Target Tracking

Course Information VT, 2019

Goal

After completing the course, the student should have the ability to describe and implement the most important concepts, methods, and algorithms used for target tracking. More specifically, after the course the student should:

• Understand and explain the fundamental principles of target tracking and target tracking systems.
• Know of and be able to use common target and sensor models in target tracking.
• Know how to deal with maneuvering targets, and sensor artifacts.
• Be able to implement a single target tracker.
• Understand the principles behind track management and be able to implement classic multi-target tracking methods.
• Know of modern approaches to the multi-target tracking problem.

Responsible

• Gustaf Hendeby, e-mail: gustaf.hendeby@liu.se
• Rickard Karlsson, e-mail: rickard.g.karlsson@liu.se

Prerequisites

The course assumes basic knowledge of probability theory and Bayesian estimation theory, eg, as taught in the Sensor Fusion course (TSRT14). The computer exercises will require some coding in MATLAB or similar tool. Interested students with basic knowledge of math from an engineering MSc program are expected to be able to pick up what they need on the way.

Literature:

Selected papers handed out during the course will be enough to follow the course.

For a fairly complete overview of the target tracking problem, methods, and algorithm collected at one place, the flowing books are good entry points.

• S. Blackman and R. Popoli. Design and Analysis of Modern Tracking Systems. Archtech House, Norwood, MA. 1999.
• Y. Bar-Shalom, P. K. Willett, and X. Tian. Tracking and Data Fusion: A Handbook of Algorithms. Yaakov Bar-Shalom Publishing. 2011.

Articles used throughout the course (this list will be updated throughout the course):

• Bar-Shalom, Y., Blackman, S. S., and Fitzgerald, R. J. "Dimensionless score function for multiple hypothesis tracking", in IEEE Transactions on Aerospace and Electronic Systems, 43(1):392-400, January 2007.
• Bar-Shalom, Y., Daum, F., and Huang, J. "The probabilistic data association filter", in IEEE Control Systems Magazine, 29(6):82-100, Nov. 2009.
• Bertsekas, D. "Auction algorithms".
• Blackman, S. "Multiple hypothesis tracking for multiple target tracking", in IEEE Transactions on Aerospace and Electronic Systems, 19(1):5-18, 2004.
• Blom, Henk A. P. and Bar-Shalom, Yaakov. "The Interacting Multiple Model Algorithm for Systems with Markovian Switching Coefficients", in IEEE Transactions on Automatic Control 33(8), August 1988.
• Boers, Y., Driessen, H., Torstensson, J., Trieb, M., Karlsson, R., and Gustafsson, F. "Track-before-detect algorithm for tracking extended targets", in IEE Proc on Radar Sonar Navigation, 153(4):345-351, Aug. 2006.
• Chong, C., Mori, S., and Reid, D. "Forty years of multiple hypothesis tracking - A review of key developments", in Proceedings of the 21st International Conference on Information Fusion, Cambridge, UK, July 2018.
• Fränken, D., Schmidt, M., and Ulmke, M. ""Spooky action at a distance" in the cardinalized probability hypothesis density filter", in IEEE Transactions on Aerospace and Electronic Systems 45(4):1657-1664, 2009.
• García-Fernández, Á. F., Williams, J. L., Granström, K., and Svensson, L. "Poisson multi-Bernoulli mixture filter: direct derivation and implementation", in IEEE Transactions on Aerospace and Electronic Systems 54(4), Aug. 2018.
• Granström, K., Baum, M., and Reuter, S. "Extended object tracking: Introduction, overview and applications", in Journal of Advances in Information Fusion 12(1), Dec. 2017.
• Granström, K., Svensson, L., Reuter, S. , Xia, Y., and Fatemi, M. "Likelihood-based data association for extended object tracking using sampling methods", in IEEE Transactions on Intelligent Vehicles, 3(1), Mar. 2018.
• Guerriero, M., Svensson, L., Svensson, D. and Willett, P. "Shooting two birds with two bullets: How to find minimum mean OSPA estimates", in Proceedings of the 13st International Conference on Information Fusion, Edinburgh, UK, July 2010.
• Li, X. Rong and Jilkov, Vesslin P. "Survey of Maneuvering Target Tracking. Part I: Dynamic Models", in IEEE Transactions on Aerospace and Electronic Systems 39(4), Oct 2003.
• Li, X. Rong and Jilkov, Vesslin P. "A Survey of Maneuvering Target Tracking. Part III: Measurement Models", in Proceedings of SPIE --- The International Society for Optical Engineering: Signal and Data Proceedings of Small Targets, Orlando, Juli 2001.
• Li, X. Rong and Jilkov, Vesslin P. "A Survey of Maneuvering Target Tracking. Part V: Multiple-Model Methods", in IEEE Transactions on Aerospace and Electronic Systems 41(4), Oct 2005.
• Mahler, R. P. S. "Multitarget Bayes Filtering via First-Order Multitarget Moments", in IEEE Transactions on Aerospace and Electronic Systems 39(4):1152-1178, 2003.
• Mahler, R. P. S. "PHD filters of higher order in target number", in Proceedings of SPIE 6235, May 2006.
• Mahler, R. P. S. and Zajic, T. "Multitarget filtering using a multitarget first-order moments", in Proceedings of SPIE 4380, Aug, 2001.
• Noack, B. Sijs, J. and Hanebeck, U. D. "Inverse covariance intersection: New insights and properties", in proceedings of 20st International Conference on Information Fusion, Xi'an, China, July 2017.
• Nygårds, J., Deleskog, V., and Hendeby, G. "Safe fusion compared to established distributed fusion methods", in Proceedings of IEEE lntemational Conference on Multisensor Fusion and Integration for Intelligent Systems, Baden-Baden, Germany, Sept. 2016.
• Olofsson, J. " On Multi-UAS Sea Ice Monitoring". Phd thesis, Norwegian University of Science and Technology, 2019.
• Reid. D. "An algorithm for tracking multiple targets", in IEEE Transactions on Automatic Control, 24(6):843-854, Dec. 1979.
• Reuter, S., Vo, B.-T., Vo,B.-N., and Dietmayer, K. "The Labeled Multi-Bernoulli Filter", in IEEE Transactions on Signal Processing 62(12):3246-3260, 2014.
• Singh, S. K., Premalatha, M., and Nair, G. "Ellipsoidal gating for an airborne track while scan radar", in Proceedings of the International Radar Conference, pages 334-339, Alexandria, VA, May 8-11 1995.
• Uhlmann, J. K. "Covariance consistency methods for fault-tolerant distributed data fusion" in Information Fusion 4(3):201-215, 2003.
• Vo, B.-N., Mallick, M., Bar-Shalom, Y., Coraluppi, S., Osborne III, R., Mahler, R., and Vo, B.-T. "Multitarget Tracking" in Wiley Encyclopedia of Electrical and Electronics Engineering, 2015.
• Vo, B.-N., Pasha, A., and Tuan, H. D. A Gaussian Mixture PHD Filter for Nonlinear Jump Markov Models" in Proceedings of the 45th IEEE Conference on Decision and Control, 2006.
• Vo, B.-N. , Vo, B.-T., and Phung, D. "Labeled Random Finite Sets and the Bayes Multi-Target Tracking Filter" in IEEE Transactions on Signal Processing 62(24):6554-6567, 2014.
• Vo, B.-T. and Vo, B.-N. "Labeled Random Finite Sets and Multi-Object Conjugate Priors" in IEEE Transactions on Signal Processing 61(13):3460-3475, 2013.
• Williams., "J. Marginal multi-bernoulli filters: RFS derivation of MHT, JIPDA, and association-based MeMBer", in IEEE Transactions on Aerospace and Electronic Systems, 51(3):1664-1687, July 2015.