{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T11:05:12Z","timestamp":1790075112928,"version":"4.0.1"},"reference-count":40,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2026,9,19]],"date-time":"2026-09-19T00:00:00Z","timestamp":1789776000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"General Projects in Natural Sciences Research","award":["202303021221114"],"award-info":[{"award-number":["202303021221114"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>GNSS measurement outliers degrade positioning accuracy in integrated global navigation satellite system\/inertial navigation system (GNSS\/INS) georeferencing for highly dynamic remote-sensing platforms. This study presents an adaptive kernel density robust Kalman filter (KDE-RKF) for attenuating anomalous observations through continuous measurement weighting. The method estimates the distribution of normalized innovation energies using a sliding-window logarithmic Gaussian kernel density estimator with adaptive bandwidth selection. Local density estimates determine channel-specific soft-gating weights that scale the effective measurement covariance. Performance was evaluated through 100 Monte Carlo runs per scenario covering isolated outliers, attitude-related bursts, terminal multipath, and simulated jamming. At 15% isolated-outlier contamination, KDE-RKF achieved a three-dimensional position root mean square error of\u00a038.4m, compared with\u00a087.3m\u00a0for the extended Kalman filter. Corresponding errors for the Huber and variational-Bayes Student\u2019s t filters were\u00a047.2\u00a0and\u00a044.3m, respectively. Following simulated jamming, positioning accuracy returned to near-nominal levels within\u00a01.8s. Each GNSS update required\u00a00.312ms\u00a0on the simulation platform. During a natural GPS excursion in the Zurich Urban Micro Aerial Vehicle dataset, peak position error decreased from\u00a041.63\u00a0to\u00a028.97m. These results support density-based soft-gating for reducing positioning errors under the evaluated GNSS degradation conditions.<\/jats:p>","DOI":"10.3390\/s26185921","type":"journal-article","created":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T10:21:48Z","timestamp":1790072508000},"page":"5921","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Adaptive Kernel Density Soft-Gating for Robust GNSS\/INS Georeferencing of Highly Dynamic Remote-Sensing Platforms Under Measurement Outliers"],"prefix":"10.3390","volume":"26","author":[{"given":"Kaiqiang","family":"Feng","sequence":"first","affiliation":[{"name":"State key Laboratory of Extreme Environment Optoelectronic Dynamic Measurement Technology and Instrument, North University of China, Taiyuan 030051, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"}]},{"given":"Jie","family":"Li","sequence":"additional","affiliation":[{"name":"State key Laboratory of Extreme Environment Optoelectronic Dynamic Measurement Technology and Instrument, North University of China, Taiyuan 030051, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"funding-acquisition","vocabulary":"credit"},{"role":"project-administration","vocabulary":"credit"},{"role":"supervision","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"}]},{"given":"Zhirui","family":"Sun","sequence":"additional","affiliation":[{"name":"State key Laboratory of Extreme Environment Optoelectronic Dynamic Measurement Technology and Instrument, North University of China, Taiyuan 030051, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"data-curation","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"software","vocabulary":"credit"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,19]]},"reference":[{"key":"ref_1","unstructured":"Groves, P.D. 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