对数零相位谱在雷达目标识别中的应用研究

高分辨距离像的频谱相位包含了大部分目标信息,对数零相位谱特征能够保留这些信息,且具有平移不变性。提出一种对数零相位谱最小距离雷达目标识别方法,并利用外场实测数据计算仿真,比较了最小欧氏距离与最小马氏距离准则下对数零相位谱的识别性能,同时与功率谱、幅度谱做对比,验证了该方法的可行性与有效性。     

基于短板效应的网络对抗效果研究

从网络空间和作战空间的映射关系出发,提出了一种＂基于短板效应的网络可达度＂的网络中心战度量准则,对度量指标进行了定义并构建了相应的度量模型。运用该准则对作战网络的对抗效果进行了仿真分析。结果表明,作战网络的对抗效果主要取决于网络中关键节点及其链路的有效性。     

双星编队星座相对状态自主确定

针对NASA的ST-3中自主编队飞行的双星星座，研究在无GPS信号覆盖区域，利用星载类GPS的伪距和载波观测数据自主确定双星星座之间相对位置与钟差的问题。文中首先给出了系统的数学模型；然后研究利用卫星姿态机动提供的几何信息，进行单差整周模糊度初始化的问题，讨论了最优化的卫星姿态机动方案；最后给出了仿真协方差分析结果。     

在轨服务系统评估方案研究

在轨服务系统是复杂的空间应用系统,直观、有效的评估方法将对该系统总体研究工作以及今后的任务实施起到重要的指导作用.为对在轨服务系统完成任务的能力做出科学合理的评估,在把握相关领域技术发展的前提下,建立了在轨服务系统综合效能评估指标体系.运用层次分析法和灵敏度分析的思路.研究了在轨服务系统效能评估方法,为在轨服务系统的建设提供理论参考.     

基于相位差变化率的单站无源跟踪算法研究

利用机载观测站与辐射源之间的相对运动信息,在方位角测量的基础上增加相位差变化率的测量,可以对固定目标实现即时定位,为了提高精度,需要利用滤波算法进行跟踪滤波.在机载单站无源定位原理研究的基础上,通过计算机仿真分析了该定位方法下KF、EKF和MVEKF多种滤波算法的性能,对工程应用具有一定的参考意义.     

线阵CCD成像仿真研究

文章根据空间遥感用CCD(Charge-Coupled Devices)探测器的工作原理,研究了CCD成像仿真的数学模型,设计了一套完整的CCD成像模型,并研究了像元响应不一致性、电荷扩散、暗电流噪声等参数的分布特性.仿真试验表明,该模型仿真结果与实际器件的相关测量参数吻合度较高,与系统的MTF和S/R测试结果一致,准确度较高.     

基于MSC.Fatigue的电子设备随机振动疲劳分析

针对机载电子设备随机振动问题,研究利用数字仿真技术预测结构随机振动疲劳寿命的方法.以某机载电子设备结构为研究对象,根据随机振动理论和有限单元法,采用MSC.Fatigue软件进行随机振动疲劳分析,计算疲劳寿命大小及分布.通过把计算结果与试验结果进行对比,证明利用随机振动疲劳分析方法预测此类产品的疲劳寿命是可行的.     

农林飞机近地作业飞行的横航向稳定特性

 分析了地面效应对飞机产生附加滚转和偏航力矩的气动新机理,研究了农林飞机近地作业飞行时横航向气动特性随高度的变化规律,推导了考虑地面效应影响时的飞机横航向静稳定性新准则,并分析了不同飞行高度时这些静稳定性的变化趋势。采用地效区内飞机的运动方程,计算并分析了农林飞机不同作业高度下的横航向模态特性及变化规律,并进行了模态特性的简化和验证分析。     

Improved robust Kalman filter for state model errors in GNSS-PPP/MEMS-IMU double state integrated navigation

The integration of Global Navigation Satellite System (GNSS) with Inertial Navigation Systems (INS) has been actively researched and widely applied as it can provide reliable positioning information continuously. In recent years, Micro Electro Mechanical Systems (MEMS) technology achieves rapid development and Micro Electro Mechanical Systems and Inertial Measurement Unit (MEMS-IMU) has aroused wide concern due to its excellent properties in some cases. However, the observations from MEMS-IMU are easy to be influenced by motion state and location environment because of its manufacturing process. It is not easy to judge whether gross errors are in the state model or the observation model by the widely adopted robust filter based on innovation. In this contribution, we present an improved robust filter with a double state model on the basis of the chi-square distribution of the square of the Mahalanobis distance. The vehicle motion model acts as the external constraint information and can be adopted to construct robust statistic with the results from INS mechanization. And then a robust factor was determined to adjust the observation noise covariance matrix. To evaluate the performance of this method, the simulation test and the field test based on locomotive platform of Nottingham Geospatial Institute (NGI) were carried out. According to the results, in the simulation test, the position improvements are 33%, 30% in the north and east directions; in the real test, the loosely and tightly coupled was adopted and the position accuracy can be improved by about 50–60% in the horizontal direction and the improvement of the pitch and the roll accuracy was lower than the azimuth accuracy due to poor observability and experimental scene which is of the characteristics of small elevation change. Therefore, the proposed robust filter could diminish the effect of the gross error from MEMS-IMU and enhance the integrated system.