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The multiple fading factors are employed to make different state channels have separate adjustment ability, which enhances the tracking performance for status mutation. The second-order difference transformation is adopted to improve the approximation accuracy of state posterior mean and covariance. Therefore, a multiple fading second-order central difference Kalman filter (MFSCDKF) is formed for CubeSat attitude estimation system in the presence of status mutation. Compared with the single fading factor first-order central difference Kalman filter, the proposed one can improve tracking performance and estimation accuracy simultaneously. Simulation results based on real telemetry data from the on-orbit CubeSat NJUST-1 verify the effectiveness of the proposed MFSCDKF.<\/jats:p>","DOI":"10.1177\/01423312211019542","type":"journal-article","created":{"date-parts":[[2021,7,20]],"date-time":"2021-07-20T04:41:30Z","timestamp":1626756090000},"page":"3519-3530","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["Strong tracking central difference Kalman filter for CubeSat attitude estimation with status mutation"],"prefix":"10.1177","volume":"43","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4667-5217","authenticated-orcid":false,"given":"Haining","family":"Ma","sequence":"first","affiliation":[{"name":"Micro\/Nano Satellite Research Center, School of Mechanical Engineering, Nanjing University of Science and Technology, 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