任意16k阶Franklin完美幻方构造法

提出了一种构造任意16k阶Franklin完美幻方的方法并予以证明.通过讨论Franklin幻方行列各数的对称性,给出了加强及弱化的对称性条件.     

面向曲面零件的在线检测系统误差补偿技术研究

数控机床在线检测不但能显著提高加工质量,也能提高加工效率,但在线检测系统的精度因受各类误差因素的影响尚需进一步的提高,以便在高精度曲面零件的加工中得以应用.针对数控机床接触式在线检测的误差源及误差补偿技术进行深入研究,建立包括机床几何误差和测头系统误差的数控机床在线检测的误差补偿数学模型,提出基于三角网格模型的测球半径补偿方法,实现对检测数据的补偿修正.在此基础上,通过VC++6.0编程工具,开发出具有误差自动补偿功能的在线检测系统,并通过在线检测实验平台的搭建対实例零件进行验证.通过与CMM检测结果的比较,结果表明,所提出的在线检测误差补偿技术是可行和有效的.     

匀变速运动中编码器细分误差分析方法的研究(英文)

编码器的误差不仅与位置有关,还与速度、加速度等运动参数有关,分析编码器细分误差的产生原因,给出细分误差的计算公式,建立了匀变速运动中编码器光电信号的数学模型,通过计算机模拟仿真,提出了匀变速编码器光电信号参数特征的提取方法,即对实际采集的信号进行等间隔处理后,进行谐波分析,可以恢复出较真实的光电信号参数,进而计算出细分误差,最后给出了本方法的适用条件。     

动力学模型系统误差及其协方差阵的随机加权拟合法

在现有的基于移动窗口函数模型和随机模型系统误差自适应拟合方法的基础上,提出一种基于移动窗口动态导航模型系统误差的随机加权拟合法,在相同的窗口内给出了相应的状态预报向量协方差阵的随机加权拟合。由于动力学模型系统误差难以直接修正,采用修正状态估计误差向量及动力学模型误差向量的方法,实现对动力学模型系统误差的修正,然后利用修正后的动力学模型及相应的协方差阵进行导航滤波计算,有效地抑制动力学模型系统系统误差的影响,提高导航解算的精度。仿真结果证明,采用随机加权拟合后的算法精度优于未进行拟合的卡尔曼滤波和自适应卡尔曼滤波算法。     

非均匀圆阵天线模型解模糊误差研究

基于干涉仪的立体基线法与传统测向解模糊方法相比,天线摆放方式更为灵活。针对这一优点,建立了非均匀圆阵天线阵列模型,给出了该模型理论测向误差的表达式。通过分析解算过程中影响测向误差的因素,提出了一种减小天线阵列实际测向误差的方法。为保证系统具有一定的解模糊能力,给出了该方法中天线孔径对系统解模糊频段的限制条件。基于建立的天线模型,通过Matlab仿真,验证了方法及理论分析的正确性,对合理选择天线盘孔径、减小测向系统的误差具有可行性。     

挠性捷联惯组的多位置对准技术

弹用惯组的误差是影响系统落点导航精度的关键因素。针对如何利用已知的航向信息最大程度地提高弹用挠性陀螺的实际使用精度的问题,将多位置对准技术应用于惯组误差的在线标定,利用行列式法对陀螺静态漂移误差进行了可观性分析,给出常用两位置对准的理论分析及最优三位置的限定方程。仿真结果表明,最优三位置对准可以有效分离常值漂移和与比力一次项有关的漂移,实现挠性陀螺静态漂移误差状态变量全部可观测,最大程度地降低其对系统误差的影响。     

变宽度凸组合变阶数LMS自适应滤波算法

为了进一步改善凸组合变阶数最小均方(convex combination variable fractional tap-length least mean square,CFTLMS)自适应滤波算法的稳态性能,在证明其稳态性能的基础上,提出了一种变宽度凸组合变阶数(variable width-CFTLMS, VW-CFTLMS)自适应滤波算法,并给出参数的选择依据。仿真结果验证了低信噪比情况下,VW-CFTLMS算法稳态性能和参数选择依据的正确性;同时该算法的稳态性能要优于CFTLMS算法,其额外均方误差相比于CFTLMS算法降低约1.8 dB,具有实用价值。     

Novel reference range selection method in InlSAR imaging

Aiming at the reference range selection for different antennas in interferometric inverse synthetic aperture radar (InISAR) systems, this paper proposes a respective focusing (RF) method. The reference ranges for echoes of different antennas are selected respectively for RF, which is different from the traditional uniform focusing (UF) with the same reference range applied to all the antennas. First, a comparison between UF and RF for InISAR signal model considering the ranging error is given. Compared with RF, UF has an advantage in overcoming the ranging error differences between different antennas. Then the influence of ranging error upon the interferometric imaging with RF is investigated particularly, and it is found that the ranging error differences between different antennas are far smaller than the wavelength, which is advantageous to imaging. By comparing the capabilities of interferometric imaging between RF and UF, it is concluded that RF is a better choice in conquering problems such as image mismatching and phase ambiguity even with ranging errors. Simulations demonstrate the validity of the proposed method.     

Mobile channel estimation for MU-MIMO systems using KL expansion based extrapolation

In multi-user multiple input multiple output(MU-MIMO) systems,the outdated channel state information at the transmitter caused by channel time variation has been shown to greatly reduce the achievable ergodic sum capacity.A simple yet effective solution to this problem is presented by designing a channel extrapolator relying on Karhunen-Loeve(KL) expansion of timevarying channels.In this scheme,channel estimation is done at the base station(BS) rather than at the user terminal(UT),which thereby dispenses the channel parameters feedback from the UT to the BS.Moreover,the inherent channel correlation and the parsimonious parameterization properties of the KL expansion are respectively exploited to reduce the channel mismatch error and the computational complexity.Simulations show that the presented scheme outperforms conventional schemes in terms of both channel estimation mean square error(MSE) and ergodic capacity.