均匀离散线阵幅相误差快速校准方法研究

针对实践中声基阵校准问题,分别研究了远场和近场条件下均匀离散线阵幅相误差快速校准方法.远场时,采用单声源且不需要精确已知声源方位,只需精确水平旋转基阵1次,对接收数据的协方差矩阵进行特征子空间分解,再根据推导的公式可快速计算出幅相误差矩阵.近场时,波阵面为球面,不能采用现有的校准方法,因此提出了一种最多只需精确水平旋转基阵3次,通过转动前后的几何关系建立方程组求解各参量,通过公式可把球面波补偿为平面波,然后采用单辅助源法可快速计算出幅相误差矩阵.仿真实验验证了两种校准方法的有效性,并详细分析了各种因素对幅相误差矩阵估计及声源方位估计精度的影响.两种校准方法计算简单且精度较高,操作简单易于工程实用.     

Symmetry in world trade network

Symmetry of the world trade network provides a novel perspective to understand the world-wide trading system. However, symmetry in the world trade network (WTN) has been rarely studied so far. In this paper, the authors systematically explore the symmetry in WTN. The authors construct WTN in 2005 and explore the size and structure of its automorphism group, through which the authors find that WTN is symmetric, particularly, locally symmetric to a certain degree. Furthermore, the authors work out the symmetric motifs of WTN and investigate the structure and function of the symmetric motifs, coming to the conclusion that local symmetry will have great effect on the stability of the WTN and that continuous symmetry-breakings will generate complexity and diversity of the trade network. Finally, utilizing the local symmetry of the network, the authors work out the quotient of WTN, which is the structural skeleton dominating stability and evolution of WTN. This research was supported by the National Natural Science Foundation of China under Grant No. 70371070; Shanghai Leading Academic Discipline Project under Grant No. S30504; and Key Project for Fundamental Research of STCSM under Grant No. 06JC14057.     

Reduced K-best sphere decoding algorithm based on minimum route distance and noise variance

This paper focuses on reducing the complexity of K-best sphere decoding （SD） algorithm for the detection of uncoded multi-ple input multiple output （MIMO） systems. The proposed algorithm utilizes the threshold-pruning method to cut nodes with partial Euclidean distances （PEDs） larger than the threshold. Both the known noise value and the unknown noise value are considered to generate the threshold, which is the sum of the two values. The known noise value is the smal est PED of signals in the detected layers. The unknown noise value is generated by the noise power, the quality of service （QoS） and the signal-to-noise ratio （SNR） bound. Simulation results show that by considering both two noise values, the proposed algorithm makes an efficient reduction while the performance drops little.     

DOES INVESTOR SENTIMENT PREDICT STOCK RETURNS？ THE EVIDENCE FROM CHINESE STOCK MARKET

This paper examines the proxy variables of investor sentiment in Chinese stock market carefully, and tries to construct an investor sentiment index indirectly. We use cross correlation analysis to examine lead-lag relationship between the proxy variables and HS300 index. The results show that net added accounts （NAA）, SSE share turnover （TURN）, and closed-end fund discount （CEFD） are leading variables to stock market. The average first day return of IPOs （RIPO） and relative degree of active trading in equity market （RDAT） are contemporary variables, while number of IPOs （NIPO） is a lagging variable of stock market. Using the sentiment proxy variables with most possible leading order, and forward selection stepwise regression method, the empirical results on monthly stock returns reveal that three leading proxy variables can be used to form a sentiment index. And the out of sample tests prove that this sentiment index has good predictive power of Chinese stock market, and it is robust.     

A partial robust optimization approach to inventory management for the offline-to-online problem under different selling prices

This study examines an optimal inventory strategy when a retailer markets a product at different selling prices through a dual-channel supply chain, comprising an online channel and an offline channel. Using the operating pattern of the offline-to-online (O2O) business model, we develop a partial robust optimization (PRO) model. Then, we provide a closed-form solution when only the mean and standard deviation of the online channel demand distribution is known and the offline channel demand follows a uniform distribution (partial robust). Specifically, owing to the good structural properties of the solution, we obtain a heuristic ordering formula for the general distribution case (i.e., the offline channel demand follows a general distribution). In addition, a series of numerical experiments prove the rationality of our conjecture. Moreover, after comparing our solution with other possible policies, we conclude that the PRO approach improves the performance of incorporating the internet into an existing supply chain and, thus, is able to adjust the level of conservativeness of the solution. Finally, in a degenerated situation, we compare our PRO approach with a combination of information approach. The results show that the PRO approach has more “robust” performance. As a result, a reasonable trade-off between robustness and performance is achieved.     

作战单元战场空间感知建模研究

依托仿真进行军事作战过程研究所要解决的建模问题之一就是对作战单元战场空间感知过程进行合理建模,而其有效性需求决定了模型必须要能够正确地表达实际作战过程中作战单元战场空间感知所具有的、面向区域的特性。根据作战单元战场空间感知的区域特性,阐述了基于空间划分的作战单元空间感知建模实现思想,并就基于空间划分的战场空间感知模型实现进行了详细的形式化描述。就基于空间划分的作战单元空间感知模型的运行效率,进行了实例对比分析。     

基于仿真数据采集单的仿真评估需求研究

在装备系统仿真与评估领域中,出现了仿真建模与评估需求之间的工作难以协调,难以相互支持的现象。针对该问题,提出了仿真数据采集单的思想,即以评估需求为牵引,建立评估指标,针对底层末级评估指标,建立一个可供评估者与仿真建模者交互协商的平台以使仿真数据采集单能确保仿真可采集,需求可体现。以装甲坦克分队作战效能仿真评估为例,借助仿真数据采集单,仿真执行的结果表明,该方法获得的仿真数据满足了评估需求,也明确了建模仿真的目的。     

多UAV协同区域覆盖搜索研究

针对多无人机协同区域覆盖搜索问题,为降低问题求解的复杂度,将其分解为多UAV任务区域分配和完全覆盖路径规划两个子问题,对子问题分别优化求解。建立了无人机任务执行代价模型,采用分层模糊推理求解无人机的性能评估指数,根据性能评估指数采用基于面积的区域分割方法实现多无人机搜索任务区域的分配。分析了无人机实现区域内覆盖搜索的最优路径问题,给出了在特定多边形区域下最小代价的搜索模式和搜索路径。仿真实验结果验证了所给方法的有效性。     

基于BP神经网络模型的目标属性识别仿真

在地面防空作战中,对空中目标进行属性识别是防空导弹武器发射决策的关键环节之一,可靠及时的识别可有效地避免误伤我（友）机,准确消灭敌机。结合现代防空作战特点,对影响目标属性识别的各种因素进行定性和定量分析,建立了基于BP神经网络的目标属性识别模型,仿真分析表明了模型的有效性和实时性。     

执行器饱和时的SISO系统模型参考自适应控制

针对大多数执行器不可避免地会出现饱和现象,尤其是工作范围大、非线性特性严重的被控制对象,提出了一种模型参考自适应设计方法,把输入过饱和部分看作干扰信号,并用可调参数和跟踪误差函数对饱和干扰进行估计,通过参数调节消除饱和现象,针对不同相对阶的系统分别进行讨论,使本方法更具普遍性。仿真结果表明,本方法能够使系统有较好的跟踪能力和抗饱和能力。