MONITORING OF ENERGETIC PARTICLE ENVIRONMENT INSIDE THE CHINA-BRAZIL EARTH RESOURCE SATELLITE

On 14 October 1999, the Chinese-Brazil earth resource satellite (CBERS-1) was launched in China. On board of the satellite there was an instrument designed at Peking University to detect the energetic particle radiation inside the satellite so the radiation fluxes of energetic particles in the cabin can be monitored continuously. Inside a satellite cabin, radiation environment consists of ether penetrated energetic particles or secondary radiation from satellite materials due to the interactions with primary cosmic rays.Purpose of the detectors are twofold, to monitor the particle radiation in the cabin and also to study the space radiation environment The data can be used to study the radiation environment and their effects on the electronics inside the satelhte cabin. On the other hand, the data are useful in study of geo-space energetic particle events such as solar proton events, particle precipitation and variations of the radiation belt since there should be some correlation between the radiation situation inside and outside the satellite.The instrument consists of two semi-conductor detectors for protons and electrons respectively. Each detector has two channels of energy ranges. They are 0.5-2MeV and ≥2MeV for electrons and 5-30MeV and 30-60MeV for protons. Counting rate for all channels are up to 104/(cm2@s)and power consumption is about 2.5 W. There are also the additional functions of CMOS TID (total integrated dose) effect and direct SEU monitoring. The data of CBMC was first sent back on Oct. 17 1999 and it's almost three years from then on. The detector has been working normally and the quality of data is good.The preliminary results of data analysis of CBMC not only reveal the effects of polar particle precipitation and radiation belt on radiation environment inside a satellite, but also show some important features of the geo-space energetic particle radiation.As one of the most important parameters of space weather, the energetic charged particles have great influences on space activities and ground tech nology. CBMC is perhaps the first long-term on-board special equipment to monitor the energetic particle radiation environment inside the satellite and the data it accnmulated are very useful in both satellite designing and space research.     

柱面菲涅耳太阳聚光透镜的光学设计和光学效率

研究了柱面线聚焦菲涅耳太阳聚光透镜的光学设计和光学效率。依据理论分析，对透镜参数进行了优化设计，成功地研制出了柱面线聚焦菲涅耳聚光透镜。还分析了透镜相对孔径（F数）和成型模具等因素对透镜光学效率的影响。     

Noise in wireless systems from solar radio bursts

Solar radio bursts were first discovered as result of their interference in early defensive radar systems during the Second World War (1942). Such bursts can still affect radar systems, as well as new wireless technologies. We have investigated a forty-year record of solar radio burst data (1960–1999) as well as several individual radio events in the 23rd solar cycle. This paper reviews the results of a portion of this research. Statistically, for frequencies f  1 GHz (near current wireless bands), there can be a burst with amplitudes >10³ solar flux units (SFU; 1 SFU = 10⁻²² W/m²) every few days during solar maximum conditions, and such burst levels can produce problems in contemporary wireless systems.     

应用加权中值滤波法检测薄壁梁式挠性器件下摆量

应用加权中值滤波法对薄壁梁式挠性器件下摆量进行高准确度CCD检测。薄壁梁式挠性器件在测量过程中测量图像存在高频抖动现象,因此测量准确度不高,运用加权中值滤波后使用最小二乘法细分技术,可以在实现提高测量准确度的同时,消除高频抖动带来的误差,从而可以有效提高CCD测量薄壁梁式挠性器件下摆量的准确度。实验表明,该方法比传统测量方法准确度提高20倍以上。     

Space telescope and cosmology

The status of institutional arrangements and of the hardware development for Space Telescope are highlighted. After a brief summary of instrument characteristics, some examples are given on the possible use of the ST to study objects of interest to cosmology.     

Coronal mass ejection detection using wavelets,curvelets and ridgelets: Applications for space weather monitoring

Coronal mass ejections (CMEs) are large-scale eruptions of plasma and magnetic field that can produce adverse space weather at Earth and other locations in the Heliosphere. Due to the intrinsic multiscale nature of features in coronagraph images, wavelet and multiscale image processing techniques are well suited to enhancing the visibility of CMEs and suppressing noise. However, wavelets are better suited to identifying point-like features, such as noise or background stars, than to enhancing the visibility of the curved form of a typical CME front. Higher order multiscale techniques, such as ridgelets and curvelets, were therefore explored to characterise the morphology (width, curvature) and kinematics (position, velocity, acceleration) of CMEs. Curvelets in particular were found to be well suited to characterising CME properties in a self-consistent manner. Curvelets are thus likely to be of benefit to autonomous monitoring of CME properties for space weather applications.     

Hybrid integration method for highly maneuvering radar target detection based on a Markov motion model

To detect highly maneuvering radar targets in low signal-to-noise ratio conditions, a hybrid long-time integration method is proposed, which combines Radon-Fourier Transform (RFT), Dynamic Programming (DP), and Binary Integration (BI), named RFT-DP-BI. A Markov model with unified range-velocity quantification is formulated to describe the maneuvering target’s motion. Based on this model, long-time hybrid integration is performed. Firstly, the whole integration time is divided into multiple time segments and coherent integration is performed in each segment via RFT. Secondly, non-coherent integration is performed in all segments via DP. Thirdly, 2/4 binary integration is performed to further improve the detection performance. Finally, the detection results are exported together with target range and velocity trajectories. The proposed method can perform the long-time integration of highly maneuvering targets with arbitrary forms of motion. Additionally, it has a low computational cost that is linear to the integration time. Both simulated and real radar data demonstrate that it offers good detection and estimation performances.     

空间激光通信系统中的信道纠错编码技术

由于空间激光通信系统的信道状态和链路捕获跟踪的不确定性,多种形式的信道纠错编码技术正被广泛发展研究。结合空间激光通信链路中误码性能的主要影响因素,分别选择合适的编码方案进行分析。通过仿真实验可知,对于在大气结构参数为1.5×10~(-14) m~(-2/3)、风速为20 m/s的空地激光链路的环境下,在系统数据速率为2 Gbit/s、要求误码率为10~(-6)时,LDPC码结合交织码相对未编码系统有3 dB的等效编码增益,LT码相对未编码系统有3.8 dB的等效编码增益。提供了一种能快速生成、扩展和校验的编码和交织实现方法,以抵抗大气湍流的快速变化对系统性能产生的影响。     

双框架飞机蒙皮检测机器人切换运动控制方法

针对一种双框架飞机蒙皮检测机器人,通过分析该机器人在飞机表面上的受力情况,在飞机表面该机器人受到了非完整约束,基于牛顿-欧拉法建立了机器人非完整约束动力学模型。根据机器人机械结构和运动步态分析,将该非完整机器人系统分为子系统A和子系统B。为了实现机器人在飞机表面运动,采用反演技术和快速Terminal滑模控制相结合的思想对系统设计了控制器,提出了一种反演-滑模控制方法;对于非完整机器人子系统A和子系统B,设计了一种基于事件驱动的切换策略,实现了机器人对期望轨迹的全局渐近跟踪,并利用Lyapunov稳定性证明系统的跟踪误差收敛。仿真和试验表明,采用该切换策略和反演-滑模控制方法,双框架飞机蒙皮检测机器人可以在飞机表面自由运动并进行损伤检测,具有良好的可靠性和稳定性。     

Multi-mode diagnosis of a gas turbine engine using an adaptive neuro-fuzzy system

Gas Turbine Engines (GTEs) are vastly used for generation of mechanical power in a wide range of applications from airplane propulsion systems to stationary power plants. The gas-path components of a GTE are exposed to harsh operating and ambient conditions, leading to several degradation mechanisms. Because GTE components are mostly inaccessible for direct measurements and their degradation levels must be inferred from the measurements of accessible parameters, it is a challenge to acquire reliable information on the degradation conditions of the parts in different fault modes. In this work, a data-driven fault detection and degradation estimation scheme is developed for GTE diagnostics based on an Adaptive Neuro-Fuzzy Inference System (ANFIS). To verify the performance and accuracy of the developed diagnostic framework on GTE data, an ensemble of measurable gas path parameters has been generated by a high-fidelity GTE model under (a) diverse ambient conditions and control settings, (b) every possible combination of degradation symptoms, and (c) a broad range of signal to noise ratios. The results prove the competency of the developed framework in fault diagnostics and reveal the sensitivity of diagnostic results to measurement noise for different degradation symptoms.