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。     

重点目标防空作战中多预警机协同探测空域配置

针对重点目标防空作战中预警机空域配置问题,构建了多预警机阵位选择和架数优化配置模型.通过分析重点目标预警线划分,确定预警机防空作战具体任务,从而构建其阵位选择量化模型,并以此为基础,提出了一种在确保自身安全且充分发挥预警机固有探测威力前提下的多预警机并立航线和串接航线空域配置量化模型.实例运算结果表明,该模型能够对比分...     

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。     

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.     

Repeater jamming suppression method for pulse Doppler fuze based on identity recognition and chaotic encryption

Pulse Doppler (PD) fuze is widely used in current battlefield. However, with the threat of repeater jamming, especially digital radio frequency memory technology, the deficiency in the anti-repeater jamming of a traditional PD fuze increasingly emerges. Therefore, a repeater jamming suppression method for a PD fuze based on identity (ID) recognition and chaotic encryption is proposed. Every fuze has its own ID which is encrypted with different chaotic binary sequences in every pulse period of the transmitted signal. The thumbtack-shaped ambiguity function shows a good resolution and distance cut-off characteristic. The ability of anti-repeater jamming is emphatically analyzed, and the results at different signal-to-noise ratio (SNR) show a strong anti-repeater jamming ability and range resolution that the proposed method possesses. Furthermore, the anti-repeater jamming ability is influenced by processing gain, bit error rate (BER) and correlation function. The simulation result validates the theo-retical analysis, it shows the proposed method can significantly improve the anti-repeater jamming ability of a PD fuze.