Probing solar and stellar interior dynamics and dynamo

Solar and stellar activity is a result of complex interaction between magnetic field, turbulent convection and differential rotation in a star’s interior. Magnetic field is believed to be generated by a dynamo process in the convection zone. It emerges on the surface forming sunspots and starspots. Localization of the magnetic spots and their evolution with the activity cycle is determined by large-scale interior flows. Thus, the internal dynamics of the Sun and other stars hold the key to understanding the dynamo mechanism and activity cycles. Recently, significant progress has been made for modeling magnetohydrodynamics of the stellar interiors and probing the internal rotation and large-scale dynamics of the Sun by helioseismology. Also, asteroseismology is beginning to probe interiors of distant stars. I review key achievements and challenges in our quest to understand the basic mechanisms of solar and stellar activity.     

Results from the ESA SREM monitors and comparison with existing radiation belt models

The Standard Radiation Environment Monitor (SREM) is a simple particle detector developed for wide application on ESA satellites. It measures high-energy protons and electrons of the space environment with a 20° angular resolution and limited spectral information. Of the ten SREMs that have been manufactured, four have so far flown. The first model on STRV-1c functioned well until an early spacecraft failure. The other three are on-board, the ESA spacecraft INTEGRAL, ROSETTA and PROBA-1. Another model is flying on GIOVE-B, launched in April 2008 with three L-2 science missions to follow: both Herschel and Planck in 2008, and GAIA in 2011). The diverse orbits of these spacecraft and the common calibration of the monitors provides a unique dataset covering a wide range of B-L* space, providing a direct comparison of the radiation levels in the belts at different locations, and the effects of geomagnetic shielding. Data from the PROBA/SREM and INTEGRAL/IREM are compared with existing radiation belt models.     

Solar activity prediction studies and services in NAOC

Solar activity prediction services started in 1960’s in National Astronomical Observatories, Chinese Academy of Sciences (NAOC). As one of the members of the International Space Environment Service (ISES), Regional Warning Center of China (RWC-China) was set up in 1990’s. Solar Activity Prediction Center (SAPC), as one of the four sub-centers of RWC-China, is located in NAOC. Solar activity prediction studies and services in NAOC cover short-term, medium-term, and long-term forecast of solar activities. Nowadays, certain prediction models, such as solar X-ray flare model, solar proton event model, solar 10 cm radio flux model, have been established for the practical prediction services. Recently, more and more physical analyses are introduced in the studies of solar activity prediction, such as the magnetic properties of solar active regions and magnetic structure of solar atmosphere. Besides traditional statistics algorithms, Machine Learning and Artificial Intelligence techniques, such as Support Vector Machine (SVM) method, are employed in the establishment of forecast models. A Web-based integrated platform for solar activity data sharing and forecast distribution is under construction.     

Energy conversion of the flare due to direct electric fields from the sheared reconnection

In this paper we present a new mechanism of the main energy conversion of the solar flare. Since a flare inducing prominence (flux tube) rises V_z ? 300 km s⁻¹, the plasmas below it cannot continuously eject with Alfvén speeds of V_A = 3000 km s⁻¹ but probably with V_z ≈ ±100 km s⁻¹. Plasma up and downflows with V_A will within a short duration be blocked between the chromosphere where reconnected flux tubes are piling up, and the slowly rising flux rope. Hence the Petschek slow shock mechanism is difficult to be realized as a major energy converting mechanism.     

基于CompactPCI总线的红外目标跟踪系统

红外目标跟踪方法的理论研究较多,而通用的实时跟踪系统较少。给出了具有CompactPCI总线、并行分布式结构的系统方案,核心是基于标准总线的实时系统,上位机实现卡尔曼预测,DSP并行完成频域转换与相关,CPLD实现总线接口控制。所实现的系统具有运算能力强、通信带宽大、可扩展性和通用性强的特点,实用表明了它的可行性。     

基于自适应Kalman滤波的改进PSO算法

针对基于Kalman滤波的PSO算法在设计与应用过程中存在的不足,提出了基于自适应Kalman滤波的改进PSO算法。利用粒子群状态空间Markov链模型,建立粒子群系统状态方程;采用粒子的速度和位置作为观测量,构建观测方程;引入记忆衰减因子动态调整Kalman滤波模型参数及噪声方差阵,降低模型误差,提高粒子的位置估计精度。仿真实验表明:改进的PSO算法无论在优化精度、收敛速度,还是在稳定性方面都有很大的改进和提高,这就有效避免了粒子的"早熟"收敛问题;尤其在处理复杂多峰问题上,改进算法表现出很明显的优越性。     

未知互耦条件下混合信号波达方向估计

阵列天线互耦对导向矢量的扰动以及信号相干性对数据协方差矩阵造成的秩损,使得基于子空间正交性原理的超分辨波达方向估计(Direction-of-Arrival,DOA)算法性能恶化,甚至失效。针对这一问题,提出一种在相干与非相干信号混合状态下无需阵列互耦补偿的特征矢量平滑DOA估计算法。该算法对部分阵元接收数据的协方差矩阵特征分解,将得到的特征矢量平滑处理后构造等效协方差矩阵,抑制阵列互耦影响的同时完成混合信号DOA估计。在阵列互耦和信号相干性均未知的条件下,正确估计了信号DOA,无需互耦参数估计或补偿。计算机仿真结果验证了算法的有效性。     

基于偏最小二乘回归分析的装备研制费用估算方法及应用

介绍了寿命周期费用的概念以及各阶段分布情况;针对经典回归分析的不足,采用偏最小二乘回归分析对某装备样本数据进行分析建模;建立了研制费用与几个相关指标的回归方程,并将估算结果与经典的回归分析进行对比,验证模型的合理性。该模型能较好地反映了费用与各指标之间的关系,对后续寿命周期费用的分析与控制有一定的意义。     

全球卫星导航星座网络协议体系与运行模式

针对全球卫星导航星座网络建设初期或论证阶段所涉及的网络体系结构、协议体系及相关组网等技术问题,开展了基于导航星座星间链路构建空间信息网络的技术研究,分别提出了由子网、接入网、骨干网等节点及其相互之间星间、星地无线链路构成的分层网络系统结构,设计了兼容遥控、遥测、测量与网络交互支持等业务的基于IP over CCSDS(基于空间数据系统咨询委员会标准的空间链路承载互联网协议业务)的协议体系,给出了全系统基本通信业务运行模式等。与传统高轨卫星通信系统相比,该星座网络具有高覆盖、低时延、随遇接入等优点,可实现星座导航性能与中低轨及地面用户通信性能的全方位提升,相关结果对我国全球卫星导航星座网络技术研究具有一定的参考意义。     

相控斜侧面阵AEW雷达时空二维自适应杂波抑制

在分析了斜侧面阵与地面反射点几何关系的基础上建立了地面杂波回波的信号模型，利用这一杂波模型采用构造矩阵的方法对杂波子空间进行了分析，得到了杂波子空间的主要特征，给出了二维杂波谱和最优处理器性能的仿真结果。