An Improved Particle Filter Map Matching Algorithm for Personal Inertial Positioning

The current particle filtering map matching algorithm has problems such as low map utilization and poor accuracy of turnoff positioning, etc. This paper proposed an improved particle filtering-based map-matching algorithm for the inertial positioning of personnel. The historical moment position constraint and feasible region constraint of particles were introduced in this paper. A resampling method based on multi-stage backtracking of particles was proposed. Therefore, the effectiveness of newly generated particles could be guaranteed. The utilization rate of map information could be improved, thus enhancing the accuracy of personnel localization. The walking experiment results showed that, compared with the traditional PDR algorithm, the proposed method had higher localization accuracy and better repeatability of the localization trajectory for multi-turn paths. Under the total travel of 480 meters, the deviation of the starting end point was less than 2 meters, which was about 0.4% of the total travel.

A novel vehicle navigation map matching algorithm based on fuzzy logic and its application

A new real-time map matching algorithm based on fuzzy logic is proposed. 3 main factors affecting the reliability of map matching, including the distance between the vehicle location and the matching road segment, the angle between the vehicle direction and the road segment direction and the road connectivity are discussed. Fuzzy rules for the distance, angle and connectivity are presented to calculate the matching reliability. 2 indicators for estimating the matching reliability are then derived, one is the lower limit of the reliability, and the other is the limit error of the difference between the maximal value and the second-maximal value of the reliability. A real-time map-matching system based on fuzzy logic is therefore developed. Using the real data of global positioning system(GIS) based navigation and geographic information system(GPS) based road map, the method is verified and the (results) prove the effectiveness of the proposed method.

Low-complexity online correction and calibration of pedestrian dead reckoning using map matching and GPS

Dead Reckoning is a relative positioning scheme that is used to infer the change of position relative to a point of origin by measuring the traveled distance and orientation change.Pedestrian Dead Reckoning(PDR)applies this concept to walking persons.The method can be used to track someone's movement in a building after a known landmark like the building's entrance is registered.Here,the movement of a foot and the corresponding direction change is measured and summed up,to infer the current position.Measuring and integrating the corresponding physical parameters,e.g.using inertial sensors,introduces small errors that accumulate quickly into large distance errors.Knowledge of a buildings geography may reduce these errors as it can be used to keep the estimated position from moving through walls and onto likely paths.In this paper,we use building maps to improve localization based on a single foot-mounted inertial sensor.We describe our localization method using zero velocity updates to accurately compute the length of individual steps and a Madgwick filter to determine the step orientation.Even though the computation of individual steps is quite accurate,small errors still accumulate in the long term.We show how correction algorithms using likely and unlikely paths can rectify errors intrinsic to pedestrian dead reckoning tasks,such as orientation and displacement drift,and discuss restrictions and disadvantages of these algorithms.We also present a method of deriving the initial position and orientation from GPS measurements.We verify our PDR correction methods analyzing the corrected and raw trajectories of six participants walking four routes of varying length and complexity through an office building,walking each route three times.Our quantitative results show an endpoint accuracy improvement of up to 60%when using likely paths and 23%when using unlikely paths.However,both approaches can also decrease accuracy in certain scenarios.We identify those scenarios and offer further ideas for improving Pedestrian Dead Reckoning methods.

An accurate indoor map matching algorithm based on activity detection and crowdsourced Wi-Fi

Map matching has been widely investigated in indoor pedestrian navigation to improve positioning accuracy and robustness.This paper proposes an accurate map matching algorithm based on activity detection and crowdsourced Wi-Fi(AiFiMatch).Firstly, by taking indoor road segments between activity-related locations as nodes, and the activity type from one road segment to another as directed edge, the indoor floor plan is abstracted as a directed graph. Secondly, the smartphone’s motion sensors are utilized to detect different activities based on a decision tree and then the pedestrian’s walking trajectory is divided into subtrajectory sequence according to location-related activities. Finally, the sub-trajectory sequence is matched to the directed graph of indoor floor plan to position the pedestrian by using a Hidden Markov Model(HMM). Simultaneously, Wi-Fi fingerprints are bound to road segments based on timestamp. Through crowdsourcing, a radio map of indoor road segments is constructed. The radio map in turn inversely promotes the HMM based map matching algorithm. AiFiMatch is evaluated by the experiments using smartphones in a teaching building. Experimental results show that the pedestrian can be accurately tracked even without knowing the starting position and AiFiMatch is robust to a certain degree of step length and heading direction errors.

A bottom-up method for module-based product platform development through mapping,clustering and matching analysis

Designing product platform could be an effective and efficient solution for manufacturing firms. Product platforms enable firms to provide increased product variety for the marketplace with as little variety between products as possible. Developed consumer products and modules within a firm can further be investigated to find out the possibility of product platform creation. A bottom-up method is proposed for module-based product platform through mapping, clustering and matching analysis. The framework and the parametric model of the method are presented, which consist of three steps:(1) mapping parameters from existing product families to functional modules,(2) clustering the modules within existing module families based on their parameters so as to generate module clusters, and selecting the satisfactory module clusters based on commonality, and(3) matching the parameters of the module clusters to the functional modules in order to capture platform elements. In addition, the parameter matching criterion and mismatching treatment are put forward to ensure the effectiveness of the platform process, while standardization and serialization of the platform element are presented. A design case of the belt conveyor is studied to demonstrate the feasibility of the proposed method.

A Map-Matching Algorithm forGPS/DR Integrated Navigation Systems Basedon Dempster-Shafer Evidence Reasoning

GPS (Global Positioning System) has been widely used in car navigation systems. Most car navigation systems estimate the car position from GPS and DR (dead reckoning). However, the unknown GPS noise characteristic and the unbounded DR accumulation of errors over time make the position information with undesirable position errors. The map matching can improve the position accuracy and availability of the vehicular position system. In this paper, general principle of map matching is investigated according to segmentation and feature extraction, and a map matching algorithm based on D-S (Dempster-Shafer) evidence reasoning for GPS integrated navigation system is proposed, which can find the exact road on which a car moves. For the experiments, a car navigation system is developed with some sensors and the field test demonstrates the effectiveness and applicability of the algorithm for the car location and navigation.

Scan matching using line segment relationships for map-based localization of mobile robot

A new scan matching method for mobile robot localization is presented, which takes line segment as the feature and matches the real scans in the given reference map by relationships of the directional-defined line segments. The alignment was done by hierarchically identifying the multiple relationships and the result was recorded in a correspondence matrix, where the best match is defined and selected for localization. It is indicated that the searching algorithm of the best match can find the ambiguities and get rid of them. This method with less computational cost works well in occluded environment, and can correct the error in pose estimation without the need for the estimation itself. The efficiency, accuracy and robustness of this method were verified by experiments of localization in an occluded environment and a long-distance indoor navigation.

基于Spark Streaming的海量GPS数据实时地图匹配算法

浮动车GPS数据作为交通信息处理的基础,随着被监控车辆数量的高速增长,产生了海量GPS数据,对地图匹配提出了挑战。为了解决传统匹配方法难以满足匹配效率和精度的不足,提出一种针对海量GPS数据的实时并行地图匹配算法,能够同时保证较高匹配精度和运算效率。为构建一种面向实时数据流的高效、准确实时地图匹配算法,首先通过引入速度、方向综合权重因子对依赖历史轨迹的离线地图匹配算法进行重构,进而引入Spark Streaming分布式计算框架,实现地图匹配算法的实时、并行运算,大幅提升实时地图匹配效率。实验结果表明,该算法在复杂路段的匹配准确率较常规拓扑匹配算法提高10%以上,整体匹配准确率达到95%以上;在匹配效率方面,较同等数量的单机服务器效率可提高4倍左右。实验结果表明,该算法在由11台机器组成的计算集群上实现8000万个GPS数据点的实时地图匹配,证明了该算法可以完成城市地区的实时车辆匹配。

基于无人艇的导航雷达目标检测跟踪算法

在无人艇利用导航雷达进行环境感知的过程中,针对雷达回波图中出现的区域破碎现象以及对运动目标进行跟踪时存在较大误差的问题,提出了一种应用于导航雷达的目标检测跟踪方法提高无人艇对水面目标的检测能力。首先,对雷达原始回波图像解析并进行预处理操作;其次,在图像连通的基础上,设计自适应阈值分割Hausdorff匹配算法对回波图和地图进行匹配,区分属于目标和陆地的回波;然后,对连续两帧的雷达回波图进行目标匹配;最后,通过加入预测序列模型的经验模态分解算法优化检测跟踪结果,提高获取目标信息的准确性。实验验证结果表明:对1 km内相对运动速度低于30节的水面目标,所提方法目标检测概率提升了6.5%,距离误差低于2%,航速误差低于6%,航向误差低于6°,整体性能优于工程中常用的检测跟踪方法。

一种车辆GPS轨迹数据的改进地图匹配算法

文中提出一种车辆GPS轨迹数据的改进地图匹配算法.以车辆GPS轨迹数据进行隐马尔可夫模型动态地图匹配后的缓冲区内候选路径为初始群体,以遗传算法中的改进的适应度函数为基准进行半交叉迭代,选择车辆轨迹更优的匹配路径;设计了改进地图匹配方法的算法流程;利用微软亚洲团队的GeoLift轨迹数据集验证了改进方法的有效性.

面向地图匹配的室内位置-语义模型设计

传统的室内空间信息模型或者过于复杂导致操作性较差,或者没有充分表达地图匹配所需的空间要素信息,阻碍地图匹配方法的高效实施。该研究将以构建能够有效支撑地图匹配的室内空间信息模型作为研究目标,此模型应明确室内空间要素的表达内容,并应确定具体的表达方法。模型的构建应以地图匹配方法的机理为基础,以室内地图匹配的实际需要为导向,以表达支撑室内地图匹配的空间信息为目的,分别对室内空间要素的位置及属性,室内空间要素之间的拓扑关系进行表达。该研究构建面向地图匹配的室内位置-语义模型。实验表明此模型较为简洁且信息完备,可在保证地图匹配实际需要的同时提高运行效率。

采用FME和ArcMap实现地形图制作服务

为了实现数字地形图DLG快速制作地图服务,解决数据格式转换和数字地形图DLG符号自动匹配的问题,采用FME空间数据转换系统实现CASS DWG至GIS GDB数据格式的无缝转换,且保留所需的属性信息,如图层名、要素编码、角度等;采用ArcMap相关功能模块,将要素编码与ArcMap符号库关联起来,实现要素与符号的自动匹配,从而实现数字地形图DLG快速制作地图服务及其衍生的各类专题图制作服务。

一种结合光流追踪的双目视觉里程计算法

针对特征点法视觉里程计频繁计算和匹配描述子导致系统实时性能变差的问题,提出一种结合光流追踪的双目视觉里程计算法;首先进行初始化,生成初始的关键帧和地图点,随后在追踪线程中使用光流追踪特征点获取匹配关系,计算并优化相机位姿;满足生成关键帧的条件后,将当前帧设置为关键帧,提取图像的ORB特征点,并使用描述子匹配获取与上一关键帧特征点的匹配关系,三角化生成新的地图点;最后在优化线程中将新的关键帧和地图点使用滑动窗口算法进行优化,剔除冗余关键帧和地图点;在KITTI数据集上的实验结果表明,所提出的算法轨迹误差与双目模式下的ORB-SLAM3算法处于同一水平,同时实时性能有大幅度提高,追踪每一帧图像的平均时间从52 ms降至16 ms,在保证高精度的情况下运行速度大大提高,具有较高的实用价值。

基于云平台的新能源汽车通信网络定位技术

现行技术在新能源汽车通信网络定位中的应用效果不佳,定位偏移率较高,因此提出基于云平台的新能源汽车通信网络定位技术。利用云平台传输和存储新能源汽车全球定位系统(Global Positioning System,GPS)数据,通过地图匹配新能源汽车定位,采用差分定位算法确定新能源汽车位置,并通过地图可视化展示定位结果,以此实现基于云平台的新能源汽车通信网络定位。实验结果表明,所设计的技术定位偏移率在1%以内,在新能源汽车发展中具有较好的通信网络定位效果。

GPS/DRS/DMAP汽车定位导航系统

阐述了一种基于单片机的由速率陀螺、磁罗盘和里程仪组成的新型航迹推算系统及其工作原理 ,在此基础上设计了多级滤波组合方式GPS(GlobalPo sitioningSystem) /DRS(DeadReckoningSystem)汽车定位导航系统 ,并通过地图匹配进一步提高定位精度 ,同时利用GSM(GlobalSystemforMobilecommunications)进行定位数据的无线传输 .跑车实验表明该系统具有较高的定位精度和可靠性 .

基于知识图谱的制造资源推荐方法研究

在新时期智能制造飞速发展的背景下,制造业规模持续扩大但是制造模式和技术平台落后,许多企业制造资源联系不紧密,难以形成高效协同的产品制造方法。为在产品制造加工时给出合理的制造资源推荐方案,提高产品制造效率量,提出了一种基于知识图谱的制造资源推荐方法,通过本体构建和实体抽取技术构建制造领域知识图谱以及零件需求知识图谱,实现供需信息的表达,然后根据知识图谱嵌入方法,实现制造资源和产品需求的匹配,得到最优的制造资源推荐,实现了对于产品制造需求的快速响应和精准资源推荐,并通过实例对该方法进行了验证。

基于MapObjects的浮动车中心地图匹配综合算法开发

浮动车技术是一种新型交通流信息采集技术。以杭州市浮动车中心地图匹配算法开发为例,对地图匹配算法的实现步骤、组成进行了分析,基于MapObects组件技术,给出了部分功能的具体实现方法。

GNSS/INU/DMAP组合导航定位技术在车辆导航中的应用

利用先进的组合导航技术组成GNSS系统,充分发挥GPS和GLONASS各自优势,并采用航迹推算(DR)技术、精确地图匹配(DMAP)技术组成GNSS/INU/DMAP组合导航系统,提高了系统精度和可靠性,并利用GSM网进行定位数据的无线传输。该系统将卫星导航技术、惯性导航技术、计算机技术、无线通讯技术融合在一起,实际跑车试验验证了系统具有全方位、全天候、无遮挡、高精度的特点。

基于MAPGIS的地图数字化与地图接边

地图是GIS主要数据源 ,地图数字化是GIS数据输入的主要手段。分幅数字化常导致数据在接边处不匹配 ,地图接边是实现数字匹配的重要手段。文中详细阐述了MAPGIS地图数字化输入方法 ,通过MAPGIS图形变换功能 ,总结了 9幅分幅数字化地图拼接过程 ,通过MAPGIS图幅接边功能介绍了交互式、全自动。