Direct position determination using single moving rotating linear array: Noncoherent and coherent processing

To improve the resolution and accuracy of Direct Position Determination (DPD), this paper investigates the problem of positioning multiple emitters directly with a single moving Rotating Linear Array (RLA). Firstly, the geometry of the RLA is formulated and analysed. According to its geometry, the intercepted noncoherent signals in multiple interception intervals are modeled. Correspondingly, the MUltiple SIgnal Classification (MUSIC) based noncoherent DPD approach is proposed. Secondly, the synchronous coherent pulse signals are individually considered and formulated. And the coherent DPD approach which aims for localizing this special type of signal is presented by stacking all array responses at different interception intervals. Besides, we also derive the constrained Cramér-Rao Lower Bound (CRLB) expression for both noncoherent and coherent DPD with RLA under the constraint that the altitudes of the emitters are known. At last, computer simulations are included to examine the performance of the proposed approach. The results demonstrate that the localization accuracy and resolution of DPD with single moving linear array can be significantly improved by the array rotation. In addition, coherent DPD with RLA further improves the resolution and increases the maximum emitter number that can be localized compared with the noncoherent DPD with RLA.     

Assessment study of ionosphere correction model using single- and multi-shell algorithms approach over sub-Saharan African region

It is a known fact that ionosphere is the largest and the least predictable among the sources of error limiting the reliability and accuracy of Global Navigation Satellite Systems (GNSS) and its regional augmentation systems like Satellite Based Augmentation System (SBAS) in a safety-of-life application. The situation becomes worse in the Equatorial Ionization Anomaly (EIA) region, where the daytime ionization distribution is modified by the fountain effect that develops a crest of electron density at around ±15° to ±20° of the magnetic equator and a trough at the magnetic equator during the local noon hours. Related to this phenomenon is the appearance of ionosphere irregularities and plasma bubbles after local sunset. These may degrade further the quality of service obtained from the GNSS/SBAS system of the said periods. Considering the present operational augmentation systems, the accuracy and integrity of the ionosphere corrections estimate decreases as the level of disturbances increases. In order to provide a correct ionosphere correction to the user of GNSS operating in African EIA region and meet the integrity requirements, a certified ionosphere correction model that accurately characterizes EIA gradient with the full capacity to over-bound the residual error will be needed. An irregularities detector and a decorrelation adaptor are essential in an algorithm usable for African sub-Saharan SBAS operation. The algorithm should be able to cater to the equatorial plasma vertical drifts, diurnal and seasonal variability of the ionosphere electron density and also should take into account the large spatial and temporal gradients in the region. This study presents the assessment of the ionosphere threat model with single and multi-layer algorithm, using modified planar fit and Kriging approaches.     

一种地理围栏内无人机航迹跟踪方法

针对UTM体制中无人机在地理围栏内的飞行监视问题,提出一种约束状态相关模态转换混合估计算法(CSDTHE)。采用随机线性混杂系统模型对无人机运动状态进行建模,利用CV、CT和CA三种模态描述无人机的飞行状态,以构建地理围栏内无人机运行的通用模态转换模型框架。利用飞行模态改变点(FMCP)定义相关模态转换参数,设计模态转换条件,生成模态转换概率矩阵,从而建立与状态相关的模态转换模型。运用约束卡尔曼滤波(CKF)方法对直线阶段和转弯阶段的无人机运动速度分别施加等式约束,并通过仿真实验验证了CSDTHE算法对无人机跟踪的有效性。     

基于改进的卷积神经网络的步态识别

为了提高惯性传感器采集到的序列数据中步态识别的准确率,建立了一个激励层改进的卷积神经网络(CNN)模型。针对三轴加速度传感器对运动太过敏感导致步态周期划分不准确的问题,采用加速度传感器与弯曲度传感器组合获取人体运动信息。将CNN模型中激励层的线性整流函数(ReLU)改进为带泄露线性整流函数(Leaky ReLU),以解决遇到卷积输出数据小于0时神经元被抑制的问题,进而达到提高步态识别准确率的目的。实验结果表明激励层优化的CNN模型在行走、上下楼和上下坡五种步态模式下识别率达到了95.79%,与未采用弯曲度传感器的改进CNN模型和未进行激励层改进的CNN模型相比,步态识别率有所提高。     

基于 Kriging与多点取样算法的压气机特性建模

针对航空燃气轮机流量系数插值建模过程中,获取样本数据时的实验成本较高以及插值模型精度偏低这 2个问题,根据样本点在设计空间中的分布与模型精度的关系,在 Kriging插值模型的基础上,采用把垂距作为设计变量取值标准的取样算法。首先,将样本点与相邻 2点之间连线的垂距与垂距阈值进行比较,筛选出符合条件的数据点,形成候选点集;其次,选用高斯函数判定基础点集和候选点集的相关性;最后,使用该算法筛选后的样本点构建 Kriging插值模型。实验结果表明,该方法使用的样本点为原来数量的 70%左右,并且预测精度得到了提高,该方法是有效可行的。     

空军武器装备系统作战效能评估方法探讨

空军武器装备系统,一般认为由飞机装备,雷达装备和防空武器装备三大部分组成,对于单一武器装备的作战效能的分析方法,已有很多相关理论,对于上述三个部分构成的武器装备（总）系统的作战效能的评估方法,采用什么样的数字模型,进行哪些方面的判断决策,如何根据蓝方现有（或假想）武器装备对应求解红方现有（或假想）武器装备的最优配置方案等等,是本文所要讨论的问题。     

交互外形设计中的有理插值方法

在CAGD中,构造光滑曲线通过给定的二维或三维点集是非常重要的问题。广泛釆用的方法是Hermite技术,但是依照这种方法,插值曲线的形状过多地依赖于切矢的模长,且形状的修改不能依几何的方式交互完成。本文提出了一种结合交互技术和插值技术于一体的曲线插值方法,插值基函数为有理函数,在此基础上讨论了形状参数在几何修形中的作用,     

用TH神经网络方法外推数据的超分辨雷达成象

研究用Ｔａｎｋ－Ｈｏｐｆｉｅｌｄ神经网络（ＴＨＮＮ）求解ＡＲ模型参数作数据外推的超分辨雷达成象,并用微波暗室实测数据对ＴＨＮＮ方法和Ｂｕｒｇ方法作了验证,结果表明,两种方法均能在较低的信噪比条件下实现超分辨成象,且随着ＶＬＳＩ技术的发展,神经网络方法将是一种很有希望的超分辨成象方法。     

超分辨成象信号处理的硬件实现

简要介绍线性预测数据外推的超分辨距离－多普勒成象方法,并以一片高速数字信号处理（ＤＳＰ）芯片—ＴＭＳ３２０Ｃ２５为核心设计了一个专用信号处理器,能完成数据外推、加窗和１２８复数点ＦＦＴ,实现超分辨二维成象。文中给出了对Ｂ－５２模型飞机微波暗室转台实测数据的成象结果,并作了比较。     

材料非线性对复合材料层板损伤的影响

根据Hahn-Tsai非线性应力应变关系,用有限元方法对受拉伸载荷作用的含孔复合材料层板损伤演变进行了模拟计算,由非线性有限元方法得到的应力、应变以及最终载荷与以往线性分析方法得到的结果比较表明:考虑材料非线性可以提高计算精度;参数研究表明非线性系数的变化对正交各向异性板的影响较大,而对准各向同性板的影响较少.