• 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

具有最佳区域预设的 LPS 自动校准算法。

LPS auto-calibration algorithm with predetermination of optimal zones.

机构信息

Electronics Department, University of Alcalá de Henares, Escuela Politécnica. Ctra. Madrid-Barcelona, Km. 33,600, 28871 Alcalá de Henares, Spain.

出版信息

Sensors (Basel). 2011;11(11):10398-414. doi: 10.3390/s111110398. Epub 2011 Oct 31.

DOI:10.3390/s111110398
PMID:22346649
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3274291/
Abstract

Accurate coordinates for active beacons placed in the environment are required in local positioning systems (LPS). These coordinates and the distances (or differences of distances) measured between the beacons and the mobile node to be localized are inputs to most trilateration algorithms. As a first approximation, such coordinates are obtained by means of manual measurements (a time-consuming and non-flexible method), or by using a calibration algorithm (i.e., automatic determination of beacon coordinates from ad hoc measurements). This paper presents a method to calibrate the beacons' positions in a LPS using a mobile receiver. The method has been developed for both, spherical and hyperbolic trilateration. The location of only three test points must be known a priori, while the position of the other test points can be unknown. Furthermore, the paper describes a procedure to estimate the optimal positions, or approximate areas in the coverage zone, where the test-points necessary to calibrate the ultrasonic LPS should be placed. Simulation and experimental results show the improvement achieved when these optimal test-points are used instead of randomly selected ones.

摘要

在本地定位系统 (LPS) 中,需要准确的环境中放置的有源信标的坐标。这些坐标以及测量到的信标与要定位的移动节点之间的距离(或距离差异)是大多数三边测量算法的输入。作为初步近似,这些坐标通过手动测量(一种耗时且不灵活的方法)获得,或者通过使用校准算法(即,从特定测量中自动确定信标坐标)获得。本文提出了一种使用移动接收器校准 LPS 中信标位置的方法。该方法已针对球形和双曲线三边测量进行了开发。仅需事先知道三个测试点的位置,而其他测试点的位置可以未知。此外,本文还描述了一种程序,可以估计最佳位置或覆盖区域的近似区域,应在这些位置放置校准超声波 LPS 所需的测试点。仿真和实验结果表明,使用这些最佳测试点而不是随机选择的测试点可以提高精度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e58b/3274291/a3a0502ae9d0/sensors-11-10398f12.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e58b/3274291/576fcc9273b6/sensors-11-10398f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e58b/3274291/2a9d14e57047/sensors-11-10398f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e58b/3274291/6dce5bd1581d/sensors-11-10398f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e58b/3274291/d733601c77b9/sensors-11-10398f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e58b/3274291/52188cd1b986/sensors-11-10398f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e58b/3274291/a47837896bc9/sensors-11-10398f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e58b/3274291/31b966dd7b4d/sensors-11-10398f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e58b/3274291/657b711bc317/sensors-11-10398f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e58b/3274291/174c16063980/sensors-11-10398f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e58b/3274291/6678b5376d01/sensors-11-10398f10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e58b/3274291/0d62b9a15bd4/sensors-11-10398f11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e58b/3274291/a3a0502ae9d0/sensors-11-10398f12.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e58b/3274291/576fcc9273b6/sensors-11-10398f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e58b/3274291/2a9d14e57047/sensors-11-10398f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e58b/3274291/6dce5bd1581d/sensors-11-10398f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e58b/3274291/d733601c77b9/sensors-11-10398f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e58b/3274291/52188cd1b986/sensors-11-10398f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e58b/3274291/a47837896bc9/sensors-11-10398f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e58b/3274291/31b966dd7b4d/sensors-11-10398f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e58b/3274291/657b711bc317/sensors-11-10398f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e58b/3274291/174c16063980/sensors-11-10398f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e58b/3274291/6678b5376d01/sensors-11-10398f10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e58b/3274291/0d62b9a15bd4/sensors-11-10398f11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e58b/3274291/a3a0502ae9d0/sensors-11-10398f12.jpg

相似文献

1
LPS auto-calibration algorithm with predetermination of optimal zones.具有最佳区域预设的 LPS 自动校准算法。
Sensors (Basel). 2011;11(11):10398-414. doi: 10.3390/s111110398. Epub 2011 Oct 31.
2
Error estimation for the linearized auto-localization algorithm.线性自定位算法的误差估计。
Sensors (Basel). 2012;12(3):2561-81. doi: 10.3390/s120302561. Epub 2012 Feb 24.
3
Calibration of Beacons for Indoor Environments based on a Digital Map and Heuristic Information.基于数字地图和启发式信息的室内环境信标校准。
Sensors (Basel). 2019 Feb 6;19(3):670. doi: 10.3390/s19030670.
4
Characterization of an Ultrasonic Local Positioning System for 3D Measurements.用于三维测量的超声局部定位系统的特性描述。
Sensors (Basel). 2020 May 14;20(10):2794. doi: 10.3390/s20102794.
5
An Improved Trilateration Positioning Algorithm with Anchor Node Combination and K-Means Clustering.一种改进的基于锚节点组合和K均值聚类的三边定位算法。
Sensors (Basel). 2022 Aug 15;22(16):6085. doi: 10.3390/s22166085.
6
A Novel Hybrid NN-ABPE-Based Calibration Method for Improving Accuracy of Lateration Positioning System.一种基于新型混合 NN-ABPE 的校准方法,用于提高测距定位系统的精度。
Sensors (Basel). 2021 Dec 8;21(24):8204. doi: 10.3390/s21248204.
7
Easily-Deployable Acoustic Local Positioning System Based on Auto-Calibrated Wireless Beacons.基于自校准无线信标的易部署声定位系统。
Sensors (Basel). 2019 Mar 20;19(6):1385. doi: 10.3390/s19061385.
8
Measuring time-of-flight in an ultrasonic LPS system using generalized cross-correlation.利用广义互相关测量超声 LPS 系统中的飞行时间。
Sensors (Basel). 2011;11(11):10326-42. doi: 10.3390/s111110326. Epub 2011 Oct 31.
9
Calibration of Visible Light Positioning Systems with a Mobile Robot.基于移动机器人的可见光定位系统校准
Sensors (Basel). 2021 Mar 30;21(7):2394. doi: 10.3390/s21072394.
10
Locally-referenced ultrasonic--LPS for localization and navigation.局部参考超声——用于定位和导航的LPS
Sensors (Basel). 2014 Nov 18;14(11):21750-69. doi: 10.3390/s141121750.

引用本文的文献

1
Calibration of Beacons for Indoor Environments based on a Digital Map and Heuristic Information.基于数字地图和启发式信息的室内环境信标校准。
Sensors (Basel). 2019 Feb 6;19(3):670. doi: 10.3390/s19030670.
2
Sensorial systems applied to Intelligent Spaces.应用于智能空间的传感系统。
Sensors (Basel). 2012;12(8):10707-12. doi: 10.3390/s120810707. Epub 2012 Aug 6.