Abstract
This paper addresses track management for multiple target tracking (MTT) with a sensor network. Track management is needed for track generation and extinction when the targets set is unknown. Based on a consensus-based fusion algorithm, we develope a MTT algorithm that includes the measurement-to-track association (M2TA) and track management. It can be effectively applied even when the sensor detection range is limited and the field-of-view (FOV)s of each sensor are different. Numerical examples are presented in a multi-sensor multi-target scenario to verify that the proposed algorithm works properly in various network structures and clutter environments.
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Olfati-Saber, R.: Distributed Kalman filtering for sensor networks. In: 2007 46th IEEE Conference on Decision and Control, pp. 5492–5498. IEEE (2007)
Wang, Z., Gu, D.: Cooperative target tracking control of multiple robots. IEEE Trans. Ind. Electron. 59(8), 3232–3240 (2012)
Zhu, S., Chen, C., Li, W., Yang, B., Guan, X.: Distributed optimal consensus filter for target tracking in heterogeneous sensor networks. IEEE Trans. Cybern. 43(6), 1963–1976 (2013)
Olfati-Saber, R., Jalalkamali, P.: Collaborative target tracking using distributed Kalman filtering on mobile sensor networks. In: 2011 American Control Conference (ACC), pp. 1100–1105. IEEE (2011)
Zhou, Z., Fang, H., Hong, Y.: Distributed estimation for moving target based on state-consensus strategy. IEEE Trans. Autom. Control 58(8), 2096–2101 (2013)
Sandell, N.F., Olfati-Saber, R.: Distributed data association for multi-target tracking in sensor networks. In: 47th IEEE Conference on Decision and Control, CDC 2008, pp. 1085–1090. IEEE (2008)
Blackman, S.S.: Multiple-Target Tracking with Radar Applications, 463 p. Artech House Inc., Dedham (1986)
Bar-Shalom, Y., Willett, P.K., Tian, X.: Tracking and Data Fusion. YBS Publishing, Storrs (2011)
Bar-Shalom, Y., Li, X.R.: Multitarget-Multisensor Tracking: Principles and Techniques, vol. 19. YBS, London (1995)
Musicki, D., Evans, R.: Joint integrated probabilistic data association: JIPDA. IEEE Trans. Aerosp. Electron. Syst. 40(3), 1093–1099 (2004)
Blom, H.A., Bloem, E.A.: Probabilistic data association avoiding track coalescence. IEEE Trans. Autom. Control 45(2), 247–259 (2000)
Musicki, D., Evans, R.J.: Multiscan multitarget tracking in clutter with integrated track splitting filter. IEEE Trans. Aerosp. Electron. Syst. 45(4), 1432–1447 (2009)
Acknowledgements
This work was supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIT) (No. 20150002130042002, Development of High Reliable Communications and Security SW for Various Unmanned Vehicles).
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Lee, WC., Choi, HL. (2019). Track Management for Distributed Multi-target Tracking in Sensor Network. In: Kim, JH., Myung, H., Lee, SM. (eds) Robot Intelligence Technology and Applications. RiTA 2018. Communications in Computer and Information Science, vol 1015. Springer, Singapore. https://doi.org/10.1007/978-981-13-7780-8_13
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DOI: https://doi.org/10.1007/978-981-13-7780-8_13
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