Today, the GNSS （global navigation satellite system） is used for more complicate and accurate applications such as monitoring or stake out works. The truth lies in the fact that in the most of the times not enough a...Today, the GNSS （global navigation satellite system） is used for more complicate and accurate applications such as monitoring or stake out works. The truth lies in the fact that in the most of the times not enough attention is paid to the antenna＇s setup. Usually, gross errors are found in the antenna＇s centering, leveling and in the measurement of its height, which are significant. In this paper, a thoroughly analysis of the above mentioned errors is carried out. The influence of these errors in the calculation of the X, Y, Z Cartesian geocentric coordinates and the ~, 2, h ellipsoid geodetic coordinates of a point P on the earth＇s surface, is analyzed and is presented in several diagrams. Also a new convenient method for the accurate measurement of the antenna＇s height is presented and it is strongly proposed. The conclusions outline the magnitude of these errors and prove the significance of the antenna＇s proper setup at the accurate GNSS applications.展开更多
Two types of sensitivities are proposed for stat- ically stable sailcrafts. One type is the sensitivities of solar-radiation-pressure force with respect to position of the center of mass, and the other type is the sen...Two types of sensitivities are proposed for stat- ically stable sailcrafts. One type is the sensitivities of solar-radiation-pressure force with respect to position of the center of mass, and the other type is the sensitivities of solar-radiation-pressure force with respect to attitude. The two types of sensitivities represent how the solar-radiation- pressure force changes with the position of mass center and the attitude. Sailcrafts with larger sensitivities undergo larger error of the solar-radiation-pressure force, leading to larger orbit error, as demonstrated by simulation. Then as a case study, detailed formulas are derived to calculate the sensi- tivities for sailcrafts with four triangular sails. According to these formulas, in order to reduce both types of sensitivities, the angle between opposed sails should not be too large, and the center of mass should be as close to the axis of symmetry of the four sails as possible and as far away from the center of pressure of the sailcraft as possible.展开更多
To address the issue of low denoising accuracy of unmanned aerial vehicle(UAV)sensor data in a nonlinear non-Gaussian system,an adaptive central error entropy(CEE)—strong tracking cubature Kalman filter(STCKF)algorit...To address the issue of low denoising accuracy of unmanned aerial vehicle(UAV)sensor data in a nonlinear non-Gaussian system,an adaptive central error entropy(CEE)—strong tracking cubature Kalman filter(STCKF)algorithm based on fuzzy broad learning system(fuzzy-BLS)is proposed in this paper.Although entropy algorithms are known to be effective for denoising in non-Gaussian systems,their application in nonlinear systems is still limited.To address this issue,this study combines the central error entropy criterion with the STCKF algorithm.This approach is boosted by the denoising capabilities of the STCKF algorithm for nonlinear systems,thereby compensating for the shortcomings of the CEE criterion for nonlinear systems and leveraging the advantages of CEE in non-Gaussian systems.Thus,the new algorithm has enhanced robustness and accuracy for nonlinear non-Gaussian systems.To further optimize this algorithm,a parameter update method based on fuzzyBLS is adopted to address the problem of excessive reliance on experience and lack of dependency in the selection of parameters,such as weight and kernel width,in the fusion of the CEE criterion.This method can dynamically adjust the optimal parameter template obtained from offline training online to minimize the root mean square error of the denoising results and provide adaptive denoising capability.Simulation and actual data denoising experiments confirmed that the proposed data denoising method accurately addresses the denoising problem of UAV sensor data in nonlinear non-Gaussian systems.展开更多
文摘Today, the GNSS （global navigation satellite system） is used for more complicate and accurate applications such as monitoring or stake out works. The truth lies in the fact that in the most of the times not enough attention is paid to the antenna＇s setup. Usually, gross errors are found in the antenna＇s centering, leveling and in the measurement of its height, which are significant. In this paper, a thoroughly analysis of the above mentioned errors is carried out. The influence of these errors in the calculation of the X, Y, Z Cartesian geocentric coordinates and the ~, 2, h ellipsoid geodetic coordinates of a point P on the earth＇s surface, is analyzed and is presented in several diagrams. Also a new convenient method for the accurate measurement of the antenna＇s height is presented and it is strongly proposed. The conclusions outline the magnitude of these errors and prove the significance of the antenna＇s proper setup at the accurate GNSS applications.
基金supported by the National Natural Science Foundation of China (10832004)China Postdoctoral Science Foundation (023200006)
文摘Two types of sensitivities are proposed for stat- ically stable sailcrafts. One type is the sensitivities of solar-radiation-pressure force with respect to position of the center of mass, and the other type is the sensitivities of solar-radiation-pressure force with respect to attitude. The two types of sensitivities represent how the solar-radiation- pressure force changes with the position of mass center and the attitude. Sailcrafts with larger sensitivities undergo larger error of the solar-radiation-pressure force, leading to larger orbit error, as demonstrated by simulation. Then as a case study, detailed formulas are derived to calculate the sensi- tivities for sailcrafts with four triangular sails. According to these formulas, in order to reduce both types of sensitivities, the angle between opposed sails should not be too large, and the center of mass should be as close to the axis of symmetry of the four sails as possible and as far away from the center of pressure of the sailcraft as possible.
基金partially supported by the National Natural Science Foundation of China(Grant Nos.62033010,U23B2061)the Qing Lan Project of Jiangsu Province of China(Grant No.R2023Q07)the Joint Fund of Zhejiang Provincial Natural Science Foundation of China(Grant No.ZJMD25D050002)。
文摘To address the issue of low denoising accuracy of unmanned aerial vehicle(UAV)sensor data in a nonlinear non-Gaussian system,an adaptive central error entropy(CEE)—strong tracking cubature Kalman filter(STCKF)algorithm based on fuzzy broad learning system(fuzzy-BLS)is proposed in this paper.Although entropy algorithms are known to be effective for denoising in non-Gaussian systems,their application in nonlinear systems is still limited.To address this issue,this study combines the central error entropy criterion with the STCKF algorithm.This approach is boosted by the denoising capabilities of the STCKF algorithm for nonlinear systems,thereby compensating for the shortcomings of the CEE criterion for nonlinear systems and leveraging the advantages of CEE in non-Gaussian systems.Thus,the new algorithm has enhanced robustness and accuracy for nonlinear non-Gaussian systems.To further optimize this algorithm,a parameter update method based on fuzzyBLS is adopted to address the problem of excessive reliance on experience and lack of dependency in the selection of parameters,such as weight and kernel width,in the fusion of the CEE criterion.This method can dynamically adjust the optimal parameter template obtained from offline training online to minimize the root mean square error of the denoising results and provide adaptive denoising capability.Simulation and actual data denoising experiments confirmed that the proposed data denoising method accurately addresses the denoising problem of UAV sensor data in nonlinear non-Gaussian systems.
