基于现场数据的紧密光学积分(TOI)算法论证

T. Arthur, Z. Zhu, S. Bhattacharya, K. Johnson, K. Scheff
{"title":"基于现场数据的紧密光学积分(TOI)算法论证","authors":"T. Arthur, Z. Zhu, S. Bhattacharya, K. Johnson, K. Scheff","doi":"10.1109/PLANS.2008.4570065","DOIUrl":null,"url":null,"abstract":"Recently a biologically inspired algorithm, called tight optical integration (TOI), was developed for tightly integrating optical sensor with GPS. The algorithm involves the integration of a standard camera along with GPS range (pseudorange or carrier phase) measurements to form position estimates. Initial simulations showed that TOI is capable of providing a position solution with an insufficient number of GPS satellites and a visible ldquomarkerrdquo at a known location, with an inertial unit to provide attitude information. This paper demonstrates how a marker is selected from a picture frame and tracked among consecutive frames. TOI has the potential to navigate with one known marker and two or three GPS satellites. In this work attitude information is derived from the GPS velocity estimates assuming zero roll for a terrestrial vehicle. Additionally, the same TOI algorithm can auto-locate unknown features when the position of the marker is not available, and navigate by these features when location is lost. The TOI algorithm is unique because it relies only on GPS range measurements and the pixel data from a camera. No ranging sources such as radar or LIDAR are required. It has particular application to scenarios involving a reduced constellation; such a reduced constellation may be due either to an urban canyon or a denied signal environment.","PeriodicalId":446381,"journal":{"name":"2008 IEEE/ION Position, Location and Navigation Symposium","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Demonstration of Tight Optical Integration (TOI) algorithm using field data\",\"authors\":\"T. Arthur, Z. Zhu, S. Bhattacharya, K. Johnson, K. Scheff\",\"doi\":\"10.1109/PLANS.2008.4570065\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recently a biologically inspired algorithm, called tight optical integration (TOI), was developed for tightly integrating optical sensor with GPS. The algorithm involves the integration of a standard camera along with GPS range (pseudorange or carrier phase) measurements to form position estimates. Initial simulations showed that TOI is capable of providing a position solution with an insufficient number of GPS satellites and a visible ldquomarkerrdquo at a known location, with an inertial unit to provide attitude information. This paper demonstrates how a marker is selected from a picture frame and tracked among consecutive frames. TOI has the potential to navigate with one known marker and two or three GPS satellites. In this work attitude information is derived from the GPS velocity estimates assuming zero roll for a terrestrial vehicle. Additionally, the same TOI algorithm can auto-locate unknown features when the position of the marker is not available, and navigate by these features when location is lost. The TOI algorithm is unique because it relies only on GPS range measurements and the pixel data from a camera. No ranging sources such as radar or LIDAR are required. It has particular application to scenarios involving a reduced constellation; such a reduced constellation may be due either to an urban canyon or a denied signal environment.\",\"PeriodicalId\":446381,\"journal\":{\"name\":\"2008 IEEE/ION Position, Location and Navigation Symposium\",\"volume\":\"52 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-05-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 IEEE/ION Position, Location and Navigation Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PLANS.2008.4570065\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE/ION Position, Location and Navigation Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PLANS.2008.4570065","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

最近,一种受生物学启发的算法被称为紧密光学集成(TOI),用于将光学传感器与GPS紧密集成。该算法包括将标准相机与GPS距离(伪距或载波相位)测量相结合以形成位置估计。初始模拟表明,TOI能够在GPS卫星数量不足的情况下提供位置解决方案,并且在已知位置有一个可见的ldquarmark,并使用惯性单元提供姿态信息。本文演示了如何从图像帧中选择标记并在连续帧中跟踪标记。印度时报有潜力用一个已知的标记和两到三颗GPS卫星进行导航。在这项工作中,姿态信息来源于假定地面飞行器零滚转的GPS速度估计。此外,相同的TOI算法可以在标记位置不可用时自动定位未知特征,并在位置丢失时通过这些特征进行导航。TOI算法是独一无二的,因为它只依赖于GPS距离测量和相机的像素数据。不需要雷达或激光雷达等测距源。它特别适用于涉及减少星座的场景;这种减少的星座可能是由于城市峡谷或拒绝信号环境造成的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Demonstration of Tight Optical Integration (TOI) algorithm using field data
Recently a biologically inspired algorithm, called tight optical integration (TOI), was developed for tightly integrating optical sensor with GPS. The algorithm involves the integration of a standard camera along with GPS range (pseudorange or carrier phase) measurements to form position estimates. Initial simulations showed that TOI is capable of providing a position solution with an insufficient number of GPS satellites and a visible ldquomarkerrdquo at a known location, with an inertial unit to provide attitude information. This paper demonstrates how a marker is selected from a picture frame and tracked among consecutive frames. TOI has the potential to navigate with one known marker and two or three GPS satellites. In this work attitude information is derived from the GPS velocity estimates assuming zero roll for a terrestrial vehicle. Additionally, the same TOI algorithm can auto-locate unknown features when the position of the marker is not available, and navigate by these features when location is lost. The TOI algorithm is unique because it relies only on GPS range measurements and the pixel data from a camera. No ranging sources such as radar or LIDAR are required. It has particular application to scenarios involving a reduced constellation; such a reduced constellation may be due either to an urban canyon or a denied signal environment.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信