基于微多普勒特征的人体上肢运动参数估计

人体行走的雷达特征研究是近年发展起来的新的研究方向,基于雷达的人体目标探测在安全防护、灾害救援、生物力学和运动学研究等方面具有广阔的应用前景。人体走动时手和腿的摆动对回波信号产生调制,回波信号的微多普勒特征能精细地刻画体动规律,将有效地探测并估计人体的运动规律。主要研究人体上肢的雷达特征,首先以人体上肢的运动模型为基础,建立了其雷达回波模型,通过理论分析得到了参数估计的方法,通过广义Radon变换提取行人摆臂的微多普勒。最后通过仿真实验,验证了算法的有效性。     

直升机旋翼试验台动力学分析及建模

直升机旋翼动平衡试验台是一种主要的直升机旋翼测试设备之一,对试验台进行动力学分析和建模可以提高试验台的控制精度和试验的效果.在分析试验台结构和功能的基础上,简化了桨叶变距拉杆的载荷,通过对自动倾斜器的受力分析,得出了旋翼系统的动态模型.通过对液压系统和旋翼系统的联合仿真,分析了系统在旋翼姿态变化时的动态响应和交互耦合影响,初步了解了系统在各种不同负载特性下的响应,为试验台的姿态调节、激振的精度提高和进行理论研究提供基础,并为地面旋翼试验台系统的设计和控制提供依据.     

适用于Ad hoc网络的EIGamal型门限数字签名方案

现有ElGamal型门限数字签名方案在签名前签名各方需要协商生成一个随机数,该过程计算量与通信量比较大,不能满足Ad hoc网络的需求.将组合公钥的思想引入到ElGamal型门限数字签名的随机数生成中,为Ad hoc网络提出一种门限数字签名的改进方案.方案由密钥初始化和门限签名两部分组成.密钥初始化时,签名各方使用分布式密钥生成协议协商出系统公/私钥对和一个随机数矩阵,每个节点掌握部分私钥和部分随机数矩阵;门限签名时,每个签名方使用相同的算法在掌握的部分随机数矩阵中选择随机数进行部分签名;最后将部分签名合成整体签名.对提出的方案在随机预言(RO, Random Oracle)模型中进行了安全性证明.实用性分析表明:方案计算复杂度低,交互次数少,通信量小,有很好的执行效率与签名成功率.     

基于点线关系的透视图消隐算法

准确获取建筑物的三维形体信息,在军事和民用上都有非常重要的意义.针对建筑物三维形体获取过程中的消隐问题,提出了一种基于点线关系的三维透视图消隐算法.结合后向面判别法和光线投射算法,利用三维表面模型中点、线、面的遮挡关系和视平面域上的包含性规则,进行边界线段的显、隐程度检查,实现对模型的消隐处理.实验结果表明,该算法数据结构简单,建立的透视投影计算模型正确且消隐算法有效,为地形地物透视图的消隐提供了一种新的方法与支持手段.     

无人机舵面负载模拟系统的小脑模型控制

为解决无人机舵面负载模拟系统中非线性和多余力矩扰动问题,利用小脑模型神经网络非线性逼近能力强、结构简单、适于实时控制等特点,采用小脑模型和传统PD(Proportional-Derivative)控制结合的复合控制策略,由小脑模型实现前馈控制,PD控制实现反馈控制,以保证在系统运行各阶段的控制精度.分析讨论了复合控制的不稳定性问题,研究了基于可信度分配和学习率自适应调整的改进型小脑模型的应用情况,提出一种适用于单输入单输出系统的简化小脑模型复合控制设计方法.仿真结果表明该方法有效地解决了小脑模型和PD复合控制的不稳定问题,改善了系统动态加载性能,并具有很好的抗干扰性能.     

Upper limit of the total magnetic flux in an active region according to the photometric-magnetic dynamical model

The photometric-magnetic dynamical model handles the evolution of an individual sunspot as an autonomous nonlinear, though integrable, dynamical system. One of its consequences is the prediction of an upper limit of the sunspot areas. This upper limit is analytically expressed by the model parameters, while its calculated value is verified by the observational data. In addition, an upper limit for the magnetic strength inside the sunspot is also predicted, and then, we obtain the following significant result: The upper limit of the total magnetic flux in an active region is found to be of about 7.23 × 10²³ Mx, namely, phenomenologically equal to the magnetic flux concentrated in the totality of the granules of the quiet Sun, having a typical maximum magnetic strength of about 12G. Therefore, the magnetic flux concentrated in an active region cannot exceed the magnetic flux concentrated in the photosphere as a whole.     

Using the radial basis function neural network to predict ionospheric critical frequency of F2 layer over Wuhan

Neural networks (NNs) have been applied to ionospheric predictions recently. This paper uses radial basis function neural network (RBF-NN) to forecast hourly values of the ionospheric F₂ layer critical frequency(f_oF₂), over Wuhan (30.5N, 114.3E), China. The false nearest neighbor method is used to determine the embedding dimension, and the principal component analysis (PCA) is used to reduce noise and dimension. The whole study is based on a sample of about 26,000 observations of f_oF₂ with 1-h time resolution, derived during the period from January 1981 to December 1983. The performance of RBF-NN is estimated by calculating the normalized root-mean-squared (NRMSE) error, and its results show that short-term predictions of f_oF₂ are improved.     

Comparison of ionospheric F2 peak parameters foF2 and hmF2 with IRI2001 at Hainan

Monthly median values of foF2, hmF2 and M(3000)F2 parameters, with quarter-hourly time interval resolution for the diurnal variation, obtained with DPS4 digisonde at Hainan (19.5°N, 109.1°E; Geomagnetic coordinates: 178.95°E, 8.1°N) are used to investigate the low-latitude ionospheric variations and comparisons with the International Reference Ionosphere (IRI) model predictions. The data used for the present study covers the period from February 2002 to April 2007, which is characterized by a wide range of solar activity, ranging from high solar activity (2002) to low solar activity (2007). The results show that (1) Generally, IRI predictions follow well the diurnal and seasonal variation patterns of the experimental values of foF2, especially in the summer of 2002. However, there are systematic deviation between experimental values and IRI predictions with either CCIR or URSI coefficients. Generally IRI model greatly underestimate the values of foF2 from about noon to sunrise of next day, especially in the afternoon, and slightly overestimate them from sunrise to about noon. It seems that there are bigger deviations between IRI Model predictions and the experimental observations for the moderate solar activity. (2) Generally the IRI-predicted hmF2 values using CCIR M(3000)F2 option shows a poor agreement with the experimental results, but there is a relatively good agreement in summer at low solar activity. The deviation between the IRI-predicted hmF2 using CCIR M(3000)F2 and observed hmF2 is bigger from noon to sunset and around sunrise especially at high solar activity. The occurrence time of hmF2 peak (about 1200 LT) of the IRI model predictions is earlier than that of observations (around 1500 LT). The agreement between the IRI hmF2 obtained with the measured M(3000)F2 and the observed hmF2 is very good except that IRI overestimates slightly hmF2 in the daytime in summer at high solar activity and underestimates it in the nighttime with lower values near sunrise at low solar activity.     

Tomographic reconstruction of the ionospheric electron density as a function of space and time

Electron density distribution is the major determining parameter of the ionosphere. Computerized Ionospheric Tomography (CIT) is a method to reconstruct ionospheric electron density image by computing Total Electron Content (TEC) values from the recorded Global Positioning Satellite System (GPS) signals. Due to the multi-scale variability of the ionosphere and inherent biases and errors in the computation of TEC, CIT constitutes an underdetermined ill-posed inverse problem. In this study, a novel Singular Value Decomposition (SVD) based CIT reconstruction technique is proposed for the imaging of electron density in both space (latitude, longitude, altitude) and time. The underlying model is obtained from International Reference Ionosphere (IRI) and the necessary measurements are obtained from earth based and satellite based GPS recordings. Based on the IRI-2007 model, a basis is formed by SVD for the required location and the time of interest. Selecting the first few basis vectors corresponding to the most significant singular values, the 3-D CIT is formulated as a weighted least squares estimation problem of the basis coefficients. By providing significant regularization to the tomographic inversion problem with limited projections, the proposed technique provides robust and reliable 3-D reconstructions of ionospheric electron density.