE, 2001. http://dx.doi.org/10.1049/ic:20010236.
Texto completoJaward, M. H., L. Mihaylova, N. Canagarajah y D. Bull. "A data association algorithm for multiple object tracking in video sequences". En IEE Seminar on Target Tracking: Algorithms and Applications. IEE, 2006. http://dx.doi.org/10.1049/ic:20060565.
Texto completoInformes sobre el tema "Multiple target tracking algorithms"
Bose, N. K. Multiple Target Tracking: Fast Algorithm for Data Association and State Estimation. Fort Belvoir, VA: Defense Technical Information Center, febrero de 1995. http://dx.doi.org/10.21236/ada300870.
Texto completoKashyap, Rangasami L. Multiple Target Detection and Tracking. Fort Belvoir, VA: Defense Technical Information Center, febrero de 1999. http://dx.doi.org/10.21236/ada363925.
Texto completoLambert, Hendrick C. y Dana Sinno. Bioinspired Resource Management for Multiple-Sensor Target Tracking Systems. Fort Belvoir, VA: Defense Technical Information Center, junio de 2011. http://dx.doi.org/10.21236/ada544935.
Texto completoKamalvand, Ahmad, Paul MacDonald y Thai-Duong Tran. Factored Sampling Tracking: Comparison of the Kalman and the Condensation Algorithms for Missile Tracking in a Defense Target Environment. Fort Belvoir, VA: Defense Technical Information Center, diciembre de 2004. http://dx.doi.org/10.21236/ada430271.
Texto completoTarko, Andrew P., Mario A. Romero, Vamsi Krishna Bandaru y Cristhian Lizarazo. TScan–Stationary LiDAR for Traffic and Safety Applications: Vehicle Interpretation and Tracking. Purdue University, 2022. http://dx.doi.org/10.5703/1288284317402.
Texto completoBurks, Thomas F., Victor Alchanatis y Warren Dixon. Enhancement of Sensing Technologies for Selective Tree Fruit Identification and Targeting in Robotic Harvesting Systems. United States Department of Agriculture, octubre de 2009. http://dx.doi.org/10.32747/2009.7591739.bard.
Texto completoDaudelin, Francois, Lina Taing, Lucy Chen, Claudia Abreu Lopes, Adeniyi Francis Fagbamigbe y Hamid Mehmood. Mapping WASH-related disease risk: A review of risk concepts and methods. United Nations University Institute for Water, Environment and Health, diciembre de 2021. http://dx.doi.org/10.53328/uxuo4751.
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