Modeling the ionospheric gradient by using VSS base functions and GPS data over Iran

The spatial and temporal variations of ionosphere play an important role in positioning and navigation by the space geodetic techniques. Therefore, the ionospheric gradient should be calculated, analyzed, and applied in both space and time. Spatial gradients of the ionosphere have remarkable delay on the propagation of electromagnetic waves. This study intends to propose a new method for simultaneous modeling of the spatial gradients of ionosphere and VTECs in the local scale for Iran. Vector Spherical Slepian (VSS) base functions are used for the development of this method.Five VSS models with the maximal degrees of L = 30, 35, 40, 45 and 50 are taken into account. For implementing the VSS method, 24 permanent GPS stations from the Iranian Permanent GPS Network (IPGN) have been used. The unknown coefficients are estimated with the observations of these stations with least squares technique. Four other stations are used for evaluating the accuracy of the models. Repeatability of baselines is the measure that is used for this purpose. Based on the results obtained, L = 40 is the optimum degree for the VSS model with this input data over Iran.The baselines’ repeatability showed that ionospheric gradients have more influence on the north–south component. Moreover, the spatial gradient is negligible in the east–west and up-down component when a short baseline is processed. In other words, this kind of ionospheric modeling has significant application for baseline, which is longer than 1000 km. In the study, proposed method has improved the long baselines' solution by more than 12%, 18% and 10% in east–west, north–south and up-down components, respectively.     

飞行器最优末制导律的自适应PID滑模设计

针对传统最优末制导律作用下再入飞行器易受外界因素干扰和气动力变化的影响,致使命中精度较低、鲁棒性较差的问题,在弹目运动方程存在参数不确定性情况下,提出一种基于自适应PID滑模扰动观测器技术的鲁棒最优末制导律。其中滑模扰动观测器能够在线消除系统扰动影响,而自适应PID滑模可以有效去除抖振。基于Lyapunov稳定性理论的证明过程及数值仿真结果均表明,该末制导律不仅使飞行器各项性能指标均达到指标要求,并且保证了较高的命中精度和较强的鲁棒性。     

一种针对恒模信号的运动单站直接定位算法

相比于常规的"测向+位置估计"两步定位模式,以Weiss等提出的目标直接位置确定(DPD)算法具有估计精度高、分辨能力强和无需数据关联等诸多优点。基于该类定位算法的基本理念,提出了一种利用单个运动天线阵列对恒模(即相位调制)信号的DPD算法。首先,依据最大似然(ML)准则以及恒模信号的恒包络特征,建立了相应的直接定位优化模型;接着,根据优化函数的代数特征提出了一种有效的多参量交替迭代算法,用以获得ML估计器的最优数值解;此外,推导了针对恒模信源的位置直接估计方差的克拉美罗界(CRB),从而为新算法的定位精度提供定量的理论下界。仿真实验表明:相比于已有的基于单个运动天线阵列的直接定位算法以及传统的两步定位算法,通过利用恒模信号的恒包络特征可以明显提高目标直接定位的估计精度。     

Whole-process modeling of titanium disc forming for gradient distributions of temperature and deformation

Gradient distributions of temperature and deformation (GDTD) are crucial for achieving dual-performance discs of titanium alloys which is required by the service environment of aeroengine. However, heating, cooling and deforming sequence in the whole process of the titanium disc forming, which leads to difficulties for achieving GDTD due to a lot of parameters. To solve this problem, a whole-process model of the titanium disc forming for GDTD has been established. In the model, heating and cooling via heat radiation, conduction and convection, and deforming by local loading with mold chilling are all considered. Experiments on heating and cooling as well as deforming were carried out by using a furnace and the Gleeble-3500 machine. The experimental data are used to determine thermal parameters and constitutive relations of the IMI834 titanium alloy, and then to verify the reliability of the model. Then the model was used to simulate the evolution rules of temperature and deformation of the titanium disc. The results show that the heating surface, furnace temperature, billet profile and loading rate play the core role for the control of GDTD, and thus a set of parameters were determined. Therefore, this work provides a base for developing a new forming technology of the dual-performance titanium discs with the approach of local heating and local loading.     

一种用于目标跟踪的UT-BLUE滤波方法

雷达机动目标跟踪问题中,通常目标运动模型可精确地在直角坐标系下建模,但大多数情形下模型是非线性的,同时在传感器坐标系下所获得目标量测又是直接可用的.通过将无迹变换与最优线性无偏滤波器有机结合,提出一种新的BLUE(Best Linear Unbiased Estimator) 滤波算法,以便解决上述非线性跟踪问题.首先,该算法利用无迹变换对经由直角坐标系下非线性目标运动模型得到的目标状态及其协方差作出预测,然后在保持传感器坐标系(极坐标系)下所固有的量测误差的同时,直接对它们作出状态估计.在算法推导及Monte-Carlo仿真过程中,将新的BLUE滤波算法和EKF(Extended Kalman Filter)、UKF(Unscented Kalman Filter)滤波算法进行比较,结果表明新算法的有效性和适用性.      

抗磁性物质磁悬浮方法在空间生物学与生物技术中的应用

失重是特定空间运动条件下的重要环境物理特征之一, 一般以微重力环境来表示. 几十年来人类利用空间失重环境进行了多学科领域的科学研究与探索. 由于真实空间失重环境下科学实验机会稀少, 人类为研究空间失重环境或效应, 开发了多种地基的空间模拟实验技术方法. 然而, 对于空间生物学和空间生物技术研究而言, 已有的各种模拟实验技术手段在原理上和应用上均存在一定的局限性. 本文介绍了抗磁性物质在大梯度强磁场中的悬浮现象, 及将其用于模拟空间失重环境的方法与原理;简述了近年来利用抗磁性物质悬浮方法进行生物大分子晶体生长、分子细胞生物学及整体生物学等方面研究与应用的进展.      

卫星太阳电池阵在轨故障统计及分析

文章针对2000年1月至2012年9月期间79颗在轨卫星发生的114次太阳电池阵故障事件进行了分类统计分析,并利用Kaplan-Meier估计量分析方法对这些在轨故障进行了可靠性分析。结果表明:太阳电池阵的故障多发生在卫星在轨第一年,其中电子类故障发生率较高;不同卫星平台的系统缺陷或设计共性问题也与太阳电池阵故障紧密相关。最后,结合我国卫星太阳电池阵设计及制造工艺技术,提出了加强出厂前的测试和试验验证、加强仿真建模、加强冗余设计等建议。     

一种基于高阶统计量的SAR图像自聚焦算法

 提出了一种基于高阶统计量分析的相位误差估计算法,用于SAR 图像自聚焦。该算法从复图像域出发,通过循环移位及加窗处理孤立强点目标,利用高阶累积量对高斯噪声的抑制能力,在距离压缩相位历史域估计相位误差。由于避免了对加性噪声及干扰很敏感的差分运算,相位误差的估计结果有很好的鲁棒性。仿真及实测数据的处理结果证明了该算法的可行性。     

化学镀SiC/Ni-P功能梯度材料工艺、组织及性能

通过对化学镀Ｎｉ－ Ｐ－ ＳｉＣ复合镀层的研究,找到了制备ＳｉＣ／Ｎｉ－ Ｐ 功能梯度材料（ＦＧＭ） 的工艺方法。并采用光学显微镜、电子探针分析仪及热震试验等方法和手段对功能梯度材料的组织、形貌、成分与镀层结合力进行了研究。结果表明,功能梯度材料中ＳｉＣ微粒以弥散状态沿镀层厚度方向呈梯度分布,无团聚结块现象,材料致密,组织细小。功能梯度材料较单层Ｎｉ－ Ｐ－ ＳｉＣ复合镀层以及Ｎｉ－ Ｐ／Ｎｉ－ Ｐ－ ＳｉＣ 双层镀层具有更好的结合强度。     

A data driven approach for detection and isolation of anomalies in a group of UAVs

The use of groups of unmanned aerial vehicles(UAVs) has greatly expanded UAV’s capabilities in a variety of applications, such as surveillance, searching and mapping. As the UAVs are operated as a team, it is important to detect and isolate the occurrence of anomalous aircraft in order to avoid collisions and other risks that would affect the safety of the team. In this paper, we present a data-driven approach to detect and isolate abnormal aircraft within a team of formatted flying aerial vehicles, which removes the requirements for the prior knowledge of the underlying dynamic model in conventional model-based fault detection algorithms. Based on the assumption that normal behaviored UAVs should share similar(dynamic) model parameters, we propose to firstly identify the model parameters for each aircraft of the team based on a sequence of input and output data pairs, and this is achieved by a novel sparse optimization technique. The fault states of the UAVs would be detected and isolated in the second step by identifying the change of model parameters.Simulation results have demonstrated the efficiency and flexibility of the proposed approach.