Interacting Multiple Model Maximum Correntropy Kalman Filter with Adaptive Kernel Width

Interacting Multiple Model Maximum Correntropy Kalman Filter with Adaptive Kernel Width | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL Electronics Letters This is a preprint and has not been peer reviewed. Data may be preliminary. 12 May 2026 V1 Latest version Share on Interacting Multiple Model Maximum Correntropy Kalman Filter with Adaptive Kernel Width Authors : peng gu 0000-0002-7155-3388 [email protected] [email protected] and Zhongliang Jing [email protected] Authors Info & Affiliations https://doi.org/10.22541/authorea.15003192/v1 11 views 6 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract This paper proposes an adaptive kernel width interacting multiple model maximum correntropy Kalman filter (IMM-AMCKF) for maneuvering target tracking under non-Gaussian impulsive noise. It uses an innovation covariance ratio-based adaptive kernel width to balance accuracy and robustness. A mixed Gaussian-Sigmoid kernel is employed to avoid numerical instability when the bandwidth becomes very small. Integrated into the IMM framework, the filter handles multi-mode motion and non-Gaussian noise. Simulations demonstrate that the proposed filter achieves lower Root Mean Square Error (RMSE) than traditional filters under severe interference, with computational cost acceptable for real-time applications, providing a practical solution for robust state estimation in complex environments. Information & Authors Information Version history V1 Version 1 12 May 2026 Collection Electronics Letters Keywords aerospace navigation adaptive filters adaptive estimation Radar, Sonar and Navigation signal processing array signal processing adaptive estimation adaptive filters aerospace navigation Radar, Sonar and Navigation signal processing array signal processing aerospace navigation adaptive filters adaptive estimation Authors Affiliations peng gu 0000-0002-7155-3388 [email protected] [email protected] View all articles by this author Zhongliang Jing [email protected] Jiangsu Vocational College of Information Technology, Wuxi, China, 214153 View all articles by this author Metrics & Citations Metrics Article Usage 11 views 6 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation peng gu, Zhongliang Jing. Interacting Multiple Model Maximum Correntropy Kalman Filter with Adaptive Kernel Width. Authorea . 12 May 2026. DOI: https://doi.org/10.22541/authorea.15003192/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . Format Please select one from the list RIS (ProCite, Reference Manager) EndNote BibTex Medlars RefWorks Direct import Tips for downloading citations document.getElementById('citMgrHelpLink').addEventListener('click', function() { popupHelp(this.href); return false; }); $(".js__slcInclude").on("change", function(e){ if ($(this).val() == 'refworks') $('#direct').prop("checked", false); $('#direct').prop("disabled", ($(this).val() == 'refworks')); }); View Options View options PDF View PDF Figures Tables Media Share Share Share article link Copy Link Copied! Copying failed. 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