• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

全球导航卫星系统接收机在无人驾驶车辆中的精度研究。

Study of Global Navigation Satellite System Receivers' Accuracy for Unmanned Vehicles.

作者信息

Miletiev Rosen, Petkov Peter Z, Yordanov Rumen, Brusev Tihomir

机构信息

Faculty of Telecommunication, Technical University of Sofia, 1000 Sofia, Bulgaria.

Faculty of Electronics, Technical University of Sofia, 1000 Sofia, Bulgaria.

出版信息

Sensors (Basel). 2024 Sep 12;24(18):5909. doi: 10.3390/s24185909.

DOI:10.3390/s24185909
PMID:39338653
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11435958/
Abstract

The development of unmanned ground vehicles and unmanned aerial vehicles requires high-precision navigation due to the autonomous motion and higher traffic intensity. The existing L1 band GNSS receivers are a good and cheap decision for smartphones, vehicle navigation, fleet management systems, etc., but their accuracy is not good enough for many civilian purposes. At the same time, real-time kinematic (RTK) navigation allows for position precision in a sub-centimeter range, but the system cost significantly narrows this navigation to a very limited area of applications, such as geodesy. A practical solution includes the integration of dual-band GNSS receivers and inertial sensors to solve high-precision navigation tasks, but GNSS position accuracy may significantly affect IMU performance due to having a great impact on Kalman filter performance in unmanned vehicles. The estimation of dilution-of-precision (DOP) parameters is essential for the filter performance as the optimality of the estimation in the filter is closely connected to the quality of a priori information about the noise covariance matrix and measurement noise covariance. In this regard, the current paper analyzes the DOP parameters of the latest generation dual-band GNSS receivers and compares the results with the L1 ones. The study was accomplished using two types of antennas-L1/L5 band patch and wideband helix antennas, which were designed and assembled by the authors. In addition, the study is extended with a comparison of GNSS receivers from different generations but sold on the market by one of the world's leading GNSS manufacturers. The analyses of dilution-of-precision (DOP) parameters show that the introduction of dual-band receivers may significantly increase the navigation precision in a sub-meter range, in addition to multi-constellation signal reception. The fast advances in the performance of the integrated CPU in GNSS receivers allow the number of correlations and tracking satellites to be increased from 8-10 to 24-30, which also significantly improves the position accuracy even of L1-band receivers.

摘要

由于自主运动和更高的交通密度,无人地面车辆和无人机的发展需要高精度导航。现有的L1频段全球导航卫星系统(GNSS)接收器对于智能手机、车辆导航、车队管理系统等来说是一个不错且便宜的选择,但其精度对于许多民用目的来说还不够好。同时,实时动态(RTK)导航可实现亚厘米级的位置精度,但系统成本将这种导航方式的应用范围大幅缩小至非常有限的领域,如大地测量。一个切实可行的解决方案是将双频段GNSS接收器与惯性传感器集成,以解决高精度导航任务,但由于对无人车辆中的卡尔曼滤波器性能有很大影响,GNSS位置精度可能会显著影响惯性测量单元(IMU)的性能。精度因子(DOP)参数的估计对于滤波器性能至关重要,因为滤波器中估计的最优性与噪声协方差矩阵和测量噪声协方差的先验信息质量密切相关。在这方面,本文分析了最新一代双频段GNSS接收器的DOP参数,并将结果与L1频段的接收器进行比较。该研究使用了两种由作者设计和组装的天线——L1/L5频段贴片天线和宽带螺旋天线来完成。此外,该研究还扩展到对来自不同代但由世界领先的GNSS制造商之一在市场上销售的GNSS接收器进行比较。精度因子(DOP)参数分析表明,除了多星座信号接收外,引入双频段接收器可能会显著提高亚米级范围内的导航精度。GNSS接收器中集成CPU性能的快速提升,使得相关和跟踪卫星的数量从8 - 10颗增加到24 - 30颗,这也显著提高了即使是L1频段接收器的定位精度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/6fa90640ed74/sensors-24-05909-g017a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/4e14ca7c31b4/sensors-24-05909-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/616d00092ff4/sensors-24-05909-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/23b81ae99c3c/sensors-24-05909-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/4f9ea81c8b2c/sensors-24-05909-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/ab79f261f64a/sensors-24-05909-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/faa4ec4e6561/sensors-24-05909-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/b13dc4a314a9/sensors-24-05909-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/e4da304149bb/sensors-24-05909-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/f791206afe09/sensors-24-05909-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/ab03939ea4b3/sensors-24-05909-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/6c6c4c5f5b6c/sensors-24-05909-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/778619bd985c/sensors-24-05909-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/569f574fcc56/sensors-24-05909-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/d3c097b9fd4c/sensors-24-05909-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/552c26b5f48f/sensors-24-05909-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/fce07a0fa618/sensors-24-05909-g016a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/6fa90640ed74/sensors-24-05909-g017a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/4e14ca7c31b4/sensors-24-05909-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/616d00092ff4/sensors-24-05909-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/23b81ae99c3c/sensors-24-05909-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/4f9ea81c8b2c/sensors-24-05909-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/ab79f261f64a/sensors-24-05909-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/faa4ec4e6561/sensors-24-05909-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/b13dc4a314a9/sensors-24-05909-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/e4da304149bb/sensors-24-05909-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/f791206afe09/sensors-24-05909-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/ab03939ea4b3/sensors-24-05909-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/6c6c4c5f5b6c/sensors-24-05909-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/778619bd985c/sensors-24-05909-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/569f574fcc56/sensors-24-05909-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/d3c097b9fd4c/sensors-24-05909-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/552c26b5f48f/sensors-24-05909-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/fce07a0fa618/sensors-24-05909-g016a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b58b/11435958/6fa90640ed74/sensors-24-05909-g017a.jpg

相似文献

1
Study of Global Navigation Satellite System Receivers' Accuracy for Unmanned Vehicles.全球导航卫星系统接收机在无人驾驶车辆中的精度研究。
Sensors (Basel). 2024 Sep 12;24(18):5909. doi: 10.3390/s24185909.
2
Benefits of Multi-Constellation/Multi-Frequency GNSS in a Tightly Coupled GNSS/IMU/Odometry Integration Algorithm.多星座/多频率 GNSS 在紧耦合 GNSS/IMU/里程计组合算法中的优势。
Sensors (Basel). 2018 Sep 12;18(9):3052. doi: 10.3390/s18093052.
3
Research on Low-Cost Attitude Estimation for MINS/Dual-Antenna GNSS Integrated Navigation Method.基于MINS/双天线GNSS组合导航方法的低成本姿态估计研究
Micromachines (Basel). 2019 May 30;10(6):362. doi: 10.3390/mi10060362.
4
Precise and Robust RTK-GNSS Positioning in Urban Environments with Dual-Antenna Configuration.采用双天线配置在城市环境中实现精确且稳健的RTK-GNSS定位
Sensors (Basel). 2019 Aug 17;19(16):3586. doi: 10.3390/s19163586.
5
Global Navigation Satellite System Real-Time Kinematic Positioning Framework for Precise Operation of a Swarm of Moving Vehicles.用于一群移动车辆精确运行的全球导航卫星系统实时动态定位框架
Sensors (Basel). 2022 Oct 18;22(20):7939. doi: 10.3390/s22207939.
6
Differential GNSS and Vision-Based Tracking to Improve Navigation Performance in Cooperative Multi-UAV Systems.差分全球导航卫星系统与基于视觉的跟踪技术,以提升协同多无人机系统中的导航性能
Sensors (Basel). 2016 Dec 17;16(12):2164. doi: 10.3390/s16122164.
7
Five-State Extended Kalman Filter for Estimation of Speed over Ground (SOG), Course over Ground (COG) and Course Rate of Unmanned Surface Vehicles (USVs): Experimental Results.用于估计无人水面舰艇(USV)对地航速(SOG)、对地航向(COG)和航向变化率的五状态扩展卡尔曼滤波器:实验结果
Sensors (Basel). 2021 Nov 27;21(23):7910. doi: 10.3390/s21237910.
8
Evaluation of L6 augmentation signal reception characteristics and positioning accuracy of compact and lightweight GNSS antennas.紧凑型轻量化全球导航卫星系统(GNSS)天线的L6增强信号接收特性及定位精度评估
Sci Rep. 2023 Dec 8;13(1):21766. doi: 10.1038/s41598-023-48954-0.
9
Model-Based Autonomous Navigation with Moment of Inertia Estimation for Unmanned Aerial Vehicles.基于模型的无人机惯量估计自主导航
Sensors (Basel). 2019 May 29;19(11):2467. doi: 10.3390/s19112467.
10
NaviSoC: High-Accuracy Low-Power GNSS SoC with an Integrated Application Processor.导航片上系统:集成应用处理器的高精度低功耗全球导航卫星系统片上系统
Sensors (Basel). 2020 Feb 16;20(4):1069. doi: 10.3390/s20041069.

本文引用的文献

1
Garmin GPSMAP 66sr: Assessment of Its GNSS Observations and Centimeter-Accurate Positioning.
Sensors (Basel). 2022 Mar 2;22(5):1964. doi: 10.3390/s22051964.
2
Feasibility of Using Low-Cost Dual-Frequency GNSS Receivers for Land Surveying.使用低成本双频全球导航卫星系统(GNSS)接收机进行土地测量的可行性
Sensors (Basel). 2021 Mar 11;21(6):1956. doi: 10.3390/s21061956.
3
RTK/Pseudolite/LAHDE/IMU-PDR Integrated Pedestrian Navigation System for Urban and Indoor Environments.RTK/Pseudolite/LAHDE/IMU-PDR 集成行人导航系统,适用于城市和室内环境。
Sensors (Basel). 2020 Mar 24;20(6):1791. doi: 10.3390/s20061791.
4
Analysis of Quasi-Zenith Satellite System Signal Acquisition and Multiplexing Characteristics in China Area.中国区域准天顶卫星系统信号捕获与复用特性分析
Sensors (Basel). 2020 Mar 11;20(6):1547. doi: 10.3390/s20061547.
5
Precise Point Positioning Using Dual-Frequency GNSS Observations on Smartphone.基于智能手机双频全球导航卫星系统观测的精确点位定位
Sensors (Basel). 2019 May 11;19(9):2189. doi: 10.3390/s19092189.
6
Tightly-Coupled Integration of Multi-GNSS Single-Frequency RTK and MEMS-IMU for Enhanced Positioning Performance.多全球导航卫星系统单频实时动态定位与微机电惯性测量单元的紧密耦合集成以提升定位性能
Sensors (Basel). 2017 Oct 27;17(11):2462. doi: 10.3390/s17112462.
7
Loose and Tight GNSS/INS Integrations: Comparison of Performance Assessed in Real Urban Scenarios.松散和紧密的全球导航卫星系统/惯性导航系统集成:在真实城市场景中评估的性能比较
Sensors (Basel). 2017 Jan 29;17(2):255. doi: 10.3390/s17020255.
8
How a GNSS Receiver Is Held May Affect Static Horizontal Position Accuracy.全球导航卫星系统(GNSS)接收机的握持方式可能会影响静态水平定位精度。
PLoS One. 2015 Apr 29;10(4):e0124696. doi: 10.1371/journal.pone.0124696. eCollection 2015.