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- W2389413633 abstract "Considering particle degradation in the traditional particle filter algorithm,an adaptive unscented particle filter algorithm based on predicted residual is proposed.The algorithm adopts a new proposal distribution combing the unscented kalman filter with the adaptive factor.The algorithm uses Unscented Kalman filter to generate a proposal distribution,in which the covariance of the predicted measurement,the cross-covariance of the state and measurement and the covariance of the state update are online adjusted by predicted residual as adaptive factor.Simulation experiments results of nonlinear state estimation demonstrate that the adaptive unscented particle filter is more adaptive and accuracy is also improved." @default.
- W2389413633 created "2016-06-24" @default.
- W2389413633 creator A5048923689 @default.
- W2389413633 date "2012-01-01" @default.
- W2389413633 modified "2023-09-26" @default.
- W2389413633 title "Adaptive Unscented Particle Filter Based on Predicted Residual" @default.
- W2389413633 hasPublicationYear "2012" @default.
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