基于GPS的短基线姿态系统研究

设计一套基于全球定位系统(GPS)载波相位测量的短基线姿态系统。给出了系统的硬件结构,研究了一种综合利用QR分解法与卫星基线几何分布的模糊度解算方法,同时,提出了一种非单位向量的四元数姿态解算方法。经过静态和动态实验证明该系统可行。在基线为0.36m的条件下,星历收集完成后在30 s内可以计算出姿态角、偏航角,计算精度可以达到0.5°。     

Integer least squares with quadratic equality constraints and its application to GNSS attitude determination systems

In this paper we introduce the quadratically constrained integer least-squares problem and show how the LAMBDA method can be used to solve it for the purpose of GNSS attitude determination. The integer least-squares principle with quadratic equality constraints (ILSQE) is used to formulate our cost function. The solution of the ILSQE problem is derived and it is shown how the solution can be computed efficiently and rigorously with a novel LAMBDA based method. Experimental results with various single frequency GPS receivers are given to show the effectiveness of the proposed method. The method is also compared with some current methods of GNSS attitude determination. Apart from its efficiency, the proposed method is shown to dramatically improve the success rates of integer ambiguity GNSS attitude resolution. Recommended by Editor Hyun Seok Yang. This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education, Science and Technology (No. R11-2008-014-02001-0). The research of the second author was done in the framework of his ARC International Linkage Professorial Fellowship, at Curtin University of Technology, Perth, Australia, with Professor Will Featherstone as his host. These supports are greatly acknowledged. Chansik Park received the B.S., M.S., and Ph.D. degrees in Electrical Engineering from Seoul National University in 1984, 1986, and 1997 respectively. He is currently with the School of Electrical and Computer Engineering, Chungbuk National University, Cheongju, Korea. His research interests include GNSS, SDR, AJ, ITS and WSN. Peter J. G. Teunissen has 20 years of research experience in GNSS Positioning and Navigation. He is the inventor of the LAMBDA method for GNSS carrier phase ambiguity resolution. He is the Head of the Department of Earth Observation and Space Systems of the Delft University of Technology and a member of the Royal Netherlands Academy of Sciences.     

基于格理论的模糊度快速解算方法

为了兼顾未来全球卫星导航系统（GNSS）的兼容与互操作，解决多频多模高维模糊度在常规方法下解算效率低的问题，基于格理论，提出了一种最近格点（CLP）搜索算法对模糊度整型值进行搜索。首先，将模糊度搜索转化为对格中已知格点的最近格点搜索问题；然后，根据格基规约改进得出具有最小可能长度且相互正交的格基向量；最后，采用CLP搜索算法搜索出最优的模糊度参数值。通过模拟实验和实测数据实验验证得出，所提的CLP搜索算法理论上相较经典的最小二乘模糊度降相关（LAMBDA）和改进的LAMBDA（MLAMBDA）算法对模糊度参数的解算效率更高且更可靠，且CLP搜索算法每一个参数搜索时间稳定在0.01 s，即使在高维情况下，CLP搜索算法的搜索依然稳定可靠。     

变粒度搜索算法与整周模糊度解算

LAMBDA方法应用于GNSS单频单点载波相位定位时,其整周模糊度的搜索域过大,解算速度过慢,制约了单频单点精确定位技术的应用。针对这一问题,结合粗糙整数映射理论,提出变粒度搜索算法,通过改善整周模糊度搜索区域的拓扑结构,并采用有粒度的粗糙整数作为搜索单元,可有效提高搜索效率。仿真结果表明,基本实现了单频单点载波相位准实时定位。     

学习型离散排超联赛算法求解带时间窗的绿色多车型两级车辆路径问题

针对现实中广泛存在的带时间窗的绿色多车型两级车辆路径问题(G2E-HVRP-TW),本文提出一种结合加权K-means算法(WKA)的学习型离散排超联赛算法(LDVPLA)进行求解.首先,根据该问题规模大、约束多的特点,采用WKA将原问题G2E-HVRP-TW分解为一个绿色多车型车辆路径子问题(GHVRP)和一组带时间窗的GHVRP(GHVRP-TW),从而实现两级问题间的部分解耦,以合理缩小搜索空间.然后,利用LDVPLA求解分解后的一系列子问题,并将各子问题的解合并后得到原问题的解. LDVPLA在竞赛阶段将标准排超联赛算法(VPLA)中实数个体更新操作替换为一系列排序操作,使其能够直接在问题离散解空间内执行基于VPLA机制的搜索,可提高搜索效率;在学习阶段构建三维概率矩阵模型合理学习并积累优质解信息,有利于驱动算法较快到达解空间中的优质解区域执行搜索;在淘汰阶段设计一种重启策略,可避免算法过早陷入局部最优.最后,通过在不同规模算例上的仿真实验和算法对比,验证了所提算法的有效性.     

试验场中“北斗”卫星导航系统的测姿算法研究

本文对试验场中“北斗”卫星导航系统的姿态测量方法进行研究,从试验场实际需求和“北斗”卫星导航系统的特点出发,提出了用于试验场的四天线姿态测量算法,以及双天线、单天线航向算法,并研究了在试验场中,使用“北斗”卫星导航系统进行姿态测量时,多径效应和天线架设位置两个主要误差源对精度的影响。     

测量精度约束的模糊度搜索定位算法

为了快速且准确地固定整周模糊度,针对 LAMBDA 算法存在整周模糊度搜索范围过广、搜索效率低等问题,提出一种基于测量精度约束的模糊度搜索算法。该算法在最小二乘问题得到最佳加权的情况下,以标准差分进化（DE）算法为基础、载波相位测量精度为约束条件进行模糊度固定解的检验。该算法解决了不同卫星高度角产生的影响,在解算三维整周模糊度时能够达到 99% 的解算成功率。相比于 MLAMBDA、DE、自适应加权的差分进化（AWDE）算法,该算法进一步提高了模糊度的解算效率和成功率。     

多分辨率算法在磁强计辅助GPS定向测姿中的应用

基于多分辨率算法的姿态角搜索算法，能够提高模糊度的计算成功率，但基于多分辨率算法的姿态角搜索算法需要先验的姿态角信息，而电子磁强计能提供较为准确的姿态角信息，所以我们可以利用其姿态角信息来应用到GPS快速定姿中。将其姿态角信息应用到多分辨率算法中，这样能够大大提高系统的快速性和姿态角的精度。     

基于变步长算法的航天测控雷达多站跟踪技术研究

径向速度作为现代雷达测量目标特征的重要参量,提高对其的精确测量能力是目前航天测控领域重要的研究方向之一。实际上一台单脉冲雷达通常综合测距、速、角等功能,选取的重复频率不足以使雷达测速无模糊,因此必须进行解速度模糊操作。基于不变量嵌入法的解速度模糊技术更加成熟但解模糊的时间相对较长。变重复频率法能够有效的解速度模糊以获取精确值,但通过实验证明其进行的变频率操作与航天发射领域普遍运用的多站工作模式要求不相符,容易造成信号阻塞导致解速度模糊失败。在传统谱峰搜索方法基础上改进的变步长谱峰搜索方法通过区域搜索,改变检索步长的方式,在单站工作模式下检索7次获取谱峰所在区域,并利用频谱偶对称性质有效减少系统噪声的影响,极大的提升了解速度模糊效率和精度。在多站工作的模式下变步长搜索算法比传统搜索算法更具优势。     

一种长基线组合二维角测向方法

针对长基线相位干涉仪测量无线电辐射源来波方位和仰角可能出现的方向模糊问题,提出了一种正交长基线匹配解测向模糊的方法,并基于正确消除相位差模糊的充要条件建立了该方法正确解测向模糊的概率模型,推导了正确解测向模糊概率的解析表达式。根据工程中常用的并行接收和时分接收处理方式建立了两种相位差测量误差模型,分别给出了该方法在这两种误差模型下正确解测向模糊的概率和测向误差公式,计算机仿真试验验证了其正确性。理论分析和仿真试验表明,该测向方法具有较高的正确解测向模糊概率和测向精度,并且采用不同的接收处理方式对正确解测向模糊的概率和测向精度影响较大。     

Genetic algorithm with iterated local search for solving a location-routing problem

This paper deals with a location routing problem with multiple capacitated depots and one uncapacitated vehicle per depot. We seek for new methods to make location and routing decisions simultaneously and efficiently. For that purpose, we describe a genetic algorithm (GA) combined with an iterative local search (ILS). The main idea behind our hybridization is to improve the solutions generated by the GA using a ILS to intensify the search space. Numerical experiments show that our hybrid algorithm improves, for all instances, the best known solutions previously obtained by the tabu search heuristic.     

低成本GPS接收机定向系统研究

文章采用低成本的GPS接收机设计开发了一套精密定向系统;着重对GPS基线解算中整周模糊度的可靠性进行了研究,提出了姿态测量中三种特殊的有利条件,使得模糊度解算更加迅速和可靠;最后探讨了选用不同高度角参考卫星对定向结果的影响．并给出了试验结果。     

检测器集合生成算法及其应用研究

为了提高阴性选择算法对车辆在线检测的速度,降低检测成本,给出了一种分段检测器集合生成算法代替原有的阴性选择算法中检测器集合生成的穷举法.该算法通过求解递归方程计算候选检测器集规模和递归求解的序号随机生成检测器两个阶段组成.该算法所占用的计算机时间量和空间量都比穷举法小的多.实际应用表明该算法优于穷举法,比穷举法节省近一半的时间.     

天线分集技术在WSNs定位中的应用

针对基于接收信号强度指示（RSSI）的定位算法中根据RSSI测距误差较大的问题,提出了在锚节点上使用天线分集技术的方法。该方法在锚节点上安装2根天线,天线互成90°,采用空间分集。锚节点在接收未知节点广播信号时,选择2根天线中信号强的天线接收信号,并记录RSSI值。实验证明：在锚节点上引入天线分集技术,可以降低无线信号多径衰落的影响,提高RSSI值的稳定性,减小了测距误差,提高了定位精度。     

基于GNSS的编队卫星相对定位模糊度解算性能分析

模糊度解算性能是影响卫星导航系统相对定位精度的决定性因素之一。针对编队卫星的星间相对定位需求,对影响模糊度解算成功率的主要因素及其作用进行了分析。通过多种场景下模糊度解算成功率的定量仿真,说明组合多种GNSS星座、增加观测频率的个数以及选取与星间基线长度相适应的电离层模型,均有利于提高模糊度解算的成功率,该结果对于相对定位性能的预测与编队卫星系统优化设计具有参考意义。     

Skewed general variable neighborhood search for the cumulative capacitated vehicle routing problem

The cumulative capacitated vehicle routing problem (CCVRP) is a relatively new version of the classical capacitated vehicle routing problem, and it is equivalent to a traveling repairman problem with capacity constraints and a homogeneous vehicle fleet, which aims to minimize the total arrival time at customers. Many real‐world applications can be modeled by this problem, such as the important application resulting from the humanitarian aid following a natural disaster. In this paper, two heuristics are proposed. The first one is a constructive heuristic to generate an initial solution and the second is the skewed variable neighborhood search (SVNS) heuristic. The SVNS algorithm starts with the initial solution. At each iteration, the perturbation phase and the local search phase are used to improve the solution of the CCVRP, and the distance function in acceptance criteria phase is used to improve the exploration of faraway valleys. This algorithm is applied to a set of benchmarks, and the comparison results show that the proposed algorithms provide better solutions than those reported in the previous literature on memetic algorithms and adaptive large neighborhood search heuristics.     

GNSS姿态测量接收机性能分析

利用同源射频平台实现了一种全球导航卫星系统（ GNSS）姿态测量的接收机,接收机各射频电路相同且使用同一个晶振驱动,各射频通路之间有相同的信号处理特性。可以将射频通路分为主射频通路和从射频通路,主射频通路实现信号的捕获与跟踪,从射频通路利用差分相位鉴别器完成测量观测量提取。与传统使用独立接收机实现载波差分测向不同,主射频通道进入跟踪状态后立即输出观测量,无需检测载波半周跳变,实现快速姿态测量。利用GNSS姿态测量接收机、Novatel接收机以及惯性导航系统进行了跑车实验,实验结果表明：姿态测量接收机具有更好的载波测量输出能力,姿态测量精度和商业接收机相当。     

An efficient data mining method for learning Bayesian networks using an evolutionary algorithm-based hybrid approach

Given the explosive growth of data collected from current business environment, data mining can potentially discover new knowledge to improve managerial decision making. This paper proposes a novel data mining approach that employs an evolutionary algorithm to discover knowledge represented in Bayesian networks. The approach is applied successfully to handle the business problem of finding response models from direct marketing data. Learning Bayesian networks from data is a difficult problem. There are two different approaches to the network learning problem. The first one uses dependency analysis, while the second one searches good network structures according to a metric. Unfortunately, both approaches have their own drawbacks. Thus, we propose a novel hybrid algorithm of the two approaches, which consists of two phases, namely, the conditional independence (CI) test and the search phases. In the CI test phase, dependency analysis is conducted to reduce the size of the search space. In the search phase, good Bayesian network models are generated by using an evolutionary algorithm. A new operator is introduced to further enhance the search effectiveness and efficiency. In a number of experiments and comparisons, the hybrid algorithm outperforms MDLEP, our previous algorithm which uses evolutionary programming (EP) for network learning, and other network learning algorithms. We then apply the approach to two data sets of direct marketing and compare the performance of the evolved Bayesian networks obtained by the new algorithm with those by MDLEP, the logistic regression models, the na/spl inodot//spl uml/ve Bayesian classifiers, and the tree-augmented na/spl inodot//spl uml/ve Bayesian network classifiers (TAN). In the comparison, the new algorithm outperforms the others.     

Calculation and correction of attitude parameters without measuring angular velocity

The conventional methods of estimating the parameters of relative attitude of two coordinate trihedrons, a movable trihedron and an immovable one, using representation of vector quantities in projections on the axes of both trihedrons on a finite time interval provide for application of angular velocity of the movable trihedron. This angular velocity is found either by direct measurement or by integration of dynamic equations of angular motion of the solid body correlated with this trihedron. Both ways of calculation of angular velocity have drawbacks. The approach to processing vector information presented below is intended for estimation of the attitude parameters without using any information about the angular velocity of relative motion of the trihedrons. Two problems of determination of attitude of a low-orbit space vehicle are considered as applications.     

GPS姿态系统中周跳的检测及修复方法

讨论了利用GPS载波相位信号测量载体姿态中出现的周跳问题及解决方法。首先根据静态情况下GPS载波相位信号的特点提出了一种基于外推法的周跳检测和修复方法。在此基础上又用故障检测的原理提出了一种利用冗余双差载波相位观测量的周跳检测和修复方法，该方法可以应用于动态情况，其适用条件是要求相邻历元至少有4颗卫星锁定，并且整周模糊度已经固定。文中利用实测数据对提出的方法进行了验证，结果表明两种周跳检测及修复方法是有效的，在GPS姿态系统中，综合运用这两种方法可大大减少系统的初始化次数。