Target-enclosing affine formation control of two-layer networked spacecraft with collision avoidance

This paper addresses a target-enclosing problem for multiple spacecraft systems by proposing a two-layer affine formation control strategy. Compared with the existing methods, the adopted two-layer network structure in this paper is generally directed, which is suitable for practical space missions. Firstly, distributed finite-time sliding-mode estimators and formation controllers in both layers are designed separately to improve the flexibility of the formation control system. By introducing the properties of affine transformation into formation control protocol design, the controllers can be used to track different time-varying target formation patterns. Besides, multi-layer time-varying encirclements can be achieved with particular shapes to surround the moving target. In the sequel, by integrating adaptive neural networks and specialized artificial potential functions into backstepping controllers, the problems of uncertain Euler-Lagrange models, collision avoidance as well as formation reconfiguration are solved simultaneously. The stability of the proposed controllers is verified by the Lyapunov direct method. Finally, two simulation examples of triangle formation and more complex hexagon formation are presented to illustrate the feasibility of the theoretical results.     

A multilayer perceptron and multiclass support vector machine based high accuracy technique for daily rainfall estimation from MSG SEVIRI data

The current paper introduces a new multilayer perceptron (MLP) and support vector machine (SVM) based approach to improve daily rainfall estimation from the Meteosat Second Generation (MSG) data. In this study, the precipitation is first detected and classified into convective and stratiform rain by two MLP models, and then four multi-class SVM algorithms were used for daily rainfall estimation. Relevant spectral and textural input features of the developed algorithms were derived from the spectral MSG SEVIRI radiometer channels. The models were trained using radar rainfall data set colected over north Algeria. Validation of the proposed daily rainfall estimation technique was performed by rain gauge network data set recorded over north Algeria. Thus, several statistical scores were calculated, such as correlation coefficient (r), root mean square error (RMSE), mean error (Bias), and mean absolute error (MAE). The findings given by: (r = 0.97, bias = 0.31 mm, RMSE = 2.20 mm and MAE = 1.07 mm), showed a quite satisfactory relationship between the estimation and the respective observed daily precipitation. Moreover, the comparison of the results with those of two advanced techniques based on random forests (RF) and weighted ‘k’ nearest neighbor (WkNN) showed higher accuracy obtained by the proposed model.     

Evaluating the statistical performance of less applied algorithms in classification of worldview-3 imagery data in an urbanized landscape

In recent decade, analyzing the remotely sensed imagery is considered as one of the most common and widely used procedures in the environmental studies. In this case, supervised image classification techniques play a central role. Hence, taking a high resolution Worldview-3 over a mixed urbanized landscape in Iran, three less applied image classification methods including Bagged CART, Stochastic gradient boosting model and Neural network with feature extraction were tested and compared with two prevalent methods: random forest and support vector machine with linear kernel. To do so, each method was run ten time and three validation techniques was used to estimate the accuracy statistics consist of cross validation, independent validation and validation with total of train data. Moreover, using ANOVA and Tukey test, statistical difference significance between the classification methods was significantly surveyed. In general, the results showed that random forest with marginal difference compared to Bagged CART and stochastic gradient boosting model is the best performing method whilst based on independent validation there was no significant difference between the performances of classification methods. It should be finally noted that neural network with feature extraction and linear support vector machine had better processing speed than other.     

飞行员头部特征分析及头型分类方法研究

通过对飞行员进行实地调查,发现目前装备的飞行头盔舒适度并不理想。由此,本文介绍了一种新的头部分析方案,借助光栅投影图像测量技术构建的飞行员头部三维模型,通过数值拟合方法分析获得飞行员的头部特征外形参数。同时按照统计学原理,根据头高、头宽、头长尺寸对飞行员的头型进行了科学地分类。本文描述的外形参数分析方法和头型分类方法可以用在今后大规模飞行员头部特征测量分析以及改进头盔设计的工作中。相关标准对今后头盔设计的改进工作有参考意义。     

A reflectance spectra-based approach to mapping salt fields using PCA-fused Landsat TM data

In this paper a method based on in situ measured reflectance spectra was developed for accurately mapping salt fields in the Taibei Salt Farm in Lianyungang City of East China. After radiometric correction and geometric rectification, six multispectral ETM+ bands were fused with the panchromatic band via principal components analysis (PCA). The fused data were used to map salt fields in the farm. Salt fields were mapped 91.95% correctly in comparison with ground statistics from raw multispectral bands. This accuracy level rose to 96.4% with the use of the panchromatic band (15 m resolution). However, PCA-fused data produced the highest accuracy of 98.8%. At the zone level, coarse resolution data resulted in an accuracy of 98.93% for crystallization ponds, but only 82.68% for condensation ponds. Use of the panchromatic band alone improved the accuracy for condensation ponds but decreased the accuracy for crystallization and evaporation ponds. Results derived from PCA-fused data are highly consistent with the ground statistics at a discrepancy between 0.35% for evaporation zone and 1.80% for condensation zone. It is concluded that a fine spectral resolution is important to separation of ponds of a varying salt content while a fine spatial resolution is important to their mapped area. Ponds of a lower salt content can be mapped more accurately from fused data than from raw spectral bands.     

基于Rician分布的SAR图像MRG目标提取算法

针对SAR图像特有的乘性噪声和非恒虚警统计特性很难正确提取目标的问题,本文提出了MRG算法对SAR目标进行检测。首先用MRF-ICM算法对SAR图像进行后向散射系数的复原,再在复原后的幅度上叠加相位信息后引入Rician分布寻找自适应的最佳局域Gabor滤波器参数对SAR图像进行目标提取。和以往的算法相比,MRG算法充分利用了SAR图像幅度和相位中所携带的信息,能更准确地提取目标。实验表明:该方法能取得很好的目标检测效果,后期提取出的目标更符合实际目标形态,具有较强的通用性。     

目标飞行器测控与通信分系统

介绍了目标飞行器测控与通信分系统的组成与功能。给出了USB、S波段数传、遥测、遥控、话音、图像、高速通信、空空通信和天线子系统的性能与特点。综述了研制中的可靠性设计与验证。     

红外精确制导系统对空中点目标的识别问题

利用目标本身辐射的红外能量,实现对运动目标状态的精确测量,是当前一种较为先进的精确制导技术。由于红外干扰及红外隐身技术的发展,在制导系统的分析设计中必须要考虑红外抗干扰的问题。本文主要讨论,当存在点源目标的干扰时,红外精确制导系统中实现目标识别和信息处理基本原则和步骤。     

Haze removal for UAV reconnaissance images using layered scattering model

During the unmanned aerial vehicles(UAV) reconnaissance missions in the middle-low troposphere, the reconnaissance images are blurred and degraded due to the scattering process of aerosol under fog, haze and other weather conditions, which reduce the image contrast and color fidelity. Considering the characteristics of UAV itself, this paper proposes a new algorithm for dehazing UAV reconnaissance images based on layered scattering model. The algorithm starts with the atmosphere scattering model, using the imaging distance, squint angle and other metadata acquired by the UAV. Based on the original model, a layered scattering model for dehazing is proposed. Considering the relationship between wave-length and extinction coefficient, the airlight intensity and extinction coefficient are calculated in the model. Finally, the restored images are obtained. In addition, a classification method based on Bayesian classification is used for classification of haze concentration of the image, avoiding the trouble of manual working. Then we evaluate the haze removal results according to both the subjective and objective criteria. The experimental results show that compared with the origin image, the comprehensive index of the image restored by our method increases by 282.84%, which proves that our method can obtain excellent dehazing effect.     

利用极化信息实现目标重构的算法研究

本文研究了一个光滑的、理想导电的、凸散射体的轮廓重构问题。主要从物理光学散射场的一阶修正项入手,分析了散射场的共极化和交叉极化信息与目标表面形状之间的关系,获得了散射场的极化特性与散射体表面上镜面点的主曲率密切相关的概念。借助于微分几何中曲面再现问题,重构出目标的外形图象。