基于粒子滤波的活动轮廓模型视频跟踪(英文)

跟踪变形目标包括假定目标的全局运动和时间方程的局部变形。粒子滤波算法依靠参数化法选择,但是不能处理曲线的拓扑变化。活动轮廓模型是独立参数化,可以比较好地适应拓扑变化。基于上面两个方法的局限性,将上述两种方法相结合,运用于变形目标的跟踪。实验结果证明,该方法有很强的鲁棒性,对部分遮挡的物体有很强的适应性,证明了该方法的有效性。     

地心甚高轨道星座构形协同捕获控制策略

针对地心甚高轨道星座构形协同捕获控制问题,基于虚拟编队方法设计了协同捕获控制策略,采用三脉冲燃耗最优轨迹规划算法对构形捕获轨迹进行协同规划;并且结合自适应全程积分滑模控制器对卫星各自转移轨迹进行跟踪控制。以10万km轨道高度的三星星座构形捕获为例进行仿真验证,仿真结果表明:该策略可以有效应用于地心甚高轨道星座构形捕获控制,能够在燃耗较少的情况下使星座中卫星同时到达各自的标称位置,同时具有较高的精度。     

海战场舰艇反潜作战的优化配置研究

针对海战场舰艇反潜作战行动的特点,为增大反潜作战能力进行优化配置。在建立数学模型的基础上,以舰艇搜索突击群有效搜索带宽度为主要因素以及其他诸如概率参数的相关要素对反潜搜索能力进行优化配置,从而获得最大反潜搜索能力和最佳作战行动效果。该方法可以较好地为海战场作战行动的模拟仿真和实际应用提供理论依据和决策参考。     

美军无人机蜂群作战研究动态及应对策略

无人机蜂群是以智能化无人控制技术和网络信息系统为支撑的集群式无人作战武器装备,这种新型武器装备势必将成为改变未来战争规则的重要推手.美军作为无人机蜂群作战研究的领跑者,掌握了解其发展动态,学习其相关有益经验做法,参考借鉴其理论体系和关键技术,对于军队打赢未来智能化战争具有重要现实意义.本文通过梳理与总结美军在无人机蜂群...     

基于自由空间光的无人机集群通信载荷技术发展现状与趋势

对基于自由空间光(Free Space Optical,FSO)的无人机集群通信载荷技术应用需求进行了归纳总结,论述了 FSO通信技术及应用在无人机载荷的国内外发展现状,展望了高速移动通信环境下无人机集群FSO通信载荷技术的未来发展趋势,进一步深入分析了应用于无人机集群的FSO通信链路的关键技术.可以预见,基于FSO的...     

无人机集群反制技术剖析

无人机集群作战具有作战效能高、战场生存能力强、效费比极高的巨大优势,将给传统防空系统带来巨大挑战.现有反无人机集群技术大多来源于反无人机技术,但反平台与反集群存在显著差异,必须针对无人机集群自身技战术特点,加强对精确/高效/低成本的集群反制技术研究.因此,本文以剖析无人机集群反制技术的可行性为出发点,首先,从反无人机集...     

Equilibrium customer strategies and social–profit maximization in the single‐server constant retrial queue

We consider the single‐server constant retrial queue with a Poisson arrival process and exponential service and retrial times. This system has not waiting space, so the customers that find the server busy are forced to abandon the system, but they can leave their contact details. Hence, after a service completion, the server seeks for a customer among those that have unsuccessfully applied for service but left their contact details, at a constant retrial rate. We assume that the arriving customers that find the server busy decide whether to leave their contact details or to balk based on a natural reward‐cost structure, which incorporates their desire for service as well as their unwillingness to wait. We examine the customers' behavior, and we identify the Nash equilibrium joining strategies. We also study the corresponding social and profit maximization problems. We consider separately the observable case where the customers get informed about the number of customers waiting for service and the unobservable case where they do not receive this information. Several extensions of the model are also discussed. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

Annealing adaptive search,cross‐entropy,and stochastic approximation in global optimization

The Annealing Adaptive Search (AAS) algorithm for global optimization searches the solution space by sampling from a sequence of Boltzmann distributions. For a class of optimization problems, it has been shown that the complexity of AAS increases at most linearly in the problem dimension. However, despite its desirable property, sampling from a Boltzmann distribution at each iteration of the algorithm remains a practical challenge. Prior work to address this issue has focused on embedding Markov chain‐based sampling techniques within the AAS framework. In this article, based on ideas from the recent Cross‐Entropy method and Model Reference Adaptive Search, we propose an algorithm, called Model‐based Annealing Random Search (MARS), that complements prior work by sampling solutions from a sequence of surrogate distributions that iteratively approximate the target Boltzmann distributions. We establish a novel connection between MARS and the well‐known Stochastic Approximation method. By exploiting this connection, we prove the global convergence of MARS and characterize its asymptotic convergence rate behavior. Our empirical results indicate promising performance of the algorithm in comparison with some of the existing methods. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

邻域加强的并行子空间优化过程

针对基于响应面的并行子空间优化(CSSo-RS)过程的不足,提出了基于邻域加强的改进CSSO-RS优化过程.其主要思路是在子空间优化后,在得到的最优解附近进行全部变量的优化,以更好地协调系统级优化与子空间优化.用经典测试函数及通用航空飞机参数优化问题对该算法进行测试,测试结果表明该算法使CSSO-RS优化效率得到较大的...     

基于种群分类的变尺度免疫克隆选择算法

提出了一种基于种群分类的变尺度免疫克隆选择算法.该算法通过对目标函数进行非线性尺度变换,突出了全局最优解的优势地位;建立记忆子群实现了种群代际进化信息的交换;依据亲和度将抗体分为精英子群、普通子群、劣等子群,并对其分别执行自适应高斯变异、均匀变异和消亡更新等策略,增强了算法的局部和全局搜索能力.引入小生境技术提高了抗体...