Abstract
We consider tracking of a target with known elliptical nonlinear constraints on its motion dynamics. The state estimates are generated by sensors and sent over long-haul links to a remote fusion center for fusion. We show that the constraints can be projected onto the ellipse and hence incorporated into the estimation and fusion process. In particular, two methods based on (i) direct connection to the center, and (ii) shortest distance to the ellipse are discussed. A tracking example is used to illustrate the tracking performance using projection-based methods with various fusers in a lossy long-haul tracking environment.
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References
Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., Cayirci, E.: A survey on sensor networks. IEEE Commun. Mag. 40(8), 102–114 (2002)
Bar-Shalom, Y., Willett, P.K., Tian, X.: Tracking and Data Fusion: A Handbook of Algorithms. YBS Publishing, Storrs (2011)
Boord, W., Hoffman, J.B.: Air and Missile Defense Systems Engineering. CRC Press, Boca Raton (2016)
Borwein, J.M., Vanderwerff, J.D.: Convex Functions: Constructions, Characterizations and Counterexamples. Encyclopedia of Mathematics and its Applications. Cambridge University Press, New York (2010)
Duan, Z., Li, X.R.: Constrained target motion modeling - part I: straight line track. In: Proceedings of the 16th International Conference on Information Fusion (FUSION), Istanbul, Turkey, pp. 2161–2167, July 2013
Duan, Z., Li, X.R.: Constrained target motion modeling - part II: circular track. In: Proceedings of the 16th International Conference on Information Fusion (FUSION), Istanbul, Turkey, pp. 2153–2160, July 2013
Duan, Z., Li, X.R.: Multi-sensor estimation fusion for linear equality constrained dynamic systems. In: Proceedings of the 16th International Conference on Information Fusion (FUSION), Istanbul, Turkey, pp. 93–100, July 2013
Julier, S.J., Uhlmann, J.K.: A non-divergent estimation algorithm in the presence of unknown correlations. In: Proceedings of the American Control Conference, Albuquerque, NM, vol. 4, pp. 2369–2373, June 1997
Liu, Q., Rao, N.S.V.: Projection-based linear constrained estimation and fusion over long-haul links. In: Proceedings of the 12th International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI), Baden-Baden, Germany, pp. 365–370, September 2016
Liu, Q., Rao, N.S.V.: State estimation and fusion over long-haul links under linear constraints. In: Proceedings of the 19th International Conference on Information Fusion (FUSION), Heidelberg, Germany, pp. 1937–1944, July 2016
Liu, Q., Rao, N.S.V.: Projection-based circular constrained state estimation and fusion over long-haul links. In: Proceedings of the 20th International Conference on Information Fusion (FUSION), Xi’an, China, July 2017
Shmakov, S.L.: A universal method of solving quartic equations. Int. J. Pure Appl. Math. 71(2), 251–259 (2011)
Wang, Y., Li, X.R.: Distributed estimation fusion with unavailable cross-correlation. IEEE Trans. Aerosp. Electron. Syst. 48(1), 259–278 (2012)
Xu, L., Li, X.R., Duan, Z., Lan, J.: Modeling and state estimation for dynamic systems with linear equality constraints. IEEE Trans. Sig. Process. 61(11), 2927–2939 (2013)
Acknowledgments
This work was funded by the Mathematics of Complex, Distributed, Interconnected Systems Program, Office of Advanced Computing Research, U.S. Department of Energy, and SensorNet Project of Office of Naval Research, and was performed at Oak Ridge National Laboratory managed by UT-Battelle, LLC for U.S. Department of Energy under Contract No. DE-AC05-00OR22725.
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Liu, Q., Rao, N.S.V. (2018). Performance of State Estimation and Fusion with Elliptical Motion Constraints. In: Lee, S., Ko, H., Oh, S. (eds) Multisensor Fusion and Integration in the Wake of Big Data, Deep Learning and Cyber Physical System. MFI 2017. Lecture Notes in Electrical Engineering, vol 501. Springer, Cham. https://doi.org/10.1007/978-3-319-90509-9_3
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DOI: https://doi.org/10.1007/978-3-319-90509-9_3
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