[1] Abdallah, F., Gning, A., and Bonnifait, P. (2008). Box particle filtering for nonlinear state estimation using interval analysis. Automatica, 44(3):807–815.

[2] Baum, M. and Hanebeck, U. D. (2009). Random hypersurface models for extended object tracking. In 2009 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), pages 178–183. IEEE.

[3] Baum, M. and Hanebeck, U. D. (2011). Shape tracking of extended objects and group targets with star-convex rhms. In 14th International Conference on Information Fusion, pages 1–8. IEEE.

[4] Baur, T., Reuter, J., Zea, A., and Hanebeck, U. D. (2022a). Extent estimation of sailing boats applying elliptic cones to 3d lidar data. In 2022 25th International Conference on Information Fusion (FUSION), pages 1–8. IEEE.

[5] Buhren, M. and Yang, B. (2006). Simulation of automotive radar target lists using a novel approach of object representation. In 2006 IEEE Intelligent Vehicles Symposium, pages 314–319. IEEE.

[6] Cao, X., Lan, J., and Li, X. R. (2016). Extension-deformation approach to extended object tracking. In 2016 19th International Conference on Information Fusion (FUSION), pages 1185–1192. IEEE.

[7] CHEN, H., ZENG, W., LIAN, F., and HAN, C. (2023). Non-star-convex extended target tracking algorithm for level-set gaussian process. Journal of Electronics and Information Technology, 45:1–10.

[8] Feldmann, M. and Franken, D. (2008). Tracking of extended objects and group targets using random matrices—a new approach. In 2008 11th International Conference on Information Fusion, pages 1–8. IEEE.

[9] Feldmann, M., Fränken, D., and Koch, W. (2010). Tracking of extended objects and group targets using random matrices. IEEE Transactions on Signal Processing, 59(4):1409–1420.

[10] Fowdur, J. S., Baum, M., and Heymann, F. (2021). An elliptical principal axes-based model for extended target tracking with marine radar data. In 2021 IEEE 24th International Conference on Information Fusion (FUSION), pages 1–8. IEEE.

[11] Gao, L., Battistelli, G., Chisci, L., and Tesori, M. (2023). Superquadric-based 3d extended object tracking. Available at SSRN 4385730.

[12] Gilholm, K. and Salmond, D. (2005). Spatial distribution model for tracking extended objects. IEEE Proceedings-Radar, Sonar and Navigation, 152(5):364–371.

[13] Gning, A., Ristic, B., and Mihaylova, L. (2011). A box particle filter for stochastic and set-theoretic measurements with association uncertainty. In 14th International Conference on Information Fusion, pages 1–8. IEEE.

[14] Govaers, F. (2019). On independent axes estimation for extended target tracking. In 2019 Sensor Data Fusion: Trends, Solutions, Applications (SDF), pages 1–6. IEEE.

[15] Hammarstrand, L., Svensson, L., Sandblom, F., and Sorstedt, J. (2012). Extended object tracking using a radar resolution model. IEEE Transactions on Aerospace and Electronic Systems, 48(3):2371–2386.

[16] Honer, J. and Kaulbersch, H. (2020). Bayesian extended target tracking with automotive radar using learned spatial distribution models. In 2020 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI), pages 316–322. IEEE.

[17] Hui, C., JinRui, D., and ChongZhao, H. (2018). An adaptive tracking algorithm for irregular shape extended target. Control Theory and Applications/Kongzhi Lilun Yu Yinyong, 35(8):1–12.

[18] Hui, C., Li, W., and ChongZhao, H. (2022). Student’s t inverse wishart filter based on random matrix modeling. Control Theory and Applications/Kongzhi Lilun Yu Yinyong, 39(6):1–11.

[19] Klambauer, G., Unterthiner, T., Mayr, A., and Hochreiter, S. (2017). Self-normalizing neural networks. Advances in neural information processing systems, 30.

[20] Koch, J. W. (2008). Bayesian approach to extended object and cluster tracking using random matrices. IEEE Transactions on Aerospace and Electronic Systems, 44(3):1042–1059.

[21] Lan, J. (2023). Extended object tracking using random matrix with extension-dependent measurement numbers. IEEE Transactions on Aerospace and Electronic Systems, pages 1–16.

[22] Lan, J. and Li, X. R. (2012). Tracking of extended object or target group using random matrix—part i: New model and approach. In 2012 15th International Conference on Information Fusion, pages 2177–2184. IEEE.

[23] Lan, J. and Li, X. R. (2014a). Tracking of maneuvering non-ellipsoidal extended object or target group using random matrix. IEEE Transactions on Signal Processing, 62(9):2450–2463.

[24] Li, M., Lan, J., and Li, X. R. (2023). Tracking of elliptical object with unknown but fixed lengths of axes. IEEE Transactions on Aerospace and Electronic Systems, pages 1–14.

[25] Li, Z., Wang, H., Yan, S., Zou, H., and Du, M. (2022). Distributed extended object tracking filter through embedded admm technique. In 2022 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI), pages 1–6. IEEE.

[26] Lu, L., Shin, Y., Su, Y., and Karniadakis, G. E. (2019). Dying relu and initialization: Theory and numerical examples. arXiv preprint arXiv:1903.06733.

[27] Lyu, X., Wu, S., Ca, R., Zheng, X., and Xie, Y. (2023). Spawning extended target tracking based on ggiw-pmb. Computer Systems and Applications, 32(5):220–226.

[28] Nezhadarya, E., Liu, Y., and Liu, B. (2019). Boxnet: A deep learning method for 2d bounding box estimation from bird’s-eye view point cloud. In 2019 IEEE Intelligent Vehicles Symposium (IV), pages 1557–1564. IEEE.

[29] Povey, D., Zhang, X., and Khudanpur, S. (2014). Parallel training of dnns with natural gradient and parameter averaging. arXiv preprint arXiv:1410.7455.

[30] Steuernagel, S., Thormann, K., and Baum, M. (2022). Cnn-based shape estimation for extended object tracking using point cloud measurements. In 2022 25th International Conference on Information Fusion (FUSION), pages 1–8. IEEE.

[31] Swain, A. and Clark, D. (2010). Extended object filtering using spatial independent cluster processes. In 2010 13th International Conference on Information Fusion, pages 1–8. IEEE.

[32] Tan, J.-T., Qi, G.-Q., Qi, J.-J., Yang, Y.-J., Li, Y.-Y., and Sheng, A.-D. (2022). Model parameter adaptive approach of extended object tracking using random matrix and identification. In 2022 International Conference on Cyber-Physical Social Intelligence (ICCSI), pages 91–97. IEEE.

[33] Thormann, K., Yang, S., and Baum, M. (2020). A comparison of kalman filter-based approaches for elliptic extended object tracking. In 2020 IEEE 23rd International Conference on Information Fusion (FUSION), pages 1–8. IEEE.

[34] Xia, Y., García-Fernández, Á. F., Meyer, F., Williams, J. L., Granström, K., and Svensson, L. (2022). Trajectory pmb filters for extended object tracking using belief propagation. arXiv preprint arXiv:2207.10164.

[35] Yang, J. L., Li, P., & Ge, H. W. (2014). Extended target shape estimation by fitting B‐spline curve. Journal of Applied Mathematics, 2014(1), 741892.

[36] Yang, S. and Baum, M. (2019). Tracking the orientation and axes lengths of an elliptical extended object. IEEE Transactions on Signal Processing, 67(18):4720–4729.

[37] Yang, S., Baum, M., and Granström, K. (2016). Metrics for performance evaluation of elliptic extended object tracking methods. In 2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI), pages 523–528. IEEE.

[38] Zhang, Y., Ji, H., and Hu, Q. (2017). A box-particle implementation of standard phd filter for extended target tracking. Information Fusion, 34:55–69.