基于改进TOPSIS法和蚁群算法的反TBM目标群目标分配研究

基于改进的TOPSIS法和蚁群算法,以弹道导弹目标群为研究对象,研究了反导指控系统对目标群的目标分配问题。首先通过改进的TOPSIS法确定TBM目标群威胁排序并基于拦截排序准则确定拦截排序;其次使作战效能最大化,基于蚁群算法确定目标的最优分配方案;最后通过仿真实例验证了在考虑目标威胁值排序前提下采用此算法,可使目标群分配方案更加科学有效和符合反导作战实际。     

陆军作战复杂系统ABMS机理研究

研究陆军作战复杂系统,需要解决两个不可回避的基本问题。一是怎样利用复杂性理论研究陆军作战系统的复杂性,即怎样借鉴复杂性理论构建复杂性思维模式。要解决这个问题,首先必须弄清复杂性理论概念的核心原理。二是在复杂性思维模式下,怎样进行陆军作战复杂系统的ABMS。要解决这个问题,首先必须弄清陆军作战复杂系统ABMS的机理所在。就这两个问题,在研究复杂性理论概念核心原理的基础上,构建了复杂性思维模式框架——复杂性分析二维结构,并由此探索了陆军作战复杂系统ABMS的机理:二维结构、"四个要素"、基本过程和陆战Agent模型框架,为陆军作战复杂系统的ABMS奠定了基础。     

基于改进TOPSIS法和蚁群算法的反TBM 目标群目标分配研究*

基于改进的TOPSIS法和蚁群算法,以弹道导弹目标群为研究对象,研究了反导指控系统对目标群的目标分配问题。首先通过改进的TOPSIS法确定TBM目标群威胁排序并基于拦截排序准则确定拦截排序;其次使作战效能最大化,基于蚁群算法确定目标的最优分配方案;最后通过仿真实例验证了在考虑目标威胁值排序前提下采用此算法,可使目标群分配方案更加科学有效和符合反导作战实际。     

基于数据耕耘的探索性仿真实验框架研究

基于数据耕耘思想,设计了探索性仿真实验框架,并对框架中每个部分进行了简要探讨。基于数据耕耘的探索性仿真实验框架由乒乓式对抗推演预实验、单个仿真想定生成环、仿真想定空间运行环和仿真结果分析环四部分组成,通过将人的经验、智慧与计算机仿真手段相结合,在多次循环的过程中逐渐形成所需的军事决策建议或寻找感兴趣的战争规律。通过构建探索性仿真实验框架,能够将各种定量、定性分析方法整合起来,围绕实验目标实施探索性仿真实验。     

车联网环境下车辆协同高精度定位研究进展

车辆位置信息是许多智能交通应用的基础,如车辆导航、路径规划和车辆编队等。现有研究中融合单车车载多源传感器的定位方法无法有效解决城市峡谷、隧道和立交桥等卫星信号不可用条件下的车辆定位问题。围绕车辆高精度定位进行了综合评述,主要深入研究分析了车辆协同定位技术。首先分析了单车自主定位的关键技术及其主要应用场景;然后对车辆协同定位框架进行了研究,并对目标关联算法和多源数据融合算法进行了分析;最后展望了车联网环境下车辆协同定位的发展趋势。研究表明,高精度高可靠定位研究还存在许多关键技术未突破,车联网环境下的车辆协同定位利用无线通信实现多源定位传感器信息动态交互,为智能汽车定位系统研发提供新思路。     

基于物链网的军事供应链管理研究

现代化军事供应链管理是实现智慧军事物流的必要手段,智能军事供应链管理离不开物联网、区块链、云计算、人工智能等高新技术的支撑。随着物联网与区块链技术的发展,研究两者深度融合的物链网应用对提高军事供应链管理具有重要意义。本文通过分析军事供应连管理特点及需求分析总结出军事供应链管理具有内外区分、网系异构、平战结合等特点,应用物联网与区块链融合可直击军事供应链痛点问题,为解决军事供应链管理智能化发展、快速响应、共识共享、安全保密等需求提供新思路;同时,对物链网应用的技术融合化、链条联盟化、连接标准化、计算边缘化展开研究,提出军事供应链在可追溯与可视化、供应链协同以及物流流程优化等方面的智能管理,以期为物链网在军事供应链管理的应用提供一定参考。     

Research on fuze microswitch based on corona discharge effect

Abnormal voltages such as electrostatic, constant current, and strong electromagnetic signals can erro-neously trigger operation of MEMS pyrotechnics and control systems in a fuze, which may result in casualties. This study designs a solid-state micro-scale switch by combining the corona gas discharge theory of asymmetric electric fields and Peek's Law. The MEMS switch can be transferred from "off" to"on" through the gas breakdown between the corona electrodes. In the model, one of the two electrodes is spherical and the other flat, so a non-uniform electric field is formed around the electrodes. The theoretical work is as follows. First, the relation among the radius of curvature of the spherical electrode, the discharge gap, and the air breakdown voltage is obtained; to meet the low voltage (30-60 V) required to drive the MEMS switch, the radius of curvature of the spherical electrode needs to be 10-50 μm and the discharge gap between the two electrodes needs to be 9-11 μm. Second, the optimal ratio ε is introduced to parameterize the model. Finally, the corona discharge structural parameters are determined by comparing the theoretical and electric field simulation results. The switch is then fabricated via MEMS processing. A hardware test platform is built and the performing chip tested. It is found that when the electrode gap is 9 μm, the electrostatic voltage is at least 37.3 V, with an error of 2.6% between the actual and theoretical air breakdown voltages. When the electrode gap is 11 μm, the electrostatic voltage is at least 42.3 V, with an error of 10.5% between the actual and theoretical air breakdown voltages. Both cases meet the design requirements.     

Automated integration of real-time and non-real-time defense systems

Various application domains require the integration of distributed real-time or near-real-time systems with non-real-time systems.Smart cities,smart homes,ambient intelligent systems,or network-centric defense systems are among these application domains.Data Distribution Service(DDS)is a communi-cation mechanism based on Data-Centric Publish-Subscribe(DCPS)model.It is used for distributed systems with real-time operational constraints.Java Message Service(JMS)is a messaging standard for enterprise systems using Service Oriented Architecture(SOA)for non-real-time operations.JMS allows Java programs to exchange messages in a loosely coupled fashion.JMS also supports sending and receiving messages using a messaging queue and a publish-subscribe interface.In this article,we pro-pose an architecture enabling the automated integration of distributed real-time and non-real-time systems.We test our proposed architecture using a distributed Command,Control,Communications,Computers,and Intelligence(C4I)system.The system has DDS-based real-time Combat Management System components deployed to naval warships,and SOA-based non-real-time Command and Control components used at headquarters.The proposed solution enables the exchange of data between these two systems efficiently.We compare the proposed solution with a similar study.Our solution is superior in terms of automation support,ease of implementation,scalability,and performance.     

A novel DOA estimation algorithm using directional antennas in cylindrical conformal arrays

In this paper, a novel direction of arrival (DOA) estimation algorithm using directional antennas in cy-lindrical conformal arrays (CCAs) is proposed. To eliminate the shadow effect, we divide the CCAs into several subarrays to obtain the complete output vector. Considering the anisotropic radiation pattern of a CCA, which cannot be separated from the manifold matrix, an improved interpolation method is investigated to transform the directional subarray into omnidirectional virtual nested arrays without non-orthogonal perturbation on the noise vector. Then, the cross-correlation matrix (CCM) of the sub-arrays is used to generate the consecutive co-arrays without redundant elements and eliminate the noise vector. Finally, the full-rank equivalent covariance matrix is constructed using the output of co-arrays, and the unitary estimation of the signal parameters via rotational invariance techniques (ESPRIT) is performed on the equivalent covariance matrix to estimate the DOAs with low computational complexity. Numerical simulations verify the superior performance of the proposed algorithm, especially under a low signal-to-noise ratio (SNR) environment.