The IMU（inertial measurement unit） error equations in the earth fixed coordinates are introduced firstly. A fading Kalman filtering is simply introduced and its shortcomings are analyzed, then an adaptive filtering ...The IMU（inertial measurement unit） error equations in the earth fixed coordinates are introduced firstly. A fading Kalman filtering is simply introduced and its shortcomings are analyzed, then an adaptive filtering is applied in IMU/GPS integrated navigation system, in which the adaptive factor is replaced by the fading factor. A practical example is given. The resuits prove that the adaptive filter combined with the fading factor is valid and reliable when applied in IMU/GPS integrated navigation system.展开更多
Inherent flaws in the extended Kalman filter(EKF) algorithm were pointed out and unscented Kalman filter(UKF) was put forward as an alternative.Furthermore,a novel adaptive unscented Kalman filter(AUKF) based on innov...Inherent flaws in the extended Kalman filter(EKF) algorithm were pointed out and unscented Kalman filter(UKF) was put forward as an alternative.Furthermore,a novel adaptive unscented Kalman filter(AUKF) based on innovation was developed.The three data-fusing approaches were analyzed and evaluated in a mathematically rigorous way.Field experiments conducted in lake further demonstrate that AUKF reduces the position error approximately by 65% compared with EKF and by 35% UKF and improves the robust performance.展开更多
A two-way adaptive Kalman filter is proposed by combining a two-way filter with an adaptive filter for orbit determination of a maneuvered GEO satellite.A method of using Newton's high-resolution differential form...A two-way adaptive Kalman filter is proposed by combining a two-way filter with an adaptive filter for orbit determination of a maneuvered GEO satellite.A method of using Newton's high-resolution differential formula and polynomial fitting for modeling the thrust force of a maneuvered GEO satellite is developed.The adaptive factor,which balances the contributions of the measurements and the dynamic model information,is determined by using a two-segment function and predicted residual statistics.Simulations with a maneuvered GEO satellite tracked by the Chinese ground tracking network were conducted to verify the performance of the proposed orbit determination technique and the method of thrust force modeling.The results show that refining the thrust force model is beneficial for the orbit determination of a maneuvered GEO satellite;the two-way adaptive Kalman filter can efficiently control the influence of the dynamic model errors on the orbit state estimate.展开更多
The objective of this work is to improve the measurement accuracy of a gyroscope on a angular motion base with a simple adaptive filter scheme.Two main topics are highlighted in this work.The first topic is to show bu...The objective of this work is to improve the measurement accuracy of a gyroscope on a angular motion base with a simple adaptive filter scheme.Two main topics are highlighted in this work.The first topic is to show building a dual-process model employed for the conventional Kalman filter.The second topic is to show developing a modified noise adaptive algorithm when measurement noise and process noise are unknown.The experimental results are presented to show that the simple adaptive filtering scheme outperforms the other conventional scheme in this paper in terms of noise reduction.展开更多
基金Supported by the National Natural Science Foundation of China (No.40274002 No.40474001).
文摘The IMU（inertial measurement unit） error equations in the earth fixed coordinates are introduced firstly. A fading Kalman filtering is simply introduced and its shortcomings are analyzed, then an adaptive filtering is applied in IMU/GPS integrated navigation system, in which the adaptive factor is replaced by the fading factor. A practical example is given. The resuits prove that the adaptive filter combined with the fading factor is valid and reliable when applied in IMU/GPS integrated navigation system.
基金Projects(2009AA093302,2002AA401003)supported by the National High-Tech Research and Development Program of ChinaProject(YYYJ-0917)supported by the Knowledge Innovation of Chinese Academy of Sciences+1 种基金Projects(61273334,61233013)supported by the National Natural Science Foundation of ChinaProject(2011010025-401)supported by the Natural Science Foundation of Liaoning Province,China
文摘Inherent flaws in the extended Kalman filter(EKF) algorithm were pointed out and unscented Kalman filter(UKF) was put forward as an alternative.Furthermore,a novel adaptive unscented Kalman filter(AUKF) based on innovation was developed.The three data-fusing approaches were analyzed and evaluated in a mathematically rigorous way.Field experiments conducted in lake further demonstrate that AUKF reduces the position error approximately by 65% compared with EKF and by 35% UKF and improves the robust performance.
基金supported by the Foundation for the Author of National Excellent Doctoral Dissertation of China (Grant No. 2007B51)National Natural Science Foundation of China (Grant Nos. 41174008 and 41020144004)China Postdoctoral Science Foundation (Grant Nos. 20080430148 and200902444)
文摘A two-way adaptive Kalman filter is proposed by combining a two-way filter with an adaptive filter for orbit determination of a maneuvered GEO satellite.A method of using Newton's high-resolution differential formula and polynomial fitting for modeling the thrust force of a maneuvered GEO satellite is developed.The adaptive factor,which balances the contributions of the measurements and the dynamic model information,is determined by using a two-segment function and predicted residual statistics.Simulations with a maneuvered GEO satellite tracked by the Chinese ground tracking network were conducted to verify the performance of the proposed orbit determination technique and the method of thrust force modeling.The results show that refining the thrust force model is beneficial for the orbit determination of a maneuvered GEO satellite;the two-way adaptive Kalman filter can efficiently control the influence of the dynamic model errors on the orbit state estimate.
文摘The objective of this work is to improve the measurement accuracy of a gyroscope on a angular motion base with a simple adaptive filter scheme.Two main topics are highlighted in this work.The first topic is to show building a dual-process model employed for the conventional Kalman filter.The second topic is to show developing a modified noise adaptive algorithm when measurement noise and process noise are unknown.The experimental results are presented to show that the simple adaptive filtering scheme outperforms the other conventional scheme in this paper in terms of noise reduction.
