{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,19]],"date-time":"2025-10-19T16:02:26Z","timestamp":1760889746204,"version":"build-2065373602"},"reference-count":36,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2018,12,1]],"date-time":"2018-12-01T00:00:00Z","timestamp":1543622400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100010097","name":"China Association for Science and Technology","doi-asserted-by":"publisher","award":["No.2017CASTQNJL046"],"award-info":[{"award-number":["No.2017CASTQNJL046"]}],"id":[{"id":"10.13039\/100010097","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["No.61790552","No.61501378","No.61501305"],"award-info":[{"award-number":["No.61790552","No.61501378","No.61501305"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>We propose an iterative nonlinear estimator based on the technique of variational Bayesian optimization. The posterior distribution of the underlying system state is approximated by a solvable variational distribution approached iteratively using evidence lower bound optimization subject to a minimal weighted Kullback-Leibler divergence, where a penalty factor is considered to adjust the step size of the iteration. Based on linearization, the iterative nonlinear filter is derived in a closed-form. The performance of the proposed algorithm is compared with several nonlinear filters in the literature using simulated target tracking examples.<\/jats:p>","DOI":"10.3390\/s18124222","type":"journal-article","created":{"date-parts":[[2018,12,3]],"date-time":"2018-12-03T06:02:09Z","timestamp":1543816929000},"page":"4222","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["An Iterative Nonlinear Filter Using Variational Bayesian Optimization"],"prefix":"10.3390","volume":"18","author":[{"given":"Yumei","family":"Hu","sequence":"first","affiliation":[{"name":"School of Automation, Northwestern Polytechnical University, Xi\u2019an 710072, China"},{"name":"Key Laboratory of Information Fusion Technology, Ministry of Education, Xi\u2019an 710072, China"}]},{"given":"Xuezhi","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Engineering, RMIT University, Melbourne 3000, Australia"}]},{"given":"Hua","family":"Lan","sequence":"additional","affiliation":[{"name":"School of Automation, Northwestern Polytechnical University, Xi\u2019an 710072, China"},{"name":"Key Laboratory of Information Fusion Technology, Ministry of Education, Xi\u2019an 710072, China"}]},{"given":"Zengfu","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Automation, Northwestern Polytechnical University, Xi\u2019an 710072, China"},{"name":"Key Laboratory of Information Fusion Technology, Ministry of Education, Xi\u2019an 710072, China"}]},{"given":"Bill","family":"Moran","sequence":"additional","affiliation":[{"name":"Department of Electrical and Electronic Engineering, University of Melbourne, Melbourne, VIC 3010, Australia"}]},{"given":"Quan","family":"Pan","sequence":"additional","affiliation":[{"name":"School of Automation, Northwestern Polytechnical University, Xi\u2019an 710072, China"},{"name":"Key Laboratory of Information Fusion Technology, Ministry of Education, Xi\u2019an 710072, China"}]}],"member":"1968","published-online":{"date-parts":[[2018,12,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Barshalom, Y., and Li, X.R. 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