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Fundamentals, vol.E105-A, no.9, pp.1289-1297, Sept. 2022. 10.1587\/transfun.2021eap1152","DOI":"10.1587\/transfun.2021EAP1152"},{"key":"4","doi-asserted-by":"publisher","unstructured":"[4] C.C. Shen and J.S. Li, \u201cJoint DOA and dod estimation using KR-MUSIC for overloaded target in bistatic MIMO radars,\u201d IEICE Trans Fundamentals, vol.E107-A, no.4, pp.675-679, April 2024. 10.1587\/transfun.2023eal2028","DOI":"10.1587\/transfun.2023EAL2028"},{"key":"5","doi-asserted-by":"publisher","unstructured":"[5] C.C. Shen and W. Jhang, \u201cJoint CFO and DOA estimation based on MVDR criterion in interleaved OFDMA\/SDMA uplink,\u201d IEICE Trans. Fundamentals, vol.E107-A, no.7, pp.1066-1070, July 2024. 10.1587\/transfun.2023eal2064","DOI":"10.1587\/transfun.2023EAL2064"},{"key":"6","doi-asserted-by":"crossref","unstructured":"[6] P. Stoica and A. Nehorai, \u201cMUSIC, maximum likelihood and cramer-rao bound,\u201d ICASSP-88, International Conference on Acoustics, Speech, and Signal Processing, vol.4, pp.2296-2299, 1988. 10.1109\/icassp.1988.197097","DOI":"10.1109\/ICASSP.1988.197097"},{"key":"7","unstructured":"[7] R.O. Schmidt, \u201cA signal subspace approach to multiple source location and spectral estimation,\u201d PhD thesis, Stanford University, 1981."},{"key":"8","doi-asserted-by":"publisher","unstructured":"[8] R. Roy, A. Paulraj, and T. Kailath, \u201cESPRIT\u2006\u2014\u2006A subspace rotation approach to estimation of parameters of cisoids in noise,\u201d IEEE Trans. Acoustics, Speech, Signal Process., vol.34, no.5, pp.1340-1342, 1986. 10.1109\/tassp.1986.1164935","DOI":"10.1109\/TASSP.1986.1164935"},{"key":"9","doi-asserted-by":"publisher","unstructured":"[9] A.L. Swindlehurst, B. Ottersten, R. Roy, and T. Kailath, \u201cMultiple invariance ESPRIT,\u201d IEEE Trans. Signal Process., vol.40, no.4, pp.867-881, 1992. 10.1109\/78.127959","DOI":"10.1109\/78.127959"},{"key":"10","doi-asserted-by":"publisher","unstructured":"[10] J.-R. Larocque, J.P. Reilly, and W. Ng, \u201cParticle filters for tracking an unknown number of sources,\u201d IEEE Trans. Signal Process., vol.50, no.12, pp.2926-2937, 2002. 10.1109\/tsp.2002.805251","DOI":"10.1109\/TSP.2002.805251"},{"key":"11","doi-asserted-by":"publisher","unstructured":"[11] N. Kabaoglu, \u201cTarget tracking using particle filters with support vector regression,\u201d IEEE Trans. Veh. Technol., vol.58, no.5, pp.2569-2573, 2009. 10.1109\/tvt.2008.2005723","DOI":"10.1109\/TVT.2008.2005723"},{"key":"12","doi-asserted-by":"crossref","unstructured":"[12] S.-Y. Hou, H.-S. Hung, and T.-S. Kao, \u201cExtended Kalman particle filter angle tracking (EKPF-AT) algorithm for tracking multiple targets,\u201d 2010 International Conference on System Science and Engineering, pp.216-220, 2010. 10.1109\/icsse.2010.5551746","DOI":"10.1109\/ICSSE.2010.5551746"},{"key":"13","doi-asserted-by":"publisher","unstructured":"[13] B. Yang, \u201cProjection approximation subspace tracking,\u201d IEEE Trans. Signal Process., vol.43, no.1, pp.95-107, 1995. 10.1109\/78.365290","DOI":"10.1109\/78.365290"},{"key":"14","doi-asserted-by":"publisher","unstructured":"[14] Y. Chi, Y.C. Eldar, and R. Calderbank, \u201cPETRELS: Parallel subspace estimation and tracking by recursive least squares from partial observations,\u201d IEEE Trans. Signal Process., vol.61, no.23, pp.5947-5959, 2013. 10.1109\/tsp.2013.2282910","DOI":"10.1109\/TSP.2013.2282910"},{"key":"15","doi-asserted-by":"crossref","unstructured":"[15] L. Balzano, R. Nowak, and B. Recht, \u201cOnline identification and tracking of subspaces from highly incomplete information,\u201d 2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton), pp.704-711, 2010. 10.1109\/allerton.2010.5706976","DOI":"10.1109\/ALLERTON.2010.5706976"},{"key":"16","doi-asserted-by":"publisher","unstructured":"[16] N. Linh-Trung, V.-D. Nguyen, M. Thameri, T. Minh-Chinh, and K. Abed-Meraim, \u201cLow-complexity adaptive algorithms for robust subspace tracking,\u201d IEEE J. Sel. Topics Signal Process., vol.12, no.6, pp.1197-1212, 2018. 10.1109\/jstsp.2018.2876626","DOI":"10.1109\/JSTSP.2018.2876626"},{"key":"17","unstructured":"[17] D. Kong and J. Chun, \u201cA fast DOA tracking algorithm based on the extended Kalman filter,\u201d Proc. IEEE 2000 National Aerospace and Electronics Conference. NAECON 2000. 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Boyd, \u201cFast linear iterations for distributed averaging,\u201d 42nd IEEE International Conference on Decision and Control (IEEE Cat. no.03CH37475), vol.5, pp.4997-5002, 2003. 10.1109\/cdc.2003.1272421"},{"key":"25","doi-asserted-by":"crossref","unstructured":"[25] A. Sandryhaila, S. Kar, and J.M.F. Moura, \u201cFinite-time distributed consensus through graph filters, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.1080-1084, 2014. 10.1109\/icassp.2014.6853763","DOI":"10.1109\/ICASSP.2014.6853763"},{"key":"26","doi-asserted-by":"publisher","unstructured":"[26] S. Safavi and U.A. Khan, \u201cRevisiting finite-time distributed algorithms via successive nulling of eigenvalues,\u201d IEEE Signal Process. Lett., vol.22, no.1, pp.54-57, 2015. 10.1109\/lsp.2014.2346657","DOI":"10.1109\/LSP.2014.2346657"},{"key":"27","doi-asserted-by":"publisher","unstructured":"[27] N. Chen, P. Wei, L. Gao, W. Li, L. Liu, and H. Zhang, \u201cRobust tracking of multiple targets subspace based on distributed array networks,\u201d IEEE Trans. Aerosp. Electron. Syst., vol.59, no.6, pp.9758-9768, 2023. 10.1109\/taes.2023.3267439","DOI":"10.1109\/TAES.2023.3267439"},{"key":"28","doi-asserted-by":"publisher","unstructured":"[28] F. Pascal, Y. Chitour, J.-P. Ovarlez, P. Forster, and P. Larzabal, \u201cCovariance structure maximum-likelihood estimates in compound Gaussian noise: Existence and algorithm analysis,\u201d IEEE Trans. Signal Process., vol.56, no.1, pp.34-48, 2008. 10.1109\/tsp.2007.901652","DOI":"10.1109\/TSP.2007.901652"},{"key":"29","doi-asserted-by":"publisher","unstructured":"[29] F. Gini and M. 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