提高DCPR接收系统信噪比和抗干扰能力的方案

文章介绍了风云二号卫星地面应用系统工程高速数据收集平台报告信号（ DCPR）接收系统在北京气象站系统预交付联试中表现的天线频繁跟踪以及经过接收变频后的90.9MHz中频信号信噪比测试结果较差问题排查过程和有效的解决方案。问题排查过程主要针对DCPR接收系统射频接收机多个关键检测点进行测试,从测试结果和系统链路组成分析问题原因,并制定了四个具有针对性解决方案,主要是：DCPR接收系统射频接收机自带5MHz锁相晶体振荡器、加强手机信号干扰抑制、降低变频前链路增益、增加变频后链路增益以满足系统使用要求。最终将以上解决方案应用到风云二号卫星地面应用系统工程高速数据收集平台报告信号（ DCPR）接收系统中,问题得到了很好解决。     

减小导弹超声速大攻角斜吹力矩的边条布局及其原理分析

针对正常式布局导弹外形,在保证其它气动性能不变的情况下,提出了一种减小超声速大攻角情况下斜吹力矩的边条布局,使该类导弹在大攻角下实现极高机动能力成为可能。以计算流体力学为主要手段,分析了此种边条布局减小斜吹力矩的作用原理,即边条对翼面局部流场的干扰影响了翼面压力的分布与大小,从而使得翼面的滚动力矩降低。
     

基于伴飞模式的补给星轨道设计与优化

针对采用伴飞模式的星座燃料补给问题,本文对其补给星的轨道进行了设计与优化。在给出补给星的轨道设计之后,利用遗传算法对补给星轨道机动所消耗的燃料质量以及每次转移给工作星的燃料质量进行了优化求解,使得补给星燃料利用率达到最高。仿真结果同时给出了燃料利用率与工作星轨道高度以及星座中卫星数目之间的关系,该结论对采用伴飞模式的星座燃料补给研究提供了较好的理论参考。     

GNSS服务空域空间信号可用性比较与分析

通过基本参数对全球卫星导航系统（GPS、GLONASS、Galileo和北斗）空间信号可用性影响实验,得出四系统的A knee 值分别为3800km、1100km、3800km和1000km,对应的平均可见卫星数为25、16、22和14/22（亚太地区、MEO星座/混合星座）。分析了三种典型轨道用户的卫星可见性,北斗和GLONASS对MEO和HEO用户的空间信号可用性能较GPS和Galileo稍差,而在LEO用户的应用中,北斗空间信号可用性能却表现最优,平均可见卫星数约为20颗,可用性时间分布比较均匀。最后对GNSS空间有效持续时间段进行统计,随着用户高度的增加,有效持续时间段数增多、总有效持续时间减少;四系统提供全弧段有效服务空间分别为地面至6100km、1600km、6100km和1700km。     

民用客机增升装置气动噪声研究进展

随着民用飞机数量的快速增加,航空噪声问题日益引起世界范围的关注。增升装置作为重要的机体噪声源之一以其流动复杂性和声源多样性成为民用航空气动声学的难点之一,欧美各国为此开展了大量的研究。总结了增升装置气动噪声的产生机理以及控制措施的研究现状,在此基础上还特别关注了目前工业部门气动与声学的设计思想及需求。     

Identifying areas of high economic-potential copper mineralization using ASTER data in the Urumieh–Dokhtar Volcanic Belt,Iran

This study investigates the application of spectral image processing methods to ASTER data for mapping hydrothermal alteration zones associated with porphyry copper mineralization and related host rock. The study area is located in the southeastern segment of the Urumieh–Dokhtar Volcanic Belt of Iran. This area has been selected because it is a potential zone for exploration of new porphyry copper deposits. Spectral transform approaches, namely principal component analysis, band ratio and minimum noise fraction were used for mapping hydrothermally altered rocks and lithological units at regional scale. Spectral mapping methods, including spectral angle mapper, linear spectral unmixing, matched filtering and mixture tuned matched filtering were applied to differentiate hydrothermal alteration zones associated with porphyry copper mineralization such as phyllic, argillic and propylitic mineral assemblages.     

高温吸波材料研究新进展与趋势

对最近报道的耐温>1 000℃的高温吸波材料进行了回顾,主要介绍了碳和陶瓷类无机耐高温吸波材料;同时对在纳米技术、静电纺丝技术等研究中报道的新型耐高温材料应用为电磁吸收材料进行了展望。     

非接触高温测量技术发展与现状

非接触高温测量技术已经成为2 000℃以上高温目标温度测量的主要手段,其发展水平直接制约着国防科技工业尤其是高速飞行器热防护及隐身性能等关键技术领域的发展。本文综述了当前各类非接触高温测量技术的研究现状、技术优缺点及应用前景,并对未来非接触高温测量技术的发展进行了展望。     

基于数值微分方法的卫星陀螺故障诊断(英文)

提出一种基于数值微分的卫星陀螺故障诊断方法。通过引入代数可观测的概念,将故障诊断问题转化为求解数值微分问题。并根据卫星姿态运动学方程证明了陀螺故障的代数可观性。然后通过高增益观测器的方法来近似姿态敏感器测量输出的数值导数,并利用李雅普诺夫理论分析和设计高增益观测器。基于陀螺故障的代数可观性和星敏感器测量输出的数值微分,可以直接得到陀螺组件的故障估计值。最后,通过突变、缓变和并发故障等仿真算例验证了算法的有效性,仿真结果表明所提出的方法不仅可以检测故障的发生,而且能够估计故障幅值。     

Aerial-BiSeNet: A real-time semantic segmentation network for high resolution aerial imagery

The aircraft system has recently gained its reputation as a reliable and efficient tool for sensing and parsing aerial scenes. However, accurate and fast semantic segmentation of high-resolution aerial images for remote sensing applications is still facing three challenges: the requirements for limited processing resources and low-latency operations based on aerial platforms, the balance between high accuracy and real-time efficiency for model performance, and the confusing objects with large intra-class variations and small inter-class differences in high-resolution aerial images. To address these issues, a lightweight and dual-path deep convolutional architecture, namely Aerial Bilateral Segmentation Network (Aerial-BiSeNet), is proposed to perform real-time segmentation on high-resolution aerial images with favorable accuracy. Specifically, inspired by the receptive field concept in human visual systems, Receptive Field Module (RFM) is proposed to encode rich multi-scale contextual information. Based on channel attention mechanism, two novel modules, called Feature Attention Module (FAM) and Channel Attention based Feature Fusion Module (CAFFM) respectively, are proposed to refine and combine features effectively to boost the model performance. Aerial-BiSeNet is evaluated on the Potsdam and Vaihingen datasets, where leading performance is reported compared with other state-of-the-art models, in terms of both accuracy and efficiency.