Blank Panel Design of Integral Wing Skin Panels Based on Feature Mapping Methods

A blank panel design algorithm based on feature mapping methods for integral wing skin panels with supercritical airfoil surface is presented.The model of a wing panel is decomposed into features,and features of the panel are decomposed into information of location,direction,dimension and Boolean types.Features are mapped into the plane through optimal surface development algorithm.The plane panel is modeled by rebuilding the mapped features.Blanks of shot-peen forming panels are designed to identify the effectiveness of the methods.     

Even–odd cycle parity in complexity of hemispheric sunspot activity

We have used the Lempel–Ziv measure to describe the complexity in sunspot activity during the solar cycles 18–23. In particular, we examined the time series of daily sunspot numbers in the northern and southern hemispheres in each of the six cycles and calculated the Lempel–Ziv complexity (LZC) value for each time series. Our results indicate that in the even cycles, the LZC values of the sunspot numbers in the two hemispheres are very close to each other, whereas in the odd cycles they differ significantly between the two hemispheres. We also find that within each hemisphere the LZC varies from cycle to cycle. This even–odd cycle parity reflects the variations in inter-hemispheric strengths of the solar magnetic field leading to different temporal distributions of sunspots in the two hemispheres. The degree of complexity may influence the predictability of sunspot activity in the two hemispheres during the various cycles. Although the physical implication of the results is not clear, these results may stimulate new ideas into modeling the complex dynamics of the solar dynamo.     

Developing a dust storm detection method combining Support Vector Machine and satellite data in typical dust regions of Asia

Enhancing the dust storm detection is a key part for the environmental protection, human healthy and economic development. The goal of this paper is to propose a new Support Vector Machine (SVM)-based method to automatically detect dust storms using remote sensing data. Existing methods dealing with this problem are usually threshold-based that are of great complexity and uncertainty. In this paper we propose a simple and reliable method combining SVM with MODIS L1 data and explore the optimal band combinations used as the feature vectors of SVM. The developed method was evaluated by MODIS and OMI data qualitatively and quantitatively on three study sites located in the Arabian Desert, Gobi Desert and Taklimakan Desert, and it was also compared to three other traditional methods based on their accuracy, complexity, reliability and sensitivity to thresholds. The detection results demonstrated that the combination of (Band7 − Band3)/(Band7 + Band3) ((B7 − B3)/(B7 + B3)), Band20 − Band31 (B20 − B31), and Band31/Band32 (B31/B32) can detect the dust storms more precisely than other individual bands or their combination. The comparison among those cases indicated that the proposed automatic method exhibited an advantage of minimizing the uncertainty and complexity, which were the limits of defining thresholds based on the threshold-based methods. The conclusions can provide references for studies that focus on statistical-based dust storm detection.     

Improving orbit prediction accuracy through supervised machine learning

Due to the lack of information such as the space environment condition and resident space objects’ (RSOs’) body characteristics, current orbit predictions that are solely grounded on physics-based models may fail to achieve required accuracy for collision avoidance and have led to satellite collisions already. This paper presents a methodology to predict RSOs’ trajectories with higher accuracy than that of the current methods. Inspired by the machine learning (ML) theory through which the models are learned based on large amounts of observed data and the prediction is conducted without explicitly modeling space objects and space environment, the proposed ML approach integrates physics-based orbit prediction algorithms with a learning-based process that focuses on reducing the prediction errors. Using a simulation-based space catalog environment as the test bed, the paper demonstrates three types of generalization capability for the proposed ML approach: (1) the ML model can be used to improve the same RSO’s orbit information that is not available during the learning process but shares the same time interval as the training data; (2) the ML model can be used to improve predictions of the same RSO at future epochs; and (3) the ML model based on a RSO can be applied to other RSOs that share some common features.     

输油管布置优化模型

根据两车站是否在同一竖线上,分成两种情况,其中重点考虑了两车站不在同一竖线上的情况。根据三角形的相关知识,给出了管线建设费用的目标函数,然后利用微分法,得出最省的管线费用,最终解决了输油管布置的问题。     

交会对接远距离接近段制导研究

基于飞行器相对目标空间站的线性化运动方程，研究了交会对接中远距离接近段最优冲量解的必要条件，推导了确定最优解特征矢量曲线方程中待定参数的计算公式，给出了在特定初始状态和末状态下实现远距离接近的四次、三次、二次最优冲量解的作用时刻和大小的算法。通过一个交会实例的数字仿真分析，得到了有关远距离接近段制导方法的有指导价值的结果，验证了该方法是正确的、合理的。     

以作战结果向量分析飞机1对1空战效能

给出了作战歼击机作战结果向量模型，并以此作为衡量歼击机作虎效能的指标。通过战例分析，指出了抢先发射对提高飞机的作战效能起着重要的作用。并根据现代歼击机及其装备的飞行战术，技术特性，分析讨论了影响抢先发射以及作战结果向量的可能因素。给了的模型，可为新一代战斗机设计提供理论依据。     

REMOTE SENSING IMAGE CODING METHOD COMBINING WAVELET TRANSFORM WITH CLASSIFIED VECTOR QUANTIZATION

A new remote sensing image coding scheme based on the wavelet transform and classified vector quantization (CVQ) is proposed. The original image is first decomposed into a hierarchy of 3 layers including 10 subimages by DWT. The lowest frequency subimage is compressed by scalar quantization and ADPCM. The high frequency subimages are compressed by CVQ to utilize the similarity among different resolutions while improving the edge quality and reducing computational complexity. The experimental results show that the proposed scheme has a better performance than JPEG, and a PSNR of reconstructed image is 31～33 dB with a rate of 0.2 bpp.     

具有星间链路的导航星座重构研究

针对具有星间链路的导航星座在卫星节点或链路失效情况下的重构优化设计问题,提出了一种基于遗传算法的设计方法。首先,根据导航星座的功能需求与设计约束,建立了星座综合重构优化设计模型。其次,提出了基于遗传算法的综合优化设计方法,并根据问题特性对遗传算法的具体操作进行了修改。最后,应用该方法对Walker 24/3/2构型星座及网状星间网络在节点和链路混合故障模式下的重构进行了优化设计。结果表明,基于该方法重构后的星座与网络拓扑性能能够得到一定程度的改善,证明了方法的可行性。     

基于视线角速率的最优增量制导技术研究

提出一种基于视线角速率最优的制导方案。方案从最优控制的性能指标函数出发,通过求解一个Riccati方程和相关约束条件,并对系统进行一系列的相关的理想化的假设,得到系统的一般形式的制导指令。同时,为了避免制导指令在正负之间的频繁切换,根据偏置比例制导的原理,在制导指令中引入一个制导指令的增量,来减轻这一问题,并与传统的比例制导进行比较。仿真结果表明,这种制导方法相对于比例制导律而言,精度较高,性能优良,具有一定工程参考意义。