The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jul. 07, 2020

Filed:

Oct. 03, 2018
Applicant:

Bastille Networks, Inc., Atlanta, GA (US);

Inventors:

Robert Baxley, Atlanta, GA (US);

Sandor Szilvasi, Atlanta, GA (US);

Luke Harwood, Decatur, GA (US);

Roy S. Thompson, III, Marietta, GA (US);

Sebastian Balint Seeber, San Francisco, CA (US);

Christian Sepulveda, San Mateo, CA (US);

Assignee:

Bastille Networks, Inc., Atlanta, GA (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G01S 5/00 (2006.01); H04W 64/00 (2009.01); G01S 5/02 (2010.01); H04B 17/391 (2015.01); G01S 5/08 (2006.01); G01S 11/06 (2006.01); H04B 17/318 (2015.01); G06N 20/00 (2019.01);
U.S. Cl.
CPC ...
G01S 5/0054 (2013.01); G01S 5/0263 (2013.01); G01S 5/08 (2013.01); G01S 11/06 (2013.01); G06N 20/00 (2019.01); H04B 17/318 (2015.01); H04B 17/391 (2015.01); H04W 64/003 (2013.01);
Abstract

Systems and methods can support improved position locating of wireless devices. A suite of machine learning models may be established. Radio frequency sensors may be positioned within an electromagnetic environment where user equipment devices are serviced by a base station. The radio frequency sensors can receive wireless signals associated with communications between the user equipment devices and the base station. The suite of machine learning models may be trained using wireless signals received from user equipment devices in known positions. The trained suite of machine learning models can be applied to wireless signals received from user equipment devices in unknown positions. The trained suite of machine learning models may be used to estimate the unknown positions. The estimated positions may be refined using additional information from the user equipment devices.


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