平台惯导系统初始对准的解耦设计

提出并设计了把状态空间解耦原理应用于平台惯导系统的一种快速初始对准方法。通过配置控制器将三个平台失调角进行解耦使其跟踪三个方向上的陀螺漂移 ,采用内外两层卡尔曼滤波器进行状态估计。仿真结果表明 ,该方法收敛较快、对漂移的抑制效果较好、对准精度高、简单易行。     

多孔超高燃速推进剂的燃烧理论

概述了有关多孔透气性超高燃速推进剂的代表性燃烧理论,其包括对流燃烧理论、两相流燃烧理论和非均一燃烧理论,介绍了它们的基本观点和主要结果,指出了彼此间的差异。     

功率型NiMH动力电池组建模研究

选取合适的动力电池模型用于混合动力汽车控制策略设计和性能仿真.比较分析了基于等效电路的电压-内阻模型和PNGV动态模型,提出了基于测试数据的特性场模型.以功率型NiMH动力电池组为例,进行了模型参数的辨识.仿真结果与实验结果对比表明:特性场模型和PNGV动态模型具有相近的精度,但PNGV动态模型的精度与模型参数的辨识结果密切相关,电压-内阻模型简单适用于稳态仿真.     

国防军工建设贯彻科学发展观思路研究

介绍了科学发展观对国防军工建设提出的全面、协调、可持续性和以人为本等发展要求。在分析当前国防军工建设存在的困难和问题的基础上,提出了将军工建设与经济建设放在一个大系统中统筹协调发展,实现国防军工领域中民用经济效应的最大化和经济领域中国防军工经济效应的最大化,鼓励国防军工人才和民用科技、工业人才参与民用领域建设和国防军工建设,以及推动建立以产业链、效益链和能力链为核心的“小核心、大协作、寓军于民”的国防科研生产机制等措施,并就国防军工建设的观念、管理机构设置、人才培养、体制改革、规划与产业政策、后勤保障等改革提出了相应的建议。     

Evaluation of craters formation in hypervelocity impact of debris particles on solid structures

The aim of this work is to develop simplified model of space debris particle collision on solid structures, which would provide closed form solution formulas for determining crater depth, radius and ejected mass being functions of impactor mass, speed and material of both impactor and target. The model will be verified with results of experiments.     

双四唑盐的合成及表征

介绍了双四唑钾盐(K2BHT)、双四唑(BHT)、双四唑胍和双四唑氨基胍的合成。采用滴加醋酸和加入硫酸铜改善中间产物双四唑锰盐过滤性,提高了产率。采用双四唑锰盐和碳酸钾高温置换反应生产双四唑钾盐。双四唑和碳酸胍、碳酸氨基直接反应生成双四唑胍和双四唑氨基胍。通过DSC-TGA、元素分析、IR、1H NMR1、3C NMR和MS等方法,对其结构进行了鉴定,并进行了常规感度测试。结果表明,双四唑感度较高,而其它双四唑盐感度较低。     

多孔材料在整流罩内中高频降噪的应用与优化研究

基于JCA模型，采用有限元仿真和声学试验获取了三聚氰胺泡沫和吸音棉的声学参数，采用统计能量分析（SEA）方法建立了某卫星-整流罩的系统级模型。通过与混响室试验结果进行对比，验证了模型的正确性；并通过仿真和试验获取了两种材料对整流罩内噪声环境的降噪效果，分析了厚度、敷设率和敷设位置对降噪效果的影响。结果表明，采用结合Biot理论的SEA方法能有效预测整流罩内中高频噪声环境及多孔材料降噪效果；总降噪量与厚度、敷设率和敷设位置关系紧密，采用多孔材料降噪时应综合考虑以上因素。     

联合符号同步的低复杂度频域并行解调结构

针对高速卫星通信系统调制信号的符号速率非常高、而处理器的工作时钟频率相对较低的问题,文章提出了一种联合符号同步的频域并行解调结构。在分析传统基于FFT的频域并行解调结构的基础上,将符号同步与匹配滤波结合起来,可以使滤波器的输出数据速率低至符号速率,同时能够缩短FFT的长度,从而大大减少了实现时的复杂度。     

Optimal reconfiguration maneuvers for spacecraft imaging arrays in multi-body regimes

Upcoming National Aeronautics and Space Administration (NASA) mission concepts include satellite arrays to facilitate imaging and identification of distant planets. These mission scenarios are diverse, including designs such as the terrestrial planet finder-occulter (TPF-O), where a monolithic telescope is aided by a single occulter spacecraft, and the micro-arcsecond X-ray imaging mission (MAXIM), where as many as 16 spacecraft move together to form a space interferometer. Each design, however, requires precise reconfiguration and star tracking in potentially complex dynamic regimes. This paper explores control methods for satellite imaging array reconfiguration in multi-body systems. Specifically, optimal nonlinear control and geometric control methods are derived and compared to the more traditional linear quadratic regulators, as well as input state feedback linearization. These control strategies are implemented and evaluated for the TPF-O mission concept.     

Multi-UAV reconnaissance task allocation for heterogeneous targets using an opposition-based genetic algorithm with double-chromosome encoding

This paper presents a novel multiple Unmanned Aerial Vehicles (UAVs) reconnaissance task allocation model for heterogeneous targets and an effective genetic algorithm to optimize UAVs’ task sequence. Heterogeneous targets are classified into point targets, line targets and area targets according to features of target geometry and sensor’s field of view. Each UAV is regarded as a Dubins vehicle to consider the kinematic constraints. And the objective of task allocation is to minimize the task execution time and UAVs’ total consumptions. Then, multi-UAV reconnaissance task allocation is formulated as an extended Multiple Dubins Travelling Salesmen Problem (MDTSP), where visit paths to the heterogeneous targets must meet specific constraints due to the targets’ feature. As a complex combinatorial optimization problem, the dimensions of MDTSP are further increased due to the heterogeneity of targets. To efficiently solve this computationally expensive problem, the Opposition-based Genetic Algorithm using Double-chromosomes Encoding and Multiple Mutation Operators (OGA-DEMMO) is developed to improve the population variety for enhancing the global exploration capability. The simulation results demonstrate that OGA-DEMMO outperforms the ordinary genetic algorithm, ant colony optimization and random search in terms of optimality of the allocation results, especially for large scale reconnaissance task allocation problems.