{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T21:11:27Z","timestamp":1792789887368,"version":"4.5.0"},"reference-count":47,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T00:00:00Z","timestamp":1790121600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Water Resources Science and Technology Plan Project of Zhejiang Province","award":["RC2521"],"award-info":[{"award-number":["RC2521"]}]},{"name":"Zhejiang Provincial Natural Science Foundation","award":["LZJMY24E090001"],"award-info":[{"award-number":["LZJMY24E090001"]}],"id":[{"id":"https:\/\/ror.org\/04aqat463","id-type":"ROR","asserted-by":"crossref"}]},{"award":["LZJMY24E090001"],"award-info":[{"award-number":["LZJMY24E090001"]}],"id":[{"id":"https:\/\/ror.org\/04aqat463","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In complex environments such as cities and canyons, cross-view matching of UAV and satellite imagery serves as a complementary approach to self-localization in the absence of GNSS signals. To address the limitations of existing datasets\u2014namely their limited variety of scenes and low annotation accuracy\u2014we have constructed the Cross-View, Multi-Altitude, Multi-Scene UAV Localization Dataset (CMHUAV). This dataset covers nine adjacent, non-overlapping subregions in Hangzhou and comprises 8625 precisely matched pairs of drone and satellite images, providing high-precision supervision for cross-view feature learning. Furthermore, we designed a Transformer-based global feature enhancement localization model (SLUG) equipped with a lightweight Adaptive Part Weighting (APW) module, which learns part-level scalar importance weights to dynamically recalibrate the contribution of each annular region. By integrating adaptive part-level weighting with a joint supervision strategy, we significantly enhance SLUG\u2019s spatial discrimination capability. We also propose the Height-aware Normalized Distance Matching (HNDM@K) metric, which unifies retrieval ranking quality and geospatial bias within a single framework, enabling joint evaluation of elevation-adaptive localization accuracy and retrieval performance. Experiments demonstrate that, on the CMHUAV dataset, SLUG achieves a recall of 93.53% and a mean precision of 93.9%; under the HNDM@1 metric, the localization scores at all three altitude levels exceed 94.8%. These results demonstrate that the proposed method, evaluated via offline visual retrieval, exhibits strong potential as a vision-based localization module for UAVs under GNSS disruption. Nevertheless, closed-loop flight tests and system-level localization performance still require further validation.<\/jats:p>","DOI":"10.3390\/s26196030","type":"journal-article","created":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T14:03:26Z","timestamp":1790172206000},"page":"6030","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["SLUG: Vision-Based UAV Self-Localization in GNSS-Denied Urban Environments"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-0642-9050","authenticated-orcid":false,"given":"Xuxu","family":"Qi","sequence":"first","affiliation":[{"name":"School of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"software","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1358-7846","authenticated-orcid":false,"given":"Enhui","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"resources","vocabulary":"credit"},{"role":"supervision","vocabulary":"credit"},{"role":"project-administration","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-4193-107X","authenticated-orcid":false,"given":"Beicheng","family":"Li","sequence":"additional","affiliation":[{"name":"School of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"software","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"},{"role":"visualization","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-3700-1172","authenticated-orcid":false,"given":"Chen","family":"Tian","sequence":"additional","affiliation":[{"name":"School of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"validation","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"resources","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-5180-2536","authenticated-orcid":false,"given":"Xuehao","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"4376","DOI":"10.1109\/TCSVT.2021.3135013","article-title":"A transformer-based feature segmentation and region alignment method for UAV-view geo-localization","volume":"32","author":"Dai","year":"2021","journal-title":"IEEE Trans. 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