三坐标雷达目标真实高度估计算法研究

在目标跟踪领域,通过三坐标雷达的测量值(斜距、仰角及方位角)来估算目标的真实高度一直是个难点。目前主要有两类处理方法:坐标转换法和等效地球半径法。前者把与雷达天线相关的三坐标测量值转换到大地坐标系统来计算目标高度;后者充分考虑地球曲率以及大气折射的特性,通过增加地球半径来估算目标的高度。最后对上述的两类方法进行总结、比较与分析。     

一种基于SOAP安全的网络中心发布/订阅机制

针对网络中心发布/订阅系统异步、松散耦合和多对多通信等特点,采用了SOAP消息传递机制对信息进行了封装,从而屏蔽了信息的异构性。考虑到信息传输的可靠性,采用XML-Encryption机制构造SOAP消息,为消息交换和数据传输提供一种安全的保证。实际应用表明该系统在网络中心战中有较好的应用前景。     

某自动补弹系统翻转机构的优化设计

根据自动补弹系统中翻转机构的功能和设计要求,设计了一种新型的翻转机构,使用ADAMS软件对其进行优化设计,得到相应的曲线和较为理想的结果参数。结果表明通过对翻转机构的优化设计,为自动补弹系统翻转机构的改进设计起到指导作用,该方法对自动补弹系统中其他机构的优化分析也具有一定参考价值。     

基于激励机制的装备采办风险总量控制

针对装备采办中的风险总量控制,提出一种激励方式来提高承包商的积极性。在单目标风险控制模型的基础上,建立了多目标风险控制模型,推导出了激励机制下风险控制的最优合同公式。对激励机制中存在的两类错误进行了理论分析和实例验证,得出了两类错误对收益的影响,并在成本控制中得到了应用,有效地提高了装备采办的质量和效率,为军方决策者在装备采办中提供了合理的参考依据。     

胶泥缓冲器的非线性阻尼的控制机理研究

为了改善履带车辆悬挂系统在各种路面的平顺性,对悬挂系统匹配了一款具有非线性特性的粘弹性胶泥缓冲器。为了定量地研究胶泥缓冲器的非线性阻尼控制机理,建立了非线性悬挂系统的动力学方程,将非线性时滞动力系统的随机最优控制规律应用于履带车辆悬挂系统,建立了车辆垂直振动加速度与车速、路况与阻尼比之间的数学关系,从理论上推导出了最佳阻尼比。最后,对履带车辆在F级和G级路面上进行了仿真分析来验证胶泥缓冲器的非线性阻尼的变化规律,结果表明,在0.07~0.18范围内调控阻尼比,可以使车体垂直振动加速度最小。该研究工作为胶泥缓冲器的优化设计和胶泥材料的配方提供了理论指导。     

基于察打任务的无人机作战效能评估

首先根据时敏目标打击的特点,分析了察打任务模式下的察打一体无人机的作战使用。然后对评估体系中察打一体无人机的侦察能力与打击能力相关性进行了分析,同时将任务可执行度作为无人机效能评估的一项动态权衡标准,建立了基于察打任务的无人机效能评估模型,并基于效能指标体系建立了各分项模型。最后通过算例验证了模型的可行性。     

载机扰动下SAR/GMTI旋转目标微多普勒特性分析

目标微动部件激励的雷达微多普勒信号稳定而独特,反映了该目标的本质特征。针对采用相位中心偏置技术(DPCA)的SAR/GMTI系统,研究存在载机扰动下的旋转目标的微多普勒特性。构建飞行平台与微动目标的几何模型,推导旋转目标的微多普勒信号模型,分析典型的载机纵向扰动对微多普勒时频特性构成的影响;并通过仿真实验,验证了上述理论分析的正确性。     

基于χ~2检验的惯性/卫星紧耦合系统故障检测与隔离方法

研究了一种基于χ~2检验的惯性/卫星紧耦合系统故障检测与隔离方法,该方法可利用故障检测函数自动识别单个卫导故障,并实时剔除故障星重构观测信息序列,从而避免了对紧耦合系统的影响。构建数字化仿真环境对所研究的故障检测与隔离方法进行了仿真,仿真结果表明,该方法可在卫星发生故障时及时检测并隔离故障星,并自动实现观测信息重构,保证了紧耦合系统的精度和完好性。     

目标网络分层描述与自修复机制研究?

针对目标网络分层建模与自修复机制问题展开研究。首先建立了分层次的作战目标网络模型,在此基础上提出六种维度的指标以评价作战目标网络在攻击前后能力的变化情况;其次,从预警网络层、火力网络层、指控网络层分析探索作战目标体系在遭受攻击后的最优自修复策略;最后,通过模拟攻击实验仿真分析上述自修复机制的可行性。实验结果表明该目标网络的自修复机制相比传统方法,能够更好地发挥剩余节点的作战效能。     

Value management of diagnostic equipment with cancelation,no‐show,and emergency patients

Magnetic resonance imaging and other multifunctional diagnostic facilities, which are considered as scarce resources of hospitals, typically provide services to patients with different medical needs. This article examines the admission policies during the appointment management of such facilities. We consider two categories of patients: regular patients who are scheduled in advance through an appointment system and emergency patients with randomly generated demands during the workday that must be served as soon as possible. According to the actual medical needs of patients, regular patients are segmented into multiple classes with different cancelation rates, no‐show probabilities, unit value contributions, and average service times. Management makes admission decisions on whether or not to accept a service request from a regular patient during the booking horizon to improve the overall value that could be generated during the workday. The decisions should be made by considering the cancelation and no‐show behavior of booked patients as well as the emergency patients that would have to be served because any overtime service would lead to higher costs. We studied the optimal admission decision using a continuous‐time discrete‐state dynamic programming model. Identifying an optimal policy for this discrete model is analytically intractable and numerically inefficient because the state is multidimensional and infinite. We propose to study a deterministic counterpart of the problem (i.e., the fluid control problem) and to develop a time‐based fluid policy that is shown to be asymptotically optimal for large‐scale problems. Furthermore, we propose to adopt a mixed fluid policy that is developed based on the information obtained from the fluid control problem. Numerical experiments demonstrate that this improved policy works effectively for small‐scale problems. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 287–304, 2016