Satellite range scheduling with the priority constraint: An improved genetic algorithm using a station ID encoding method

Satellite range scheduling with the priority constraint is one of the most important problems in the field of satellite operation.This paper proposes a station coding based genetic algorithm to solve this problem,which adopts a new chromosome encoding method that arranges tasks according to the ground station ID.The new encoding method contributes to reducing the complexity in conflict checking and resolving,and helps to improve the ability to find optimal resolutions.Three different selection operators are designed to match the new encoding strategy,namely random selection,greedy selection,and roulette selection.To demonstrate the benefits of the improved genetic algorithm,a basic genetic algorithm is designed in which two cross operators are presented,a single-point crossover and a multi-point crossover.For the purpose of algorithm test and analysis,a problem-generating program is designed,which can simulate problems by modeling features encountered in real-world problems.Based on the problem generator,computational results and analysis are made and illustrated for the scheduling of multiple ground stations.     

扩频信号声光相关解调技术

声光相关技术在检测宽带微弱信号中有很大的潜力，提出在射频上用声光相关器对扩频信号做相关运算的方案，给出扩频信号的快速捕获、精密跟踪和信息解调的方法，并设计了实验系统，结果得到了验证。     

基于DSP的导引控制器硬件设计与实现

按照小型化、高实时性的要求,采用TI公司面向控制的DSP芯片TMS320LF2407A,设计并实现了以DSP为处理核心的导引控制器,详细介绍了系统的整体方案设计和具体的硬件选型及接口设计。重点论述了飞控计算机与导引控制器之间的串行通信设计,并给出了硬件接口电路。     

TH-DNCⅢ数控机床通讯软件研究

本文对PC机与TH-DNCⅢ型数控机床配备的通讯软件DNC．EXE进行了反汇编及分析研究，总结了该通讯软件的基本功能及关键技术。     

CCSDS-RS(255,223)码高速译码器的硬件实现研究

研究了空间通信用高速Reed-Solomon(255,223)码硬判决译码器的FPGA实现方法,提出一种新的纠错算法实现结构以最大程度提高译码器性能。设计中采用RiBM算法求解关键方程,并通过应用高速比特并行乘法器以及流水线和并行处理方法提高译码通过率。综合和测试验证结果显示,该译码器译码通过速率为1.7Gbit/s,译码延迟为296个时钟周期,优于目前同类型的RS译码器性能指标。     

非线性时间序列在卫星通信网络数据预测中的研究

卫星通信网络数据预测在卫星通信系统中起着重要的作用,是系统建模的主要研究内容之一。由于卫星通信网络数据的非平稳性和不可预知因素的影响,决定了应采用非线性时间序列建模方法来分析、预测。在分析通信网络数据的基础上,建立卫星通信网络数据的ARIMA模型,在确定预测模型的阶和进行参数估计后,给出不同预测步数条件下的通信网络数据流量的预测,并进行了仿真对比实验。仿真结果表明,该模型在预测步数较小的情况下,预测误差在4％左右,具有良好的预测精度,为卫星通信网络数据流量的预测、异常检测和网络负载预测的应用奠定了坚实的基础。     

基于模型预测控制的非线性飞行控制系统研究

应用泰勒级数展开方法设计了飞行器六自由度非线性模型预测控制器.通过对控制向量和输出向量的有限泰勒级数展开,确定闭环形式的控制输入.仿真结果表明:该方法能够适应控制项不完全或缺少控制项的病态情况,适当选择控制器的泰勒展开阶数可得到最优的控制结果,所设计的模型预测控制器具有很好的跟踪效果.     

大容量高精度自动车辆定位系统数据链路设计

目前自动车辆定位系统存在容量少,报警碰撞和精度低等缺陷.因此,对自动车辆定位系统和时隙ALOHA(SALOHA)的特点进行了分析研究,提出了广播预约ALOHA(BRALOHA)这一新的数据链路设计方法,即基站广播差分信息,子站预约传输位置等信息和平滑接收机噪声等.其集中控制策略,吞吐量负载性能以及时延吞吐量性能表明,它适宜于设计大容量高精度自动车辆定位系统.     

Cellular communication and “non-targeted effects”: Modelling approaches

During the last decade, a large number of experimental studies on the so-called “non-targeted effects”, in particular bystander effects, outlined that cellular communication plays a significant role in the pathways leading to radiobiological damage. Although it is known that two main types of cellular communication (i.e. via gap junctions and/or molecular messengers diffusing in the extra-cellular environment, such as cytokines, NO etc.) play a major role, it is of utmost importance to better understand the underlying mechanisms, and how such mechanisms can be modulated by ionizing radiation. Though the “final” goal is of course to elucidate the in vivo scenario, in the meanwhile also in vitro studies can provide useful insights. In the present paper we will discuss key issues on the mechanisms underlying non-targeted effects and cell communication, for which theoretical models and simulation codes can be of great help. In this framework, we will present in detail three literature models, as well as an approach under development at the University of Pavia. More specifically, we will first focus on a version of the “State-Vector Model” including bystander-induced apoptosis of initiated cells, which was successfully fitted to in vitro data on neoplastic transformation supporting the hypothesis of a protective bystander effect mediated by apoptosis. The second analyzed model, focusing on the kinetics of bystander effects in 3D tissues, was successfully fitted to data on bystander damage in an artificial 3D skin system, indicating a signal range of the order of 0.7–1 mm. A third model for bystander effect, taking into account of spatial location, cell killing and repopulation, showed dose–response curves increasing approximately linearly at low dose rates but quickly flattening out for higher dose rates, also predicting an effect augmentation following dose fractionation. Concerning the Pavia approach, which can model the release, diffusion and depletion/degradation of candidate signals (e.g. cytokines) travelling in the extra-cellular environment, the good agreement with ad hoc experimental data obtained in our laboratory validated the adopted approach, which in the future can be applied also to other candidate signals.     

Combining frequency and time domain models to forecast space weather

Space weather series incorporate several distinct components, cycles at multiple frequencies, irregular trends, and nonlinear variability. The cycles are stochastic, i.e., the amplitude varies over time. Similarly, the trend is stochastic: the slope and direction of trending change repeatedly. This study sets out a combined model using both frequency and time domain methods, in two stages. In the first stage, a frequency domain algorithm is estimated and forecasted. In the second stage, the forecast is used as an input in a neural network. The combined model also includes a term enabling the model to react inversely to large deviations between the actual values and forecast. The models are evaluated using two data sets, the hemispheric power data obtained from the Polar Orbiting Environment satellites, and the Aa geomagnetic index. All the series are at a daily resolution. Forecasting experiments are run over horizons of 1–7 days. The models are estimated using a moving window or adaptive approach. The combined model consistently achieves the most accurate results. Among single equation methods, the frequency domain model is more accurate for the geomagnetic index because it is able to capture the underlying cycles more effectively. In the hemispheric power series, the cycles are less pronounced, so that time domain methods are more accurate, except at very short horizons. Nevertheless, in both data sets, the combined model works well because the frequency domain algorithm captures cyclical behavior, while the neural net is better able to capture short-term dependence and trending.