Field-based landcover classification using TerraSAR-X texture analysis

The present study aims to evaluate the field-based approach for the classification of landcover using high-resolution SAR data. TerraSAR-X (TSX) strip mode imagery, coupled with digital ortho-photos (DOPs) with 20 cm spatial resolution was used for landcover classification and parcel mapping respectively. Different filtering and analysis techniques were applied to extract textural information from the TSX image in order to assess the enhancement of the classification accuracy. Several attributes of parcels were derived from the available TSX images in order to define the most suitable parameters discriminating between different landcover types. Then, these attributes were further statistically analysed in order to define separability and thresholds between different landcover types. The results showed that textural analysis resulted in high classification accuracy. Hence, this paper confirms that integrated landcover classification using the textural information of TerraSAR-X has a high potential for landcover mapping.     

基于状态条件概率的设备剩余寿命预测

针对机载设备剩余使用寿命预测中存在的不确定性因素,建立了基于状态条件概率分布的机载设备剩余寿命模型.首先,引入状态条件概率矢量对隐马尔科夫模型（HMM,Hidden Markov Model）进行不确定性改进,并推导了其计算形式.其次,给出了近似确定状态退化转移时间的方法,由此得到了以状态条件概率矢量为协变量的条件可靠度函数及剩余寿命模型.最后,以飞机发动机温控放大器为应用对象进行仿真计算.仿真结果表明该模型预测精度高,能够较大程度地降低不确定性因素的影响.      

基于多波长同轴数字全息的相位恢复算法

同轴数字全息中固有的共轭像问题会严重影响再现像质量,已有的相位恢复算法需要大量计算才能祛除共轭像,且无法获得连续分布的解包裹相位像。提出一种基于多波长的相位恢复算法,该算法利用4个波长下记录的数字全息图,并在迭代过程中借助光学解包裹原理扩展了测量范围,实现了再现成像面中共轭像祛除的同时获得解包裹的相位分布。同时,由于在物面及记录面添加了约束条件,该方法中所用波长数少于其他已提出的基于多波长原理的相位恢复算法,而且具有更快的迭代收敛速度和更好的共轭像祛除效果。数值仿真和实验结果皆证明了该方法的有效性。      

A robust object-based shadow detection method for cloud-free high resolution satellite images over urban areas and water bodies

Unwanted contrast in high resolution satellite images such as shadow areas directly affects the result of further processing in urban remote sensing images. Detecting and finding the precise position of shadows is critical in different remote sensing processing chains such as change detection, image classification and digital elevation model generation from stereo images. The spectral similarity between shadow areas, water bodies, and some dark asphalt roads makes the development of robust shadow detection algorithms challenging. In addition, most of the existing methods work on pixel-level and neglect the contextual information contained in neighboring pixels. In this paper, a new object-based shadow detection framework is introduced. In the proposed method a pixel-level shadow mask is built by extending established thresholding methods with a new C₄ index which enables to solve the ambiguity of shadow and water bodies. Then the pixel-based results are further processed in an object-based majority analysis to detect the final shadow objects. Four different high resolution satellite images are used to validate this new approach. The result shows the superiority of the proposed method over some state-of-the-art shadow detection method with an average of 96% in F-measure.     

基于H_∞估计的鲁棒故障检测

为了减少故障误警率和提高故障检测精度 ,文章利用H∞ 估计和优化理论研究了线性离散不确定系统的故障检测问题。故障检测的关键是使余量发生器产生的余量对不确定因素和干扰输入具有鲁棒性 ,同时对故障具有敏感性。另外 ,文中还讨论了门限值的计算和选择问题。最后 ,仿真计算了在模型不确定性和随机干扰情况下 ,某飞行器传感器 /执行器故障的检测过程。与基于卡尔曼滤波的方法比较 ,基于H∞ 估计的故障检测方法能有效降低误警率。     

一种复杂场景下的人眼检测算法

针对复杂场景下的人眼检测问题，间接方法和直接方法具有一定的局限性。提出了一种不依赖人脸检测的直接型人眼检测算法，以解决复杂场景下多尺度尤其是小尺度人眼检测问题。算法通过减少下采样因子并加入扩张残差单元以提升小尺度人眼检测能力，且对多尺度特征相互拼接以保证多尺度人眼检测的精度。同时，算法借助于压缩特征输出通道降低了模型复杂度，使人眼检测效率得以提升。实验结果表明:所提模型可以在小尺度下有效地进行左右眼区分，并在红外数据上表现良好。经在DIF数据集上进行训练与测试，所提模型在较小尺度下人眼检测精度达到82.59%，检测效率达到30.5 fps。      

基于时频分析的电离层多模污染抑制研究

研究高分辨线性时频分析方法和联合时频分析方法，利用这两种方法对高频电离层返回散射探测的多个传播模式实测数据，对污染抑制效果进行分析.结果显示，这两种基于时频分析的方法针对多模和相位污染同时存在的复杂情况，与其他常规方法相比均使杂波谱得到了较好的锐化，目标信号在二维时频域较清楚地显出.因此可以证明，上述两种方法具有很高的应用价值，对天波超视距雷达海上低速目标检测具有重要意义.      

基于ARM的数字电感传感器设计CSCD

针对传统金属探测方法的缺点,提出数字电感探测法。基于电涡流原理,采用先进的数字电感转换器LDC1000做为传感器,通过前端自制印制板电感线圈检测金属,通过计算将测量结果转换为数字量,经串行外设接口(以下简称SPI)与高性能ARM处理器Cortex-M4相连,可实现高速、高精度金属测量。实测结果表明:本传感器克服了传统电感测量方法抗干扰能力差、模拟接口、精度低的缺点,实现了数据采集的高速、可靠,并使测量精度提高到亚微米级,可实现对金属物距离、角度、运动、位移、压缩等的高精度测量。     

An optimization approach for observation association with systemic uncertainty applied to electro-optical systems

The observation to observation measurement association problem for dynamical systems can be addressed by determining if the uncertain admissible regions produced from each observation have one or more points of intersection in state space. An observation association method is developed which uses an optimization based approach to identify local Mahalanobis distance minima in state space between two uncertain admissible regions. A binary hypothesis test with a selected false alarm rate is used to assess the probability that an intersection exists at the point(s) of minimum distance. The systemic uncertainties, such as measurement uncertainties, timing errors, and other parameter errors, define a distribution about a state estimate located at the local Mahalanobis distance minima. If local minima do not exist, then the observations are not associated. The proposed method utilizes an optimization approach defined on a reduced dimension state space to reduce the computational load of the algorithm. The efficacy and efficiency of the proposed method is demonstrated on observation data collected from the Georgia Tech Space Object Research Telescope.     

压电柔性结构振动的鲁棒控制

针对具有多面体型参数不确定性和外界扰动的柔性悬臂梁系统,研究其振动的鲁棒控制问题.基于压电柔性悬臂梁系统的状态方程,利用一种扩展LMI(Linear Matrix Inequality),对柔性悬臂梁的振动提出了改进的 H₂/H_∞ 综合状态反馈鲁棒控制方法.此方法针对多面体型参数不确定性系统引入不同的Lyapunov函数,降低了原来 H₂/H_∞ 综合鲁棒控制方法中由于使用一个公共Lyapunov函数而产生的保守性.通过Matlab分别采用改进和未改进的 H₂/H_∞ 鲁棒控制方法对柔性悬臂梁系统的振动控制进行了数值仿真.仿真结果表明,2种方法都使柔性悬臂梁的振动得到了良好控制,而改进方法的控制效果更好.     

基于机器视觉的万用表数字识别技术研究

为提高手持式数字万用表校准系统的自动化水平，本文通过研究图像灰度阈值法、传统方法的目标分类和深度学习三种不同类型的字符识别技术，提出了两种基于机器视觉的数字识别方案。测试结果显示，两种方案的字符识别准确率均可达到99.8%，但其在硬件资源占比、编程难易程度上二者还存在显著差异。该机器视觉字符识别功能的成功开发与应用，可为更多无程控通信接口的计量测试设备，及一些不适于人工作业的危险计量工作环境进行类似的数字识别提供借鉴。     

遥测帧码数字相关检测器的神经网络实现

建立了一种利用遥测最佳帧同步码的符合度特征和多比特观测窗 数字相关检测器模型，基于模糊利用神经网络实现了这种数字相关检测器，它对帧码出现的误码的码元滑动的情况均有较高的检测率，实现结果主宰了这些结论。     

知识与数据融合的可靠性定量模型建模方法

可靠性定量设计的关键是建立可靠性定量模型。现有的可靠性定量模型建模方法主要基于设计人员对产品对象故障规律的知识,包括故障模式、环境扰动、故障机理等。但知识固有的有限性和不完整性必然会给可靠性定量模型带来模型误差和输入参数的不确定性。针对这个问题,提出了基于贝叶斯理论融合知识和数据的可靠性定量模型建模方法,量化并更新模型误差和输入参数的不确定性。为此,首先说明了知识与数据融合的可靠性定量模型建模工作,建立了知识与数据融合的可靠性定量模型建模框架;接着阐述了基于贝叶斯理论的知识与数据融合原理;然后介绍了基于贝叶斯理论融合知识与数据的通用方法,并分别针对性能波动数据和性能退化数据2种常见数据类型进一步详细讨论了各自适用的贝叶斯融合方法;最后通过机载轴向柱塞泵的案例验证了前述方法的可行性和有效性。      

Uncertainty-aware Cube algorithm for medium-term collision risk assessment

The number of Earth orbiting objects is constantly growing, and some orbital regions are becoming risky environments for space assets of interest, which are increasingly threatened by accidental collisions with other objects, especially in Low-Earth Orbit (LEO). Collision risk assessment is performed by various methods, both covariance and non-covariance based. The Cube algorithm is a non-covariance-based method used to estimate the collision rates between space objects, whose concept consists in dividing the space in cubes of fixed dimension and, at each time instant, checking if two or more objects share the same cube. Up to now its application has been limited to the long-term scenarios of orbital debris evolutionary models, where considering the uncertainties is not necessary and impractical. Within operative contexts, instead, medium-term collision risk analysis may be an important task, in which the propagation-related uncertainties play a prominent role, but the timescale poses challenges for the application of standard covariance-based conjunction analysis techniques. In this framework, this paper presents an approach for the evaluation of the medium-term collision frequency for objects in LEO, called Uncertainty-aware Cube method. It is a modified version of the Cube, able to take the possible errors in the space objects’ position into account for the detection of the conjunctions. As an object’s orbit is propagated, the along-track position error grows more and more, and each object could potentially be in a different position with respect to the one determined by numerical propagation and, thus, in a different cube. Considering the uncertainties, at each time instant the algorithm associates more than one cube to each object and checks if they share at least one cube. If so, a conjunction is detected and a degree of confidence is evaluated. The performance of the method is assessed in different LEO scenarios and compared to the original Cube method.     

GPS数字接收机中C/A码搜索算法与实现

从GPS信号结构出发,介绍了GPS时域/频域的二维序贯搜索原理.在虚警概率、检测概率与搜索速率分析的基础上,对几种序贯搜索方法性能进行了比较,提出并以实验验证了以并行12通道扩频相关器为基础的GPS C/A码捕获数字系统实现方案,改进的搜索算法的采用有效地缩短了码平均捕获时间并提高了捕获的可靠性,并成功地应用于GPS数字接收机中.     

用于遥感图像变化检测的全尺度特征聚合网络

变化检测(CD)是遥感的一项重要任务，通常面临许多伪变化和较大的尺度变化。目前的方法主要侧重于对差异特征的建模，忽略了从原始图像中提取足够的信息，影响了特征的识别能力，难以稳定地区分出变化区域。针对以上问题，提出了一种全尺度特征聚合网络(FFANet)来更充分地利用原始图像特征，促使生成的特征表示在语义上更丰富、在空间上更准确，从而提高了网络对小目标和目标边缘的检测性能。同时，拓展了深监督来结合多尺度的预测图，以促使不同对象在更合适的尺度上进行检测，从而提升了网络对对象尺度变化的鲁棒性。在CDD数据集上，相比于基线网络，所提方法仅增加了1.01×106的参数量，就将F₁分数提升了0.034。      

基于Rao-Blackwellized蒙特卡罗数据关联的检测跟踪联合优化

提出了基于Rao-Blackwellized蒙特卡罗数据关联的雷达目标检测跟踪联合优化算法。Rao-Blackwellization方法将单目标跟踪与数据关联分开处理,将序贯蒙特卡罗方法（粒子滤波）用于数据关联,实现杂波与虚警量测中的多目标跟踪。同时,根据粒子的分布范围确定波门大小。在考虑粒子权重的前提下,利用检测单元与所有粒子的相对位置对检测门限进行修正,提高检测率。将本文算法与已经实现的基于空域特性的杂波抑制算法相结合,分别应用于仿真数据、S波段相参与非相参雷达实测数据。实验结果表明,本文算法能够在粒子数较少的情况下,实现对小弱目标的检测与跟踪。      

基于准静态拉伸试验的临界CTOA测量

为了寻求更为简单、准确的临界裂纹尖端张开角（CTOA_c）测量方法以推广CTOA准则的应用,本文对材料CTOA_c的测量方法进行了研究。根据CTOA的性质及G?teborgs Kungliga Segel S?llskap（GKSS）提出的CTOA_c估算方法导出了两种不同裂纹尖端张开位移（CTOD）定义之间的关系,并进一步得到一种基于准静态拉伸试验的CTOA_c测量方法,该方法与GKSS提出的估算方法相等效但更加简单。为了验证准静态拉伸试验法的准确性,对7B04 M（T）试样进行了静态拉伸试验,并使用上述两种方法估算7B04的CTOA_c,结果表明两种方法估算出的CTOA_c仅相差1%。同时分别采用平面应变核模型、平面应力模型对试样进行了弹塑性有限元模拟,模拟结果与试验结果相吻合。      

基于ADS-B的航空器测高系统误差评估方法

针对基于广播式自动相关监视(ADS-B)数据的航空器高度保持性能监控中测高系统误差准确评估问题,提出了基于核平滑和混合正态分布模型的数据平滑和拟合分析方法。提出了ADS-B信息低分辨率高度数据的核平滑方法,通过比较分析得到了数据平滑的最优窗宽,基于实测数据的分析证明了该方法对于航空器测高系统误差评价的有效性。针对航空器使用的2套独立的测高学设备具有不同的高度保持性能分布特征的问题,提出了基于混合正态分布模型的拟合分析方法,实测结果表明,该方法可以准确拟合航空器测高系统误差的双峰特征。本文所提出的方法已经在中国RVSM航空器高度保持性能的实际分析中使用,分析结果满足国际民航组织的相关要求。