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

Overview of attention for article published in Sensors, October 2016
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Title
A Novel 3D Multilateration Sensor Using Distributed Ultrasonic Beacons for Indoor Navigation
Published in
Sensors, October 2016
DOI 10.3390/s16101637
Pubmed ID
Authors

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

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.

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The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 35 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 17%
Student > Master 5 14%
Student > Bachelor 4 11%
Student > Postgraduate 3 9%
Researcher 3 9%
Other 4 11%
Unknown 10 29%
Readers by discipline Count As %
Engineering 14 40%
Computer Science 5 14%
Agricultural and Biological Sciences 1 3%
Economics, Econometrics and Finance 1 3%
Business, Management and Accounting 1 3%
Other 0 0%
Unknown 13 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 October 2016.
All research outputs
#22,759,452
of 25,374,647 outputs
Outputs from Sensors
#16,641
of 24,303 outputs
Outputs of similar age
#287,702
of 328,119 outputs
Outputs of similar age from Sensors
#156
of 251 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 24,303 research outputs from this source. They receive a mean Attention Score of 3.1. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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