航母着舰引导系统概述

文章研究了舰载机着舰引导系统,论述了基于雷达引导系统和卫星导航的相对定位引导系统的特点,从三个方面分析了基于雷达技术的舰载机着舰引导体制的缺陷,并着眼于未来舰载机着舰技术的要求,提出了新一代多站定位引导系统,不仅能实现舰载机的快速精确定位测量,还可以将导航、防撞、通信、进近、着舰、复飞等一系列功能融为一体,为舰载机的导引控制和追尾触舰提供技术保障。     

无人机提高目标定位精度方法研究

无人机电视图像定位技术,由于采用的单站测角测距方法,存在一些无法克服的不足;空间两点交会定位方法,虽然在一定程度上提高了目标定位精度,但还不能达到高定位精度要求。通过空间三点,建立了空间三点交会定位模型;并且与现有的共线定位算法相结合,通过差分定位原理,达到快速与准确获得任意点坐标的目的。     

基于平方根UKF的机载单站无源定位跟踪算法

针对只测角机载无源定位跟踪具有收敛速度慢及定位误差大的缺点,在只测角定位跟踪模型中加入相位差变化率信息并在此基础上引入平方根不敏卡尔曼滤波（UKF）算法来实现定位与跟踪。仿真结果表明增加相位差信息能够改善定位性能,平方根UKF算法具有比EKF算更快的收敛速度和更高的收敛精度,实用性强。     

基于量子遗传算法的TDOA定位技术研究

为了解决TDOA定位估计中遇到的非线性最优化问题,提出了一种联合使用Chan算法和量子遗传算法的混合定位算法,采用二进制量子编码和量子旋转门更新个体,针对TDOA方式进行最佳坐标搜索。仿真结果表明,该算法性能稳定,能找到全局最优的解,相对于Chan算法精度更高,相对于遗传算法有更快的收敛速度。     

调距桨桨毂加载重块考核试验的设计原理

桨毂是调距机构及桨叶等部件的安装基础构件,承受了较大的载荷.从桨毂受力的角度,模拟桨叶受力的加载重块离心力对叶根法兰中心产生的弯矩和离心力能有效模拟实际机构的推力弯矩、扭力弯矩、离心力和离心力扭矩,具备试验可行性.为评估试验误差,将有限元计算方法和试验结合应用,利用试验检验有限元计算的准确性,反之,有限元计算能有效评估...     

基于港口枢纽处TOD公交站点选址模型的设计

本文针对中小型沿海城市提出的成本模型嵌入到公交站点优化方案中,构建各项成本的表达式,整合并建立以成本最小为目标的公交站点选址模型,对TOD公交站点的选址进行合理规划。此模型可有效运用到在中小型沿海城市中港口枢纽处的公交站点合理设置中,即实现乘客从轮渡到公交的零换乘,又能使港口枢纽对港口枢纽出入口与城市道路交汇处的交通现状影响达到最小,公交的通行能力达到最高。     

The impact of transport policies on railroad intermodal freight competitiveness – The case of Belgium

This paper discusses the impact of three freight transport policies aiming to promote railroad intermodal transport in Europe, and examines the case of Belgium as a testing ground. These policies consist in subsidizing intermodal transport operations (such as in Belgium, to stimulate rail transport), internalizing external costs (as recommended by the European Union in order to foster cleaner modes), and adopting a system perspective when optimizing the location of inland intermodal terminals. The study proposes an innovative mixed integer intermodal freight location-allocation model based on hub-location theory and deals with non-linear transport costs in order to replicate economies of distance. Our analysis suggests that subsidizing has a significant impact on the volumes transported by intermodal transport, and, to a lesser extent, that optimizing terminal location increases the competitiveness of intermodal transport. On the other hand, according to our assumptions, internalizing external costs can negatively impact the promotion of intermodality. This finding indicates that innovative last-mile transports are needed in order to reduce the external impacts of drayage operations.     

Promoting carsharing attractiveness and efficiency: An exploratory analysis

Carsharing has grown significantly over recent years. Understanding factors related to the usage and turnover rate of shared cars will help promote the growth of carsharing programs. This study sets station-based shared car booking requests and turnover rates as learning objectives, by which generalized additive mixed models are employed to examine various effects. The results are: (1) stations with more parking spaces, longer business hours and fewer nearby stations are likely to receive more booking requests and have a higher turnover rate; (2) an area with a higher population density, a higher percentage of adults, a higher percentage of males, a greater road density, or more mixed land use is associated with more car usage and a higher turnover rate; (3) stations nearby transit hubs, colleges, and shopping centers attract more shared car users; (4) shared cars are often oversupplied at transit hubs; (5) both transit proximity and housing price present high degrees of nonlinearity in relation to shared car usage and turnover rates. Findings provide evidence for optimizing the usage and efficiency of carsharing programs: carsharing companies should identify underserved areas to initiate new businesses; carsharing seems more competitive in a distance to a bus stop between 1.2 km and 2.4 km, and carsharing is more effectively served in areas with constraints in accessing metro services; carsharing should be optimally discouraged at transit hubs to avoid the oversupply of shared cars; local authorities should develop a location-based and geographically differentiated quota in managing carsharing programs.     

Solving the station-based one-way carsharing network planning problem with relocations and non-linear demand

One-way station-based carsharing systems allow users to return a rented car to any designated station, which could be different from the origin station. Existing research has been mainly focused on the vehicle relocation problem to deal with the travel demand fluctuation over time and demand imbalance in space. However, the strategic planning of the stations’ location and their capacity for one-way carsharing systems has not been well studied yet, especially when considering vehicle relocations simultaneously. This paper presents a Mixed-integer Non-linear Programming (MINLP) model to solve the carsharing station location and capacity problem with vehicle relocations. This entails considering several important components which are for the first time integrated in the same model. Firstly, relocation operations and corresponding relocation costs are taken into consideration to address the imbalance between trip requests and vehicle availability. Secondly, the flexible travel demand at various time steps is taken as the input to the model avoiding deterministic requests. Thirdly, a logit model is constructed to represent the non-linear demand rate by using the ratio of carsharing utility and private car utility. To solve the MINLP model, a customized gradient algorithm is proposed. The application to the SIP network in Suzhou, China, demonstrates that the algorithm can solve a real world large scale problem in reasonable time. The results identify the pricing and parking space rental costs as the key factors influencing the profitability of carsharing operators. Also, the carsharing station location and fleet size impact the vehicle relocation and carsharing patronage.     

Optimal recharging strategies for electric vehicle fleets with duration constraints

Electrical vehicles (EVs) have become a popular green transportation means recently because they have lower energy consumption costs and produce less pollution. The success of EVs relies on technologies to extend their driving range, which can be achieved by the good deployment of EV recharging stations. This paper considers a special EV network composed of fixed routes for an EV fleet, where each EV moves along its own cyclic tour of depots. By setting up a recharging station on a depot, an EV can recharge its battery for no longer than a pre-specified duration constraint. We seek an optimal deployment of recharging stations and an optimal recharging schedule for each EV such that all EVs can continue their tours in the planning horizon with minimum total costs. To solve this difficult location problem, we first propose a mixed integer program (MIP) formulation and then derive four new valid inequalities to shorten the solution time. Eight MIP models, which were created by adding different combinations of the four valid inequalities to the basic model, have been implemented to test their individual effectiveness and synergy over twelve randomly generated EV networks. Valuable managerial insights into the usage of valid inequalities and the relations between the battery capacity and the total costs, number of recharging facilities to be installed, and running time are analyzed.