Adaptive Transformed Unscented Simplex Cubature Kalman Filter for Target Tracking

References

• A. Miller, and B. Miller, “Underwater target tracking using bearing only measurements,” J. Commun. Technol. Electron., Vol. 63, no. 6, pp. 643–649, Jun. 2018.
   Web of Science ®Google Scholar
• A. Rosenqvist, “Asymptotic theory for a two-step pseudo-linear Doppler-bearing tracker,” Comput. Stat. Data. Anal., Vol. 21, no. 6, pp. 647–660, Jun. 1996.
   Web of Science ®Google Scholar
• X.-J. Tao, C.-R. Zou, and Z.-Y. He, “Passive target tracking using maximum likelihood estimation,” IEEE Trans. Aerosp. Electron. Syst., Vol. 32, no. 4, pp. 1348–1354, Oct. 1996.
   Web of Science ®Google Scholar
• J. Passerieux, D. Pillon, P. Blanc-Benon, and C. Jauffret. “Target motion analysis with bearings and frequencies measurements via instrumental variable estimator (passive sonar),” in International Conference on Acoustics, Speech, and Signal Processing. IEEE, 1989, pp. 2645–2648.
   Google Scholar
• Y. Chan, and S. Rudnicki, “Bearings-only and Doppler-bearing tracking using instrumental variables,” IEEE Trans. Aerosp. Electron. Syst., Vol. 28, no. 4, pp. 1076–1083, Oct. 1992.
   Web of Science ®Google Scholar
• K. Ho, and Y.-T. Chan, “An asymptotically unbiased estimator for bearings-only and Doppler-bearing target motion analysis,” IEEE Trans. Signal Process., Vol. 54, no. 3, pp. 809–822, Feb. 2006.
   Web of Science ®Google Scholar
• N. H. Nguyen, and K. Dogancay. “Improved weighted instrumental variable estimator for doppler-bearing source localization in heavy noise,” in 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2018, pp. 3529–3533.
   Google Scholar
• V. Teuliere, and O. Brun, “Parallelisation of the particle filtering technique and application to Doppler-bearing tracking of maneuvering sources,” Parallel. Comput., Vol. 29, no. 8, pp. 1069–1090, Aug. 2003.
   Web of Science ®Google Scholar
• U. Rajyalakshmi, R. P. Mallikarjuna, and D. Lingaraju, “Doppler-bearing passive target tracking system for underwater target detection using modified gain EKF,” International Journal on Intelligent Electronic Systems, Vol. 5, no. 2, pp. 12–17, 2011.
   Google Scholar
• M. N. Santhosh, S. K. Rao, R. P. Das, and K. L. Raju, “Underwater target tracking using unscented kalman filter,” Indian Journal of Science and Technology, Vol. 8, no. 31, pp. 1–5, Nov. 2015.
   Google Scholar
• S. Koteswara Rao, “Doppler-bearing passive target tracking using a parameterized unscented Kalman filter,” IETE. J. Res., Vol. 56, no. 1, pp. 69–75, Jan. 2010.
   Web of Science ®Google Scholar
• R. Zhan, and J. Wan, “Iterated unscented Kalman filter for passive target tracking,” IEEE Trans. Aerosp. Electron. Syst., Vol. 43, no. 3, pp. 1155–1163, Nov. 2007.
   Web of Science ®Google Scholar
• S. H. Hashemi, and A. Alfi, “Doppler and bearing tracking using adaptive modified covariance extended Kalman filter,” Journal of Control, Vol. 12, no. 4, pp. 23–33, Mar. 2019.
   Google Scholar
• S. Koteswara Rao, “Bearings-only passive target tracking: range uncertainty ellipse zone,” IETE. J. Res., 1–11, Mar. 2020. DOI:10.1080/03772063.2020.1739571.
   Web of Science ®Google Scholar
• Z. Yue, B. Lian, K. Tong, and S. Chen, “Novel strong tracking square-root cubature Kalman filter for GNSS/INS integrated navigation system,” IET Radar Sonar Navig., Vol. 13, no. 6, pp. 976–982, Feb. 2019.
   Web of Science ®Google Scholar
• S. J. Julier and J. K. Uhlmann, “New extension of the Kalman filter to nonlinear systems,” in Signal processing, sensor fusion, and target recognition VI, Vol. 3068. International Society for Optics and Photonics, 1997, pp. 182–193.
   Google Scholar
• M. T. Sabet, H. M. Daniali, A. Fathi, and E. Alizadeh, “Identification of an autonomous underwater vehicle hydrodynamic model using the extended, cubature, and transformed unscented Kalman filter,” IEEE J. Oceanic Eng., Vol. 43, no. 2, pp. 457–467, May. 2017.
   Web of Science ®Google Scholar
• I. Arasaratnam, and S. Haykin, “Cubature Kalman filters,” IEEE Trans. Autom. Control, Vol. 54, no. 6, pp. 1254–1269, May. 2009.
   Web of Science ®Google Scholar
• Y. Huang, Y. Zhang, B. Xu, Z. Wu, and J. A. Chambers, “A new adaptive extended Kalman filter for cooperative localization,” IEEE Trans. Aerosp. Electron. Syst., Vol. 54, no. 1, pp. 353–368, Sep. 2017.
   Web of Science ®Google Scholar
• Q. Zhang, Y. Yang, Q. Xiang, Q. He, Z. Zhou, and Y. Yao, “Noise adaptive Kalman filter for joint polarization tracking and channel equalization using cascaded covariance matching,” IEEE Photonics J., Vol. 10, no. 1, pp. 1–11, Jan. 2018.
   Web of Science ®Google Scholar
• D.-J. Jwo, and S.-Y. Lai, “Navigation integration using the fuzzy strong tracking unscented Kalman filter,” The Journal of Navigation, Vol. 62, no. 2, pp. 303–322, Apr. 2009.
   Web of Science ®Google Scholar
• X. Liu, H.-J. Liu, Y.-G. Tang, Q. Gao, and Z.-M. Chen, “Fuzzy adaptive unscented Kalman filter control of epileptiform spikes in a class of neural mass models,” Nonlinear Dyn., Vol. 76, no. 2, pp. 1291–1299, Apr. 2014.
   Web of Science ®Google Scholar
• C. Hajiyev, and H. E. Soken, “Robust adaptive unscented Kalman filter for attitude estimation of Pico satellites,” Int. J. Adapt Control Signal Process., Vol. 28, no. 2, pp. 107–120, Feb. 2014.
   Web of Science ®Google Scholar
• E. Ghorbani, and Y.-J. Cha, “An iterated cubature unscented Kalman filter for large-DOF systems identification with noisy data,” J. Sound. Vib., Vol. 420, pp. 21–34, Apr. 2018.
   Web of Science ®Google Scholar
• L. Chang, B. Hu, A. Li, and F. Qin, “Transformed unscented Kalman filter,” IEEE Trans. Autom. Control, Vol. 58, no. 1, pp. 252–257, Jun. 2012.
   Web of Science ®Google Scholar
• S. Wang, J. Feng, and K. T. Chi, “Spherical simplex-radial cubature Kalman filter,” IEEE Signal Process Lett., Vol. 21, no. 1, pp. 43–46, Nov. 2013.
   Web of Science ®Google Scholar
• H. Wu, S. Chen, B. Yang, and X. Luo, “Range-parameterised orthogonal simplex cubature Kalman filter for bearings-only measurements,” IET Sci. Meas. Technol., Vol. 10, no. 4, pp. 370–374, Jul. 2016.
   Web of Science ®Google Scholar
• P. H. Leong, S. Arulampalam, T. A. Lamahewa, and T. D. Abhayapala, “A Gaussian-sum based cubature Kalman filter for bearings-only tracking,” IEEE Trans. Aerosp. Electron. Syst., Vol. 49, no. 2, pp. 1161–1176, Apr. 2013.
   Web of Science ®Google Scholar
• S. H. Hashemi, and A. Alfi, “Doppler and bearing tracking using fuzzy adaptive unscented Kalman filter,” Iranian Journal of Fuzzy Systems, Vol. 16, no. 4, pp. 97–114, Aug. 2019.
   Web of Science ®Google Scholar
• Y. Dai, S. Yu, and Y. Yan, “An adaptive EKF-FMPC for the trajectory tracking of UVMS,” IEEE J. Oceanic Eng., Vol. 45, no. 3, pp. 699–713, Jul. 2019.
   Web of Science ®Google Scholar
• L. A. Scardua, and J. J. Da Cruz, “Complete offline tuning of the unscented Kalman filter,” Automatica. (Oxf), Vol. 80, pp. 54–61, Jun. 2017.
   Web of Science ®Google Scholar
• Z. Xie, and J. Feng, “Real-time nonlinear structural system identification via iterated unscented Kalman filter,” Mech. Syst. Signal. Process., Vol. 28, pp. 309–322, Apr. 2012.
   Web of Science ®Google Scholar
• A. Mehrjouyan, and A. Alfi, “Robust adaptive unscented Kalman filter for bearings-only tracking in three dimensional case,” Appl. Ocean Res., Vol. 87, pp. 223–232, Jun. 2019.
   Web of Science ®Google Scholar