Endogenous Growth and Defense Expenditures: A New Explanation of the Benoit Hypothesis

This paper develops an endogenous growth model to examine the linkage between military expenditures and economic growth. We adopt the modeling strategy where both the supply side and the demand side effects of national defense are taken into considerations. Our result finds that a rise in military spending tends to stimulate the sustained growth rate, confirming Benoit's famous empirical findings.     

基于双目视觉定位技术的无人船航迹跟踪控制室内模型实验

水面无人系统的航向控制与航迹跟踪技术在研究开发阶段一般在室内环境进行调试与运行,该过程需要定位系统进行辅助.实船常用的定位技术难以在室内发挥作用,现有的几种室内定位技术存在成本高、信号传播不稳定等问题.设计了一种基于双目视觉定位技术的船模航迹跟踪控制系统.结合实验场地和实验对象,通过在船模上布置特征物、图像预处理、图像...     

多传感器数据融合系统中的序贯航迹相关算法研究

提出了一种适合于分布式多传感器数据融合的序贯航迹相关算法,对算法进行了仿真,并和最临近法进行了比较。仿真结果表明,该算法性能与传统方法比有很大改善。     

基于模糊综合决策的航迹相关算法

引用模糊综合决策的思想,提出一种新的分布式航迹相关算法．文中论述了多因素模糊综合评判的基本模型,详细讨论了合成运算模型的选择,重点研究了模糊综合航迹关联准则,并通过仿真将它与两种经典方法进行了比较．仿真结果表明,在密集目标环境下和／或交叉、分岔及机动航迹较多的场合,模糊航迹关联算法的性能明显优于传统方法,其正确关联率比传统方法提高了大约35％．     

海洋移动目标多模型运动预测方法

分析海洋移动目标的运动特征,提出了预测前插值的灰色预测方法,改进了航迹变更预测和潜在区域预测模型。通过集成匀速运动预测、航迹变更预测、基于航迹的预测和潜在区域预测,提出多模型运动预测方法及其模型参数配置依据,根据滑动时间窗口中的观测数据与预测值的统计比较,评价不同预测方法的近期预测效果,决策下阶段适宜选择的预测方法。仿真实验表明多模型运动预测比使用单一运动预测方法降低预测风险,提高了预测精度。     

一种神经网络-模糊推理的目标航迹融合方法

在概要介绍NN-FR融合结构的基础上,提出了一种NN-FR多目标航迹融合处理方法,并进行了仿真试验.     

制导雷达组网中航迹处理技术研究

简述了防空体系制导雷达组网中对目标航迹的处理过程,进行了大量的仿真试验,结合仿真试验的结果数据,分析比较了目标航迹相关与目标航迹融合的几种典型处理方法,并针对制导雷达的特点,提出了在制导雷达组网中适用的一种航迹处理方法。     

一种多目标跟踪航迹起始新算法及其性能评估

文中提出了一种多目标跟踪的航迹起始新算法，并对算法的性能进行了详细的理论推导，得出了正确航迹建立概率和虚假航迹建立概率的解析表达式，蒙特卡洛仿真验证了分析的正确性。     

修正的逻辑航迹起始算法

根据目标的运动特性提出了一种基于修正逻辑的航迹起始方法,其主要思想是在航迹起始阶段,对落入相关域中的量测加一个限制条件,以剔除在一定程度上与航迹成V字形的测量点迹。仿真结果表明,这种方法可以有效地在杂波环境中快速获得起始航迹,具有较好的实用价值。     

Adaptive control of track tension estimation using radial basis function neural network

Track tension is a major factor influencing the reliability of a track. In order to reduce the risk of track peel-off, it is necessary to keep track tension constant. However, it is difficult to measure the dynamic tension during off-road operation. Based on the analysis of the relation and external forces depending on free body diagrams of the idler, idler arm, road wheel and road arm, a theoretical estimation model of track tension is built. Comparing estimation results with multibody dynamics simulation results, the rationality of track tension monitor is validated. By the aid of this monitor, a track tension control system is designed, which includes a self-tuning proportional-integral-derivative (PID) controller based on radial basis function neural network, an electro-hydraulic servo system and an idler arm. The tightness of track can be adjusted by turning the idler arm. Simulation results of the vehicle starting process indicate that the controller can reach different expected tensions quickly and accurately. Compared with a traditional PID controller, the proposed controller has a stronger anti-disturbance ability by amending control pa-rameters online.