Matches in SemOpenAlex for { <https://semopenalex.org/work/W2988242972> ?p ?o ?g. }
Showing items 1 to 74 of
74
with 100 items per page.
- W2988242972 endingPage "855" @default.
- W2988242972 startingPage "846" @default.
- W2988242972 abstract "Abstract Aiming at the problem that the traditional Unscented Kalman Filtering (UKF) algorithm can’t solve the problem that the measurement covariance matrix is unknown and the measured value contains outliers, this paper proposes a robust adaptive UKF algorithm based on Support Vector Regression (SVR). The algorithm combines the advantages of support vector regression with small samples, nonlinear learning ability and online estimation capability of adaptive algorithm based on innovation. Firstly, the SVR model is trained by using the innovation in the sliding window, and the new innovation is monitored. If the deviation between the estimated innovation and the measured innovation exceeds a given threshold, then measured innovation will be replaced by the predicted innovation, and then the processed innovation is used to calculate the measurement noise covariance matrix using the adaptive estimation algorithm. Simulation experiments and measured data experiments show that SVRUKF is significantly better than the traditional UKF, robust UKF and adaptive UKF algorithms for the case where the covariance matrix is unknown and the measured values have outliers." @default.
- W2988242972 created "2019-11-22" @default.
- W2988242972 creator A5011956683 @default.
- W2988242972 creator A5014708668 @default.
- W2988242972 creator A5062939247 @default.
- W2988242972 creator A5080140392 @default.
- W2988242972 date "2020-08-01" @default.
- W2988242972 modified "2023-10-16" @default.
- W2988242972 title "Robust adaptive UKF based on SVR for inertial based integrated navigation" @default.
- W2988242972 cites W1822076674 @default.
- W2988242972 cites W1940221538 @default.
- W2988242972 cites W1998727970 @default.
- W2988242972 cites W2026627614 @default.
- W2988242972 cites W2026891225 @default.
- W2988242972 cites W2047281995 @default.
- W2988242972 cites W2058676852 @default.
- W2988242972 cites W2086693977 @default.
- W2988242972 cites W2093319128 @default.
- W2988242972 cites W2116883614 @default.
- W2988242972 cites W2151611062 @default.
- W2988242972 cites W2531768534 @default.
- W2988242972 cites W2791539974 @default.
- W2988242972 cites W2792482170 @default.
- W2988242972 cites W2887157337 @default.
- W2988242972 doi "https://doi.org/10.1016/j.dt.2019.10.012" @default.
- W2988242972 hasPublicationYear "2020" @default.
- W2988242972 type Work @default.
- W2988242972 sameAs 2988242972 @default.
- W2988242972 citedByCount "12" @default.
- W2988242972 countsByYear W29882429722020 @default.
- W2988242972 countsByYear W29882429722021 @default.
- W2988242972 countsByYear W29882429722022 @default.
- W2988242972 countsByYear W29882429722023 @default.
- W2988242972 crossrefType "journal-article" @default.
- W2988242972 hasAuthorship W2988242972A5011956683 @default.
- W2988242972 hasAuthorship W2988242972A5014708668 @default.
- W2988242972 hasAuthorship W2988242972A5062939247 @default.
- W2988242972 hasAuthorship W2988242972A5080140392 @default.
- W2988242972 hasBestOaLocation W29882429721 @default.
- W2988242972 hasConcept C121332964 @default.
- W2988242972 hasConcept C128651787 @default.
- W2988242972 hasConcept C154945302 @default.
- W2988242972 hasConcept C173386949 @default.
- W2988242972 hasConcept C41008148 @default.
- W2988242972 hasConcept C62520636 @default.
- W2988242972 hasConcept C79061980 @default.
- W2988242972 hasConceptScore W2988242972C121332964 @default.
- W2988242972 hasConceptScore W2988242972C128651787 @default.
- W2988242972 hasConceptScore W2988242972C154945302 @default.
- W2988242972 hasConceptScore W2988242972C173386949 @default.
- W2988242972 hasConceptScore W2988242972C41008148 @default.
- W2988242972 hasConceptScore W2988242972C62520636 @default.
- W2988242972 hasConceptScore W2988242972C79061980 @default.
- W2988242972 hasIssue "4" @default.
- W2988242972 hasLocation W29882429721 @default.
- W2988242972 hasOpenAccess W2988242972 @default.
- W2988242972 hasPrimaryLocation W29882429721 @default.
- W2988242972 hasRelatedWork W2361177362 @default.
- W2988242972 hasRelatedWork W2376292734 @default.
- W2988242972 hasRelatedWork W2382856674 @default.
- W2988242972 hasRelatedWork W2415234998 @default.
- W2988242972 hasRelatedWork W2782016042 @default.
- W2988242972 hasRelatedWork W3006502707 @default.
- W2988242972 hasRelatedWork W3112302614 @default.
- W2988242972 hasRelatedWork W3216463974 @default.
- W2988242972 hasRelatedWork W4300961947 @default.
- W2988242972 hasRelatedWork W2164026189 @default.
- W2988242972 hasVolume "16" @default.
- W2988242972 isParatext "false" @default.
- W2988242972 isRetracted "false" @default.
- W2988242972 magId "2988242972" @default.
- W2988242972 workType "article" @default.