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一种使用分布式超声波信标的新型三维多边测量传感器用于室内导航。

A Novel 3D Multilateration Sensor Using Distributed Ultrasonic Beacons for Indoor Navigation.

作者信息

Kapoor Rohan, Ramasamy Subramanian, Gardi Alessandro, Bieber Chad, Silverberg Larry, Sabatini Roberto

机构信息

School of Engineering, RMIT University, Aerospace and Aviation Discipline Melbourne, Melbourne VIC 3000, Australia.

Mechanical and Aerospace Engineering, NC State University, Raleigh, NC 27695, USA.

出版信息

Sensors (Basel). 2016 Oct 8;16(10):1637. doi: 10.3390/s16101637.

DOI:10.3390/s16101637
PMID:27740604
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5087425/
Abstract

Navigation and guidance systems are a critical part of any autonomous vehicle. In this paper, a novel sensor grid using 40 KHz ultrasonic transmitters is presented for adoption in indoor 3D positioning applications. In the proposed technique, a vehicle measures the arrival time of incoming ultrasonic signals and calculates the position without broadcasting to the grid. This system allows for conducting silent or covert operations and can also be used for the simultaneous navigation of a large number of vehicles. The transmitters and receivers employed are first described. Transmission lobe patterns and receiver directionality determine the geometry of transmitter clusters. Range and accuracy of measurements dictate the number of sensors required to navigate in a given volume. Laboratory experiments were performed in which a small array of transmitters was set up and the sensor system was tested for position accuracy. The prototype system is shown to have a 1-sigma position error of about 16 cm, with errors between 7 and 11 cm in the local horizontal coordinates. This research work provides foundations for the future development of ultrasonic navigation sensors for a variety of autonomous vehicle applications.

摘要

导航和制导系统是任何自动驾驶车辆的关键组成部分。本文提出了一种采用40kHz超声波发射器的新型传感器网格,用于室内三维定位应用。在所提出的技术中,车辆测量传入超声波信号的到达时间并计算位置,而无需向网格广播。该系统允许进行无声或隐蔽操作,还可用于大量车辆的同时导航。首先描述了所采用的发射器和接收器。发射波瓣模式和接收器方向性决定了发射器集群的几何形状。测量的范围和精度决定了在给定空间中导航所需的传感器数量。进行了实验室实验,其中设置了一小排发射器,并对传感器系统的位置精度进行了测试。原型系统的1σ位置误差约为16厘米,局部水平坐标的误差在7至11厘米之间。这项研究工作为各种自动驾驶车辆应用的超声波导航传感器的未来发展奠定了基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b704/5087425/36a0955870e9/sensors-16-01637-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b704/5087425/f3a0ab90136e/sensors-16-01637-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b704/5087425/c02164e44219/sensors-16-01637-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b704/5087425/1d50d1828e28/sensors-16-01637-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b704/5087425/737100ac12cd/sensors-16-01637-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b704/5087425/6d20999db330/sensors-16-01637-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b704/5087425/485ec97a0052/sensors-16-01637-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b704/5087425/726038a8d0ea/sensors-16-01637-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b704/5087425/ef6fd812ea9f/sensors-16-01637-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b704/5087425/07661b26213d/sensors-16-01637-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b704/5087425/7fed46b66f70/sensors-16-01637-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b704/5087425/d82dcd603659/sensors-16-01637-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b704/5087425/75a1eead2be9/sensors-16-01637-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b704/5087425/8e515bd5cba4/sensors-16-01637-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b704/5087425/36a0955870e9/sensors-16-01637-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b704/5087425/f3a0ab90136e/sensors-16-01637-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b704/5087425/c02164e44219/sensors-16-01637-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b704/5087425/1d50d1828e28/sensors-16-01637-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b704/5087425/737100ac12cd/sensors-16-01637-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b704/5087425/6d20999db330/sensors-16-01637-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b704/5087425/485ec97a0052/sensors-16-01637-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b704/5087425/726038a8d0ea/sensors-16-01637-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b704/5087425/ef6fd812ea9f/sensors-16-01637-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b704/5087425/07661b26213d/sensors-16-01637-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b704/5087425/7fed46b66f70/sensors-16-01637-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b704/5087425/d82dcd603659/sensors-16-01637-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b704/5087425/75a1eead2be9/sensors-16-01637-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b704/5087425/8e515bd5cba4/sensors-16-01637-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b704/5087425/36a0955870e9/sensors-16-01637-g014.jpg

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本文引用的文献

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The Indoor Localization and Tracking Estimation Method of Mobile Targets in Three-Dimensional Wireless Sensor Networks.三维无线传感器网络中移动目标的室内定位与跟踪估计方法
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Network Optimisation and Performance Analysis of a Multistatic Acoustic Navigation Sensor.多基地声学导航传感器的网络优化与性能分析
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Sensors (Basel). 2020 May 14;20(10):2794. doi: 10.3390/s20102794.
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