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1.
针对利用惯性测量单元进行行人航位推算（PDR）时,其定位误差会随时间累积的问题,提出了一种基于多传感器融合的室内行人航位推算方法;对于智能移动设备的低成本多传感器,设计了基于无迹卡尔曼滤波（UKF）的初始对准,设定4种阈值条件进行步伐状态检测;在行走过程中,针对步长和航向角误差累积的问题,利用基于UKF的零速度更新（ZUPT）对速度误差进行修正,零角速率更新（ZARU）和磁力计融合对航向角误差进行修正,从而有效提高了行人最终的位置精度。试验结果表明：使用该方法可以有效提高PDR位置精度,平均位置偏差占总路程的1.5%左右。 相似文献
2.
作为室内位置服务的基础,室内定位技术近年来得到了广泛的关注。针对现有室内定位技术存在成本高、精度有限以及效率不足等问题,提出了一种融合人类活动识别、行人航迹推算(pedestrian dead recko-ning,PDR)以及地标匹配修正等技术的室内行人位置推算方法。该方法使用基于智能手机的PDR技术来估算用户的位置信息,而人类活动识别技术则用来感知用户室内移动行为中的特定地标,利用这些地标信息来辅助修正PDR轨迹中产生的累积误差。此外,为了解决用户初始位置未知的问题,引入隐式马尔科夫模型进行推断,并提出了一种顾及室内环境特征的维特比算法来确定用户轨迹。实验结果显示,所提方法在提高室内行人移动行为识别和定位精度的同时,有效实现了用户室内轨迹的追踪。 相似文献
3.
The current low-cost global navigation satellite systems (GNSS) receiver cannot calculate satisfactory positioning results for pedestrian applications in urban areas with dense buildings due to multipath and non-line-of-sight effects. We develop a rectified positioning method using a basic three-dimensional city building model and ray-tracing simulation to mitigate the signal reflection effects. This proposed method is achieved by implementing a particle filter to distribute possible position candidates. The likelihood of each candidate is evaluated based on the similarity between the pseudorange measurement and simulated pseudorange of the candidate. Finally, the expectation of all the candidates is the rectified positioning of the proposed map method. The proposed method will serve as one sensor of an integrated system in the future. For this purpose, we successfully define a positioning accuracy based on the distribution of the candidates and their pseudorange similarity. The real data are recorded at an urban canyon environment in the Chiyoda district of Tokyo using a commercial grade u-blox GNSS receiver. Both static and dynamic tests were performed. With the aid of GLONASS and QZSS, it is shown that the proposed method can achieve a 4.4-m 1σ positioning error in the tested urban canyon area. 相似文献
4.
Anastasia Petrenko Anton Sizo Winchel Qian A. Dylan Knowles Amin Tavassolian Kevin Stanley Scott Bell 《Transactions in GIS》2014,18(3):351-369
The popularization of tracking devices, such as GPS, accelerometers and smartphones, have made it possible to detect, record, and analyze new patterns of human movement and behavior. However, employing GPS alone for indoor localization is not always possible due to the system's inability to determine location inside buildings or in places of signal occlusion. In this context, the application of local wireless networks for determining position is a promising alternative solution, although they still suffer from a number of limitations due to energy and IT‐resources. Our research outlines the potential for employing indoor wireless network positioning and sensor‐based systems to improve the collection of tracking data indoors. By applying various methods of GIScience we developed a methodology that can be applicable for diverse human indoor mobility analysis. To show the advantage of the proposed method, we present the result of an experiment that included mobility analysis of 37 participants. We tracked their movements on a university campus over the course of 41 days and demonstrated that their movement behavior can be successfully studied with our proposed method. 相似文献
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利用建筑物中金属结构引起的地磁场扰动可以对室内的行人目标进行定位，而且基于地磁场的定位无需布设任何额外设施，因此可以以低成本实现定位。但仅靠单一的地磁技术无法满足室内定位的精度要求。为了解决磁场数据中单点定位的模糊性问题，本文提出了一种利用粒子滤波算法将PDR与地磁相融合的室内定位方法，并开发了地磁室内导航系统，以智能手机为硬件平台构建磁力计传感器模型，建立匹配轨迹的均方误差准则并实现PDR累积误差实时校正的迭代计算。在68 m×1.8 m的试验区域内，产生的平均定位误差为1.13 m，最大定位误差为2.17 m。本文算法的定位精度比单独PDR算法提升了42%；与单一地磁指纹匹配算法相比，定位精度提高了57%。试验证明，本文提出的融合算法对提高室内定位精度具有显著的作用。 相似文献
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Navigation applications and location-based services are now becoming standard features in smart phones. However, locating
a mobile user anytime anywhere is still a challenging task, especially in GNSS (Global Navigation Satellite System) degraded
and denied environments, such as urban canyons and indoor environments. To approach a seamless indoor/outdoor positioning
solution, Micro-Electro-Mechanical System sensors such as accelerometers, digital compasses, gyros and pressure sensors are
being adopted as augmentation technologies for a GNSS receiver. However, the GNSS degraded and denied environments are typically
contaminated with significant sources of error, which disturb the measurements of these sensors. We introduce a new sensor,
the electromyography (EMG) sensor, for stride detection and stride length estimation and apply these measurements, together
with a digital compass, to a simple pedestrian dead reckoning (PDR) solution. Unlike the accelerometer, which senses the earth
gravity field and the kinematic acceleration of the sensor, the EMG sensor senses action potentials generated by the muscle
contractions of the human body. The EMG signal is independent of the ambient environment and its disturbance sources. Therefore,
it is a good alternative sensor for stride detection and stride length estimation. For evaluating the performance of the EMG
sensor, we carried out several field tests at a sports field and along a pedestrian path. The test results demonstrated that
the accuracy of stride detection was better than 99.5%, the errors of the EMG-derived travelled distances were less than 1.5%,
and the performance of the corresponding PDR solutions was comparable to that of the global positioning system solutions. 相似文献
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提出了一种基于互补滤波融合WiFi和PDR的行人室内定位方法。首先改善WiFi位置指纹定位的KNN算法，通过阈值的设定，排除相似度高但实际上不可能的点，获取动态K值；然后通过行人航位推算（PDR）初始化算法，动态轨迹概率计算，确定PDR初始位置；最后在改进的WiFi和PDR的定位基础上，基于互补滤波原理，根据WiFi和PDR定位的不同特性，利用各自的定位优点，使用WiFi定位修正PDR的定位结果，通过相应权重参数的调整，输出最终融合定位结果。试验过程中，选取3种不同的室内环境区域，试验结果证明了该算法可大大提高室内定位的精度和稳定性。 相似文献
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针对当前WiFi-PDR室内定位中存在的WiFi信号不稳定及行人航位推算（PDR）累积误差大的问题，本文提出了一种融合上下文感知的地标检测辅助WiFi-PDR室内定位方法。该方法利用智能手机所能监测到的上下文信息建立用户模型，采用基于卷积神经网络的用户行为感知和基于WiFi-PDR室内定位的粗粒度位置感知，发现隐藏的室内地标信息，并完成用户在地标位置的位置校正，提高定位准确度。该方法在一定程度上降低了WiFi-PDR室内定位的误差，提高了用户室内定位的精度。经试验验证，该室内定位方法的精度相比于传统的WiFi-PDR方法提高了43.62%。 相似文献
9.
针对复杂环境下传统INS-EKF-ZUPT (IEZ)方法中存在位置及航向误差累积导致定位精度差的问题,本文提出一种能与RTK一同融入IEZ中的磁转向启发式航向约束(MTHDE)算法,并结合该算法设计了一种适用于四正交主方向场景的RTK+IEZ+MTHDE行人定位方法。在具有开阔地带、林荫道、林荫道及建筑半遮挡、室内等场景的约800 m矩形试验轨迹中,对该方法进行了验证。结果表明,RTK及MTHDE算法对IEZ的位置及航向进行了有效的修正,在12个参考点的试验轨迹中,该方法的平均平面定位误差为1.35 m,优于传统RTK+IEZ方法。 相似文献
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行人航迹推算(PDR)是室内定位领域中应用最广泛,最廉价有效的一种定位方法,但其误差会随时间而累积。为了有效减少航迹推算的累计误差,基于航迹推算原理建立了粒子滤波模型,辅以室内地图约束粒子传播方向;同时提出虚拟路标匹配算法克服传统定位方法中由于航向角变化误差模型不准确导致定位失败的缺点。结果表明,该算法可以有效的提高航迹推算的稳健性。 相似文献
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《制图学和地理信息科学》2013,40(4):305-310
To determine the correct floor of a user in a multi-storey building using pedestrian navigation and guidance services is a challenging task, as most common indoor location techniques provide only 2D position determination. Consequently, it is recommended to augment the position determination system with a barometric pressure sensor for direct observation of height differences. In the research project NAVIO (Pedestrian Navigation Systems in Combined Indoor/Outdoor Environments), tests with a barometric pressure sensor have been performed and their results are presented in this paper. The tests show that using a barometric pressure sensor, the building floor at which a person is located can be determined with the standard deviation of better than ± 0.5 m. 相似文献
13.
Arnab Dutta Sameer Saran A. Senthil Kumar 《Journal of the Indian Society of Remote Sensing》2017,45(6):993-1004
CityGML is an open data model for storage and exchange of 3D city models. It is categorised into thirteen thematic classes, i.e., buildings, tunnels, bridges, etc., lacking the other themes such as indoor routing and positioning. With the amplified use of indoor routing and positioning, the need for prerequisite notion of detailed semantic, as well as geometric information of the 3D building data has grown. We intend to extend the CityGML schema to add attributes of indoor features using the facility of Application Domain Extension (ADE) provided by the OGC CityGML 2.0. In this study, we aim to showcase the formation of Indoor Routing and Positioning ADE along with the process concerning its development, such as the 3D model design, network dataset creation, routing, positioning and Unified Modeling Language based ADE application schema generation. This research would help the users to easily store and exchange 3D city data on which they can perform routing and positioning inside the buildings with enhanced semantic and geometric properties. 相似文献
14.
目前行人航迹推算逐渐成为室内定位研究与应用的热点。针对利用陀螺仪推算行人航向时存在较大累积误差的问题，本文提出了一种基于智能手机传感器的行人航向解算算法。该算法根据陀螺仪输出的角速度数据与手机传感器参数计算合适的阈值，实时调节PI调节器的误差补偿系数，对预处理后加速度计和磁力计数据解算的航向角进行补偿，并与陀螺仪数据互补滤波融合，得到融合后的航向角。试验基于低成本智能手机，分别在磁场强弱环境下采集手机传感器数据，对比分析本文算法与传统互补滤波算法及九轴数据融合算法在推算行人航向时的精度。试验结果表明，在室内磁干扰较强的环境下，本文算法与传统互补滤波算法、九轴数据融合算法相比定位精度分别提升了68.4%和65.9%，平均航向误差分别减小了3.4°和1.8°，验证了本文算法有较好的抗磁干扰性能，提高了行人航向角解算的可靠性。 相似文献
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行人路网的完整性和准确性是保障步行导航服务的关键。当前的行人路网大多是基于室外道路设施构建的,缺乏室内可步行路径的数据支持,无法在导航应用中提供准确、真实的最优路径规划服务。鉴于此,本文提出了一种基于众源数据的室内外一体化行人路网构建方法,采用智能手机定位传感器与惯性传感器记录的众源轨迹,首先对缺失或者漂移的室内步行数据进行筛选,然后使用改进的行人航位推算(PDR)方法推算出准确的室内轨迹,进而采用莫尔斯理论生成涵盖室内外行人路径的完整行人路网。试验分析中对搜集到的260条步行轨迹数据进行行人路网构建,并使用高精度测量设备采集真实路网数据进行对比分析,结合OSM数据对试验结果进行综合评价。试验结果表明,本文方法能够准确、完整地生成室内外一体化行人路网。 相似文献
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准确的步数统计是进行人员航位推算的关键,通过分析行人运动模型及步行姿态,设计了一种基于零速检测的加速度量测幅值计步算法,实现了载体坐标系和行人地理坐标系的转换,剔除了伪零速现象,在室内模拟环境下采用低成本的微机电机械系统（micro electro mechanical system,MEMS）惯性测量元件对人员行走进行检测,实现了行人运动姿态的有效识别和步数的精确统计。实验结果表明,该计步方法准确性高,对不同的运动环境（走廊、拐角和楼梯）具有良好的适应性,计步正确率均达到98%以上,并且所用的测量元件功耗低,便于携带,适合室内复杂环境。 相似文献
17.
融合地磁/WiFi/PDR的自适应粒子滤波室内定位 总被引：1，自引：0，他引：1
随着国民经济的快速发展，人们在室内活动的时间越来越长，室内空间环境也越来越复杂，对室内环境的位置与导航服务的需求也越来越高。由于地磁信号具有稳定性的特点，且WiFi技术已得到广泛部署，融合使用地磁和WiFi定位具有一定的优势。因此，本文基于Android系统智能手机作为接收设备，融合地磁、WiFi及行人航迹推算（PDR）技术，通过自适应粒子滤波模型和随机抽样一致性算法对采集的信号进行处理。试验证明，地磁、WiFi、PDR三者融合进行室内定位的方法与其他单类方法相比，实现了将室内定位精度的误差最小降低到1.02 m。 相似文献
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基于GNSS系统的导航定位设备在封闭或受阻环境下导航精度受限,为此,提升地下空间或室内定位精度,摆脱对GNSS的依赖是当前的研究热点。针对该问题,本文研究了LiDAR+IMU+DMI多源传感器导航定位技术,通过将LiDAR控制标靶数据带入卡尔曼滤波方程,计算IMU+DMI组合的误差状态向量,限制其误差发散,从而获取设备的高精度位置。该技术能使移动检测设备完全摆脱对GNSS信号的依赖,实现地下封闭空间移动测量设备精确定位,便于地下空间检测。通过在武汉某地铁试验表明,本文算法适用于地下、室内空间封闭环境中无GNSS信号的移动测量设备高精度导航定位。 相似文献
20.
在测距传感器不断轻量化、小型化以及室内外地图一体化导航应用的驱动下,三维（3D）室内移动测量成为当今研究和应用的热点,在室内建模、室内定位等新兴领域中的应用越来越广泛。3D室内移动测量系统通常配备激光扫描仪、全景相机、惯性测量单元（inertial measurement unit,IMU）系统和里程计等传感器,虽能实现3D室内点云数据的采集,但其距离传感器-激光扫描仪价格昂贵且便携性较差。彩色深度（RGB depth,RGB-D）相机为低成本3D室内移动测量系统构建提供了新的距离成像传感器选择,但主流型号RGB-D相机视场角小,继而导致数据采集效率远低于传统激光扫描仪,难以做到点云数据的完整覆盖与稳健采集,且易造成同时定位与制图（simultaneous localization and mapping,SLAM）过程中跟踪失败。针对以上问题,构建了一种低成本室内3D移动测量系统采集设备,通过组合多台消费级RGB-D相机构成大视场RGB-D相机阵列,提出了一种阵列RGB-D相机内外参数标定方法,并通过实验检验了设计系统采集的点云数据的精度。 相似文献