{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,25]],"date-time":"2026-01-25T03:07:30Z","timestamp":1769310450675,"version":"3.49.0"},"reference-count":18,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2023,8,15]],"date-time":"2023-08-15T00:00:00Z","timestamp":1692057600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61673262"],"award-info":[{"award-number":["61673262"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61175028"],"award-info":[{"award-number":["61175028"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2019M651498"],"award-info":[{"award-number":["2019M651498"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["61673262"],"award-info":[{"award-number":["61673262"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["61175028"],"award-info":[{"award-number":["61175028"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2019M651498"],"award-info":[{"award-number":["2019M651498"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>This paper addresses the multi-sensor fusion target tracking problem based on maximum mixture correntropy in non-Gaussian noise environments exclusively using Doppler measurements. As Doppler measurements are non-linear, a statistical linear regression model is constructed using the unscented transformation. Then, a centralized measurement model is developed, and the mixture correntropy is determined, which contains the high-order statistics of state prediction and the measurement error caused by noise. Then, a robust fusion filter is proposed by maximizing the mixture-correntropy-based cost. To improve numerical stability, the information filter and corresponding square root version are also derived. Furthermore, the performance of the proposed algorithm is analyzed, and the selection of the kernel width is discussed. Experiments are performed using simulated data and automatic driving software. The results show that the estimation performance of the proposed algorithm is better with respect to outliers and mixture Gaussian noise than that of traditional methods.<\/jats:p>","DOI":"10.3390\/info14080461","type":"journal-article","created":{"date-parts":[[2023,8,15]],"date-time":"2023-08-15T11:09:44Z","timestamp":1692097784000},"page":"461","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Multi-Sensor Fusion Target Tracking Based on Maximum Mixture Correntropy in Non-Gaussian Noise Environments with Doppler Measurements"],"prefix":"10.3390","volume":"14","author":[{"given":"Changyu","family":"Yi","sequence":"first","affiliation":[{"name":"School of Astronautics and Aeronautics, Shanghai Jiao Tong University, Shanghai 200240, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7168-6949","authenticated-orcid":false,"given":"Minzhe","family":"Li","sequence":"additional","affiliation":[{"name":"School of Astronautics and Aeronautics, Shanghai Jiao Tong University, Shanghai 200240, China"}]},{"given":"Shuyi","family":"Li","sequence":"additional","affiliation":[{"name":"School of Astronautics and Aeronautics, Shanghai Jiao Tong University, Shanghai 200240, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,8,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1016\/j.sigpro.2015.09.001","article-title":"Augmented state gm-phd filter with registration errors for multi-target tracking by doppler radars","volume":"120","author":"Wu","year":"2016","journal-title":"Signal Process."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Zheng, J. (2021). Structure and Performance Analysis of Signal Acquisition and Doppler Tracking in LEO Augmented GNSS Receiver. Sensors, 21.","DOI":"10.3390\/s21020525"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Ristic, B., and Farina, A. (2012, January 25\u201330). Joint detection and tracking using multi-static doppler-shift measurements. 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Lett."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1723","DOI":"10.1109\/LSP.2015.2428713","article-title":"Convergence of a Fixed-Point Algorithm under Maximum Correntropy Criterion","volume":"22","author":"Chen","year":"2015","journal-title":"IEEE Signal Process. Lett."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Wang, G.Q., Gao, Z.X., Zhang, Y.G., and Ma, B. (2018). Adaptive maximum correntropy Gaussian filter based on variational Bayes. Sensors, 18.","DOI":"10.3390\/s18061960"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1109\/7.913685","article-title":"Comparison of two measurement fusion methods for Kalman-filter-based multisensor data fusion","volume":"37","author":"Gan","year":"2001","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"8659","DOI":"10.1016\/j.jfranklin.2017.10.023","article-title":"Maximum correntropy unscented Kalman and information filters for non-Gaussian measurement noise","volume":"354","author":"Wang","year":"2017","journal-title":"J. Frankl. Inst."},{"key":"ref_18","unstructured":"(2023, August 02). Udacity\u2019s Self-Driving Car Simulator, Udacity, Mountain View, CA, USA. Available online: https:\/\/github.com\/udacity\/self-drivingcar-sim."}],"container-title":["Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2078-2489\/14\/8\/461\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T20:34:25Z","timestamp":1760128465000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2078-2489\/14\/8\/461"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,15]]},"references-count":18,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2023,8]]}},"alternative-id":["info14080461"],"URL":"https:\/\/doi.org\/10.3390\/info14080461","relation":{},"ISSN":["2078-2489"],"issn-type":[{"value":"2078-2489","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,8,15]]}}}