弹道导弹的雷达探测系统仿真

该文根据弹道理论建立了雷则弹道导弹的仿真模型,并对雷达跟踪的导弹弹道数据进行了处理,预报了它的落点范围,并与理论落点进行比较,给出了落点精度。仿真结果表明：雷达对导弹的探测数据经过一数据处理,所得到的落点比较精确。     

具有大旋翼一类旋转部件的雷达目标成像

由于目标本身或目标部件的振动和旋转运动而引入的微多普勒谱会对目标主体的ISAR像造成污染,严重时无法对目标主体进行成像。介绍了雷达目标回波信号中的微多普勒信号产生原理,提出了一种微多普勒信息分离与提取的方法,基于旋转部件的微多普勒谱与目标主体谱在谱图域表现形式的不同,将旋转部件的微多普勒谱与目标主体谱分离后获得了具有大旋转部件一类目标的清晰像,同时也获得了目标旋转部件的一些运动及结构信息。最后,仿真结果验证了此方法的有效性。     

预警雷达对弹道导弹目标的检测概率计算

预警雷达对弹道导弹目标的检测概率是影响弹道导弹防御系统作战效能的重要因素,是体现雷达预警性能的关键指标。该文结合导弹飞行仿真与雷达预警探测仿真两个领域,通过弹道导弹运动、目标RCS计算、雷达探测信噪比与雷达检测概率讨。算等数学模型,构建了预警雷达的预警功能仿真模型。采用导弹与预警雷达间的相对距离、速度与电磁入射角等交互参数,针对不同突防弹道的弹道导弹目标,对预警雷达检测概率进行了计算分析。仿真结果表明,采用该方法能够准确计算预警雷达对弹道导弹的检测概率与预警时间,满足导弹突防能力评估与雷达作战效能评估的需要。     

Precise recognition of warhead and decoy based on components of micro-Doppler frequency curves

From the view of electromagnetic scattering,it is indicated that the micro-Doppler (m-D) character-istics of an extended target undergoing micro-motions are actually induced by the change of incident directions of radar pulses.Different micro-motions may lead to similar change of incident directions,consequently inducing similar m-D characteristics.To tackle this problem,rather than distinguish warhead and decoy directly from m-D characteristics,the frequency components of m-D frequency curves are used as a new characteristic for recognition in this paper.To get high precision of frequency components estimation,model-based parameter estimation (MBPE) is utilized to extract the m-D frequency curves from TFR.To obtain high accurate simu-lation results,the backscattered signal simulation is conducted by full-wave numerical method.The simulation results validate the theoretical analysis and the high performance of the proposed method.     

基于自适应和最优特征的合成孔径雷达舰船检测方法

针对合成孔径雷达(SAR)目标舰船检测中对小目标检测效果不佳的问题,提出一种自适应锚框单阶段舰船检测方法.首先,在单阶段无锚框特征选择(FSAF)算法的基础上利用神经架构搜索(NAS)得到最优特征融合方式,以充分利用图像特征信息;然后提出新的损失函数,在解决正负样本不均衡的同时使网络能够更加精确地对位置进行回归;最后结...     

基于姿态估计的安全帽佩戴检测方法研究

针对现有安全帽佩戴检测方法在施工人员复杂姿态下检测难度大、精度不高的问题,提出一种基于姿态估计的安全帽佩戴检测方法。该方法在OpenPose姿态估计模型中引入残差网络优化特征提取,获得施工人员的骨骼点信息,并提出三点定位法,通过骨骼点位置信息确定头部区域以缩小检测范围。使用RetinaNet检测头部区域安全帽的佩戴情况,以解决安全帽与施工背景之间类极不平衡的问题。实验表明,该方法在检测精度上较其他方法有明显提高,并且对环境的适应性更强。     

Feature analysis for discriminative confidence estimation in spoken term detection

Discriminative confidence based on multi-layer perceptrons (MLPs) and multiple features has shown significant advantage compared to the widely used lattice-based confidence in spoken term detection (STD). Although the MLP-based framework can handle any features derived from a multitude of sources, choosing all possible features may lead to over complex models and hence less generality. In this paper, we design an extensive set of features and analyze their contribution to STD individually and as a group. The main goal is to choose a small set of features that are sufficiently informative while keeping the model simple and generalizable. We employ two established models to conduct the analysis: one is linear regression which targets for the most relevant features and the other is logistic linear regression which targets for the most discriminative features. We find the most informative features are comprised of those derived from diverse sources (ASR decoding, duration and lexical properties) and the two models deliver highly consistent feature ranks. STD experiments on both English and Spanish data demonstrate significant performance gains with the proposed feature sets.     

Water levels in the Amazon basin derived from the ERS 2 and ENVISAT radar altimetry missions

This study sets out to analyze the stages of water bodies in the Amazon basin derived from the processing of ERS-2 and ENVISAT satellite altimetry data. For ENVISAT, GDR measurements for both Ice-1 and Ice-2 tracking algorithms were tested. For ERS-2, the Ice-2 data produced by the OSCAR project was used. Water level time series over river segments of very different width, from several kilometers to less than a hundred of meters, were studied. The water level time series that can be derived from narrow riverbeds are enhanced by off-nadir detections. Conversely, the off-nadir effect may degrade the series over large bodies if not properly accounted for. Comparison at crossovers and with in situ gauges shows that the quality of the series can be highly variable, from 12 cm in the best cases and 40 cm in most cases to several meters in the worse cases. Cautious data selection is clearly a key point to achieve high quality series. Indeed, low quality series mostly result from inclusion of outliers in the data set finally retained for the computation of the series. Ice-2 and Ice-1 tracking algorithms in the ENVISAT data perform almost equally well. ENVISAT altimetry is clearly an improvement on ERS-2 altimetry.     

基于SVM与非参数LDA 的雷达自动目标识别

针对非参数线性判别分析（LDA）的类间散布矩阵，就如何有效描述类边界结构这一问题，提出一种SVM与k近邻（kNN）法相结合的非参数类间散布矩阵构造方法——SVM—kNN．该方法消除了非类边界样本对类边界结构信息的扭曲．将SVM—kNN非参数LDA方法用于外场实测高分辨距离像的特征提取，并将识别结果与加权kNN非参数LDA法和谱域原空间法比较，结果表明，SVM—kNN非参数LDA方法能显著提高识别效率．     

基于贝叶斯网的航拍图像建筑目标提取算法*

提出一种基于贝叶斯网的建筑目标提取算法。该算法通过多场景航拍图像进行训练后建立纹元字典,将实际图像中的纹元映射到纹元字典获得图像的场景类信息;然后使用朴素贝叶斯网建模建筑目标与场景类空间上下文的关系约束,将建筑目标提取转换为求解贝叶斯网类别节点的后验概率问题。与同类方法的对比实验表明,提出的算法能有效地提取航拍图像中的建筑目标。     

Non‐destructive recognition of dielectric coated conducting objects by using WD type time–frequency transformation and PCA‐based fusion

This article demonstrates the applications of a non‐destructive electromagnetic target recognition method, called Wigner distribution‐principal component analysis (WD‐PCA) method, to dielectric coated conducting spheres. These spheres are chosen to be highly similar having the same overall size but slightly different permittivity and thickness values in coating layers. Four different classifiers are simulated by using the WD‐PCA method for varying sizes of object libraries under different noise conditions. High correct decision rates are demonstrated even for challenging classifier libraries containing a large number of coated conductors while the method is also shown to be highly robust against noise both in design and test stages. © 2013 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2013.