The prediction formula and a risk-based sensor scheduling method in target detection with guiding information

Sensor scheduling is used to improve the sensing performance in the estimation of targets' states. However, few papers are on the sensor scheduling for target detection with guiding information. This letter can remedy this deficiency. A risk-based target detection method with guiding information is provided firstly, based on which, the sensor scheduling approach is aiming at reducing the risk and uncertainty in target detection, namely risk-based sensor scheduling method. What should be stressed is that the Prediction Formula in sensor scheduling is proposed. Lastly, some examples are conducted to stress the effectiveness of this proposed method.     

Direct ink writing of 3D-Honeycombed CL-20 structures with low critical size

3D-Honeycombed CL-20 structures with low critical size of detonation have been fabricated successfully for intelligent weapon systems using a micro-flow direct ink writing (DIW) technology. The CL-20-based explosive ink for DIW technology was prepared by a two-component adhesive system with waterborne polyurethane (WPU) and ethyl cellulose (EC). Not only the preparation of the explosive ink but also the principle of DIW process have been investigated systematically. The explosive ink displayed strong shear-thinning behavior that permitted layer-by-layer deposition from a fine nozzle onto a substrate to produce complex shapes. The EC content was varied to alter the pore structure distribution and rheological behavior of ink samples after curing. The deposited explosive composite materials are of a honeycombed structure with high porosity, and the pore size distribution increases with the increase of EC content. No phase change was observed during the preparation process. Both WPU and EC show good compatibility with CL-20 particles. Apparently high activation energy was realized in the CL-20-based composite ink compared with that of the refined CL-20 due to the presence of non-energetic but stable WPU. The detonation performance of the composite materials can be precisely controlled by an adjustment in the content of binders. The 3D honeycombed CL-20 structures, which are fabricated by DIW technology, have a very small critical detonation size of less than 69 μm, as demonstrated by wedge shaped charge test. The ink can be used to create 3D structures with complex geometries not possible with traditional manufacturing techniques, which presents a bright future for the development of intelligent weapon systems.     

面向目标对峙跟踪的四旋翼协同编队控制方法

针对多四旋翼编队飞行过程中对地面目标对峙跟踪、几何队形生成、稳固保持和协同抗干扰问题,设计了一种可应对外部环境干扰和气动参数不确定性的多四旋翼主从式协同目标跟踪方法。首先,建立存在外部干扰以及参数不确定性的四旋翼运动学/动力学模型;其次,基于Lyapunov导航向量场设计领航者的对峙跟踪航迹使得领航者以固定对峙半径实现对目标的盘旋跟踪;然后,构造多四旋翼分布式位置保持控制器,为后续姿态控制器构造提供必要的期望指令;最后,针对四旋翼外部环境干扰和气动参数不确定性设计基于自抗扰控制的多四旋翼姿态跟踪控制器。仿真结果表明所提方法可以在局部智能体通信的前提下实现对地面目标的对峙跟踪,显著改善四旋翼编队系统的抗干扰能力,提升干扰环境下多四旋翼编队几何构型的稳固性。     

Arbitrary-oriented target detection in large scene sar images

Target detection in the field of synthetic aperture radar (SAR) has attracted considerable attention of researchers in national defense technology worldwide, owing to its unique advantages like high resolution and large scene image acquisition capabilities of SAR. However, due to strong speckle noise and low signal-to-noise ratio, it is difficult to extract representative features of target from SAR images, which greatly inhibits the effectiveness of traditional methods. In order to address the above problems, a framework called contextual rotation region-based convolutional neural network (RCNN) with multilayer fusion is proposed in this paper. Specifically, aimed to enable RCNN to perform target detection in large scene SAR images efficiently, maximum sliding strategy is applied to crop the large scene image into a series of sub-images before RCNN. Instead of using the highest-layer output for proposal generation and target detection, fusion feature maps with high resolution and rich semantic information are constructed by multilayer fusion strategy. Then, we put forwards rotation anchors to predict the minimum circumscribed rectangle of targets to reduce redundant detection region. Furthermore, shadow areas serve as contextual features to provide extraneous information for the detector identify and locate targets accurately. Experimental results on the simulated large scene SAR image dataset show that the proposed method achieves a satisfactory performance in large scene SAR target detection.     

An approach for predicting digital material consumption in electronic warfare

Electronic warfare is a modern combat mode, in which predicting digital material consumption is a key for material requirements planning (MRP). In this paper, we introduce an insensitive loss function (ε) and propose a ε-SVR-based prediction approach. First, we quantify values of influencing factors of digital equipments in electronic warfare and a small-sample data on real consumption to form a real combat data set, and preprocess it to construct the sample space. Subsequently, we establish the ε-SVR-based prediction model based on “wartime influencing factors - material consumption” and perform model training. In case study, we give 8 historical battle events with battle damage data and predict 3 representative kinds of digital materials by using the proposed approach. The results illustrate its higher accuracy and more convenience compared with other current approaches. Taking data acquisition controller prediction as an example, our model has better prediction performance (RMSE = 0.575 7, MAPE (%) = 12.037 6 and R² = 0.996 0) compared with BP neural network model (RMSE = 1.272 9, MAPE (%) = 23.577 5 and R² = 0.980 3) and GM (1, 1) model (RMSE = 2.095 0, MAPE (%) = 24.188 0 and R² = 0.946 6). The fact shows that the approach can be used to support decision-making for MRP in electronic warfare.     

Optimal design of a novel cylindrical sandwich panel with double arrow auxetic core under air blast loading

The increasing threat of explosions on the battle field and the terrorist action requires the development of more effective blast resistance materials and structures. Curved structure can support the external loads effectively by virtue of their spatial curvature. In review of the excellent energy absorption property of auxetic structure, employing auxetic structure as core material in curved sandwich shows the potential to improve the protection performance. In this study, a novel cylindrical sandwich panel with double arrow auxetic (DAA) core was designed and the numerical model was built by ABAQUS. Due to the complexity of the structure, systematic parameter study and optimal design are conducted. Two cases of optimal design were considered, case1 focuses on reducing the deflection and mass of the structure, while case2 focuses on reducing the deflection and increasing the energy absorption per unit mass. Parameter study and optimal design were conducted based on Latin Hypercube Sampling (LHD) method, artificial neural networks (ANN) metamodel and the nondominated sorting genetic algorithm (NSGA-Ⅱ). The Pareto front was obtained and the cylindrical DAA structure performed much better than its equal solid panel in both blast resistance and energy absorption capacity. Optimization results can be used as a reference for different applications.     

From Westphalian Failure to Heterarchic Governance in MENA: The Case of Syria

Abstract

The problematic export of the Westphalian system to MENA is examined, taking Syria as exemplar. The export model is juxtaposed to actual non-lineal trajectories, semi-sovereignty and hybrid or failing states. This is manifested in post-uprising Syria in failing statehood, fragmented and overlapping governance, permeable and collapsing borders, the loss of sovereignty to trans-state movements, “competitive regime-building” between the Asad regime and jihadist warlords, and “competitive interventionism” by external powers filling the governance vacuum with their own proxies. The result is heterarchic zones of limited statehood in which state sovereignty is contested by both international (supra-state) penetration and sub-state fragmentation.     

一类二阶Hamilton系统周期解的存在性

Hamilton系统是非线性科学中的一个重要领域,很多人在超二次或次二次条件及其他一些条件下对Hamilton系统的周期解进行了研究。此文则研究了非自制二阶Hamilton系统在零点局部环绕及“非二次”条件下周期解的存在性,并利用局部紧性条件(C)条件以及极大极小方法证明了其周期解的存在性。     

铝合金板材相对均匀性的声-超声评价研究

基于Ritec-SNAP系统建立了声-超声技术实验系统,阐述了该实验系统的原理及应力波因子的定义,分析了在声-超声技术评价过程中用声信号的幅频特性及应力波因子表征材料相对均匀性的可行性。利用建立起来的实验系统,对铝板的相对均匀性进行了声-超声评价的实验研究。实验结果表明,用应力波因子评价铝合金板材的相对均匀性具有可行性。     

复杂作战任务弹药配备模型

多阶段任务系统(PMS)是一种典型的复杂系统,它包括多个在时间上连续且无相互重叠的基本任务,武器系统的作战过程多数属于这种复杂系统.以某作战单元的一次作战任务流程为例,详细地讨论了多阶段复杂任务系统的特点,并从基本任务阶段的系统可信性、可用度的角度出发,分析了在满足给定火力指标的前提下,建立整个复杂作战任务流程中弹药配备模型的方法.