Message Passing Algorithms for Scalable Multitarget Tracking

Situation-aware technologies enabled by multitarget tracking will lead to new services and applications in fields such as autonomous driving, indoor localization, robotic networks, and crowd counting. In this tutorial paper, we advocate a recently proposed paradigm for scalable multitarget tracking...

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Vydáno v:	Proceedings of the IEEE Ročník 106; číslo 2; s. 221 - 259
Hlavní autoři:	Meyer, Florian, Kropfreiter, Thomas, Williams, Jason L., Lau, Roslyn, Hlawatsch, Franz, Braca, Paolo, Win, Moe Z.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.02.2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Biomedical measurement Clutter Complexity Computer simulation Data association data fusion factor graph Mathematical models Message passing Multiple target tracking multitarget tracking Numerical methods Radar tracking Real time operation Sensors sum–product algorithm Target tracking Time measurement
ISSN:	0018-9219, 1558-2256
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Abstract	Situation-aware technologies enabled by multitarget tracking will lead to new services and applications in fields such as autonomous driving, indoor localization, robotic networks, and crowd counting. In this tutorial paper, we advocate a recently proposed paradigm for scalable multitarget tracking that is based on message passing or, more concretely, the loopy sum-product algorithm. This approach has advantages regarding estimation accuracy, computational complexity, and implementation flexibility. Most importantly, it provides a highly effective, efficient, and scalable solution to the probabilistic data association problem, a major challenge in multitarget tracking. This fact makes it attractive for emerging applications requiring real-time operation on resource-limited devices. In addition, the message passing approach is intuitively appealing and suited to nonlinear and non-Gaussian models. We present message-passing-based multitarget tracking methods for single-sensor and multiple-sensor scenarios, and for a known and unknown number of targets. The presented methods can cope with clutter, missed detections, and an unknown association between targets and measurements. We also discuss the integration of message-passing-based probabilistic data association into existing multitarget tracking methods. The superior performance, low complexity, and attractive scaling properties of the presented methods are verified numerically. In addition to simulated data, we use measured data captured by two radar stations with overlapping fields-of-view observing a large number of targets simultaneously.
AbstractList	Situation-aware technologies enabled by multitarget tracking will lead to new services and applications in fields such as autonomous driving, indoor localization, robotic networks, and crowd counting. In this tutorial paper, we advocate a recently proposed paradigm for scalable multitarget tracking that is based on message passing or, more concretely, the loopy sum-product algorithm. This approach has advantages regarding estimation accuracy, computational complexity, and implementation flexibility. Most importantly, it provides a highly effective, efficient, and scalable solution to the probabilistic data association problem, a major challenge in multitarget tracking. This fact makes it attractive for emerging applications requiring real-time operation on resource-limited devices. In addition, the message passing approach is intuitively appealing and suited to nonlinear and non-Gaussian models. We present message-passing-based multitarget tracking methods for single-sensor and multiple-sensor scenarios, and for a known and unknown number of targets. The presented methods can cope with clutter, missed detections, and an unknown association between targets and measurements. We also discuss the integration of message-passing-based probabilistic data association into existing multitarget tracking methods. The superior performance, low complexity, and attractive scaling properties of the presented methods are verified numerically. In addition to simulated data, we use measured data captured by two radar stations with overlapping fields-of-view observing a large number of targets simultaneously.
Author	Lau, Roslyn Hlawatsch, Franz Williams, Jason L. Win, Moe Z. Meyer, Florian Kropfreiter, Thomas Braca, Paolo
Author_xml	– sequence: 1 givenname: Florian surname: Meyer fullname: Meyer, Florian email: fmeyer@mit.edu organization: Laboratory for Information and Decision Systems, Massachusetts Institute of Technology, Cambridge, MA, USA – sequence: 2 givenname: Thomas surname: Kropfreiter fullname: Kropfreiter, Thomas email: thomas.kropfreiter@tuwien.ac.at organization: Institute of Telecommunications, TU Wien, Vienna, Austria – sequence: 3 givenname: Jason L. surname: Williams fullname: Williams, Jason L. email: jason.williams@dst.defence.gov.au organization: National Security, Intelligence, Surveillance and Reconnaissance Division, Defence Science and Technology Group, Edinburgh, SA, Australia – sequence: 4 givenname: Roslyn surname: Lau fullname: Lau, Roslyn email: roslyn.lau@dst.defence.gov.au organization: Maritime Division, Defence Science and Technology Group, Edinburgh, SA, Australia – sequence: 5 givenname: Franz surname: Hlawatsch fullname: Hlawatsch, Franz email: franz.hlawatsch@tuwien.ac.at organization: Institute of Telecommunications, TU Wien, Vienna, Austria – sequence: 6 givenname: Paolo surname: Braca fullname: Braca, Paolo email: paolo.braca@cmre.nato.int organization: NATO Centre for Maritime Research and Experimentation (CMRE), La Spezia, Italy – sequence: 7 givenname: Moe Z. surname: Win fullname: Win, Moe Z. email: moewin@mit.edu organization: Laboratory for Information and Decision Systems, Massachusetts Institute of Technology, Cambridge, MA, USA
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Snippet	Situation-aware technologies enabled by multitarget tracking will lead to new services and applications in fields such as autonomous driving, indoor...
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SubjectTerms	Biomedical measurement Clutter Complexity Computer simulation Data association data fusion factor graph Mathematical models Message passing Multiple target tracking multitarget tracking Numerical methods Radar tracking Real time operation Sensors sum–product algorithm Target tracking Time measurement
Title	Message Passing Algorithms for Scalable Multitarget Tracking
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