{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,18]],"date-time":"2026-09-18T04:33:56Z","timestamp":1789706036701,"version":"4.0.1"},"reference-count":27,"publisher":"Optica Publishing Group","issue":"1","license":[{"start":{"date-parts":[[2025,12,11]],"date-time":"2025-12-11T00:00:00Z","timestamp":1765411200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/doi.org\/10.1364\/OA_License_v2#VOR"},{"start":{"date-parts":[[2025,12,11]],"date-time":"2025-12-11T00:00:00Z","timestamp":1765411200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/opg.optica.org\/policies\/opg-tdm-policy.json"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2024YFB3909400"],"award-info":[{"award-number":["2024YFB3909400"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["opg.optica.org"],"crossmark-restriction":false},"short-container-title":["Appl. Opt."],"published-print":{"date-parts":[[2026,1,1]]},"abstract":"<jats:p>The concept of software-defined satellite (SDS) enables in-orbit software reconfiguration and payload virtualization, significantly enhancing the configurability and cross-mission reusability of imaging payloads. However, this flexibility also exposes traditional star identification methods\u2014which depend on fixed intrinsic camera parameters\u2014to severe robustness limitations when dealing with multiple cameras and varying operational conditions. Therefore, a universal and adaptive star identification algorithm is essential to ensure stable and precise attitude determination within the SDS architecture. To this end, this paper proposes a parameter-independent star identification algorithm based on topological invariance features. The method integrates a topological invariant feature coordinate system with a self-organizing map (SOM) neural network, enabling consistent recognition across diverse payload configurations and observation scenarios. Extensive experiments under conditions such as stellar position noise, false-star noise, missing-star noise, focal length variation, and dynamic fields of view demonstrate that the proposed algorithm consistently outperforms three benchmark methods and maintains stable accuracy. These results confirm that the proposed method not only aligns with the SDS philosophy of hardware\u2013software decoupling but also provides a necessary algorithmic foundation for its flexible, reconfigurable, and multi-payload attitude determination framework.<\/jats:p>","DOI":"10.1364\/ao.573709","type":"journal-article","created":{"date-parts":[[2025,11,12]],"date-time":"2025-11-12T17:00:08Z","timestamp":1762966808000},"page":"1","update-policy":"https:\/\/doi.org\/10.1364\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Robust star identification using topology-invariant features and a SOM neural network"],"prefix":"10.1364","volume":"65","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-2563-2418","authenticated-orcid":true,"given":"Zhipeng","family":"Luo","sequence":"first","affiliation":[{"name":"Shanghai Ocean University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guopeng","family":"Ding","sequence":"additional","affiliation":[{"name":"Chinese Academy of Sciences"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shihao","family":"Han","sequence":"additional","affiliation":[{"name":"Chinese Academy of Sciences"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ming","family":"Chen","sequence":"additional","affiliation":[{"name":"Shanghai Ocean University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-7401-5544","authenticated-orcid":true,"given":"Haodong","family":"Yan","sequence":"additional","affiliation":[{"name":"Chinese Academy of Sciences"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"285","published-online":{"date-parts":[[2025,12,11]]},"reference":[{"key":"ao-65-1-1-R1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3565387.3565455","article-title":"Architecture design of software defined scientific experiment payload","volume-title":"Proceedings of the 6th International Conference on Computer Science and Application Engineering","author":"Gao","year":"2022"},{"key":"ao-65-1-1-R3","doi-asserted-by":"publisher","first-page":"282","DOI":"10.1016\/j.cja.2023.04.019","type":"journal-article","volume":"36","author":"Zhang","year":"2023","journal-title":"Chin. 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All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.","name":"copyright","label":"Copyright"}]}}