研究了具有 m 维输出和 n 阶可观测的连续时间系统的具有任意极点最小阶数函数观测器的设计问题。文中将构成具有任意极点的函数观测器问题化为对于降阶观测器左向量的限制条件,将满阶观测器转化为一些极点向着左半复数平面无限远渐近...研究了具有 m 维输出和 n 阶可观测的连续时间系统的具有任意极点最小阶数函数观测器的设计问题。文中将构成具有任意极点的函数观测器问题化为对于降阶观测器左向量的限制条件,将满阶观测器转化为一些极点向着左半复数平面无限远渐近的降阶观测器,在此基础上给出在μ≤m 时具有任意极点函数观测器的最小阶数及μ>m 时最小阶数的上限。展开更多
A novel method for noise removal from the rotating accelerometer gravity gradiometer(MAGG)is presented.It introduces a head-to-tail data expansion technique based on the zero-phase filtering principle.A scheme for det...A novel method for noise removal from the rotating accelerometer gravity gradiometer(MAGG)is presented.It introduces a head-to-tail data expansion technique based on the zero-phase filtering principle.A scheme for determining band-pass filter parameters based on signal-to-noise ratio gain,smoothness index,and cross-correlation coefficient is designed using the Chebyshev optimal consistent approximation theory.Additionally,a wavelet denoising evaluation function is constructed,with the dmey wavelet basis function identified as most effective for processing gravity gradient data.The results of hard-in-the-loop simulation and prototype experiments show that the proposed processing method has shown a 14%improvement in the measurement variance of gravity gradient signals,and the measurement accuracy has reached within 4E,compared to other commonly used methods,which verifies that the proposed method effectively removes noise from the gradient signals,improved gravity gradiometry accuracy,and has certain technical insights for high-precision airborne gravity gradiometry.展开更多
文摘研究了具有 m 维输出和 n 阶可观测的连续时间系统的具有任意极点最小阶数函数观测器的设计问题。文中将构成具有任意极点的函数观测器问题化为对于降阶观测器左向量的限制条件,将满阶观测器转化为一些极点向着左半复数平面无限远渐近的降阶观测器,在此基础上给出在μ≤m 时具有任意极点函数观测器的最小阶数及μ>m 时最小阶数的上限。
文摘A novel method for noise removal from the rotating accelerometer gravity gradiometer(MAGG)is presented.It introduces a head-to-tail data expansion technique based on the zero-phase filtering principle.A scheme for determining band-pass filter parameters based on signal-to-noise ratio gain,smoothness index,and cross-correlation coefficient is designed using the Chebyshev optimal consistent approximation theory.Additionally,a wavelet denoising evaluation function is constructed,with the dmey wavelet basis function identified as most effective for processing gravity gradient data.The results of hard-in-the-loop simulation and prototype experiments show that the proposed processing method has shown a 14%improvement in the measurement variance of gravity gradient signals,and the measurement accuracy has reached within 4E,compared to other commonly used methods,which verifies that the proposed method effectively removes noise from the gradient signals,improved gravity gradiometry accuracy,and has certain technical insights for high-precision airborne gravity gradiometry.
