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:
Mar. 29, 2022

Filed:

Nov. 05, 2019
Applicant:

Intelligent Fusion Technology, Inc., Germantown, MD (US);

Inventors:

Jingyang Lu, Germantown, MD (US);

Yiran Xu, Germantown, MD (US);

Dan Shen, Germantown, MD (US);

Nichole Sullivan, Germantown, MD (US);

Genshe Chen, Germantown, MD (US);

Khanh Pham, Kirtland AFB, NM (US);

Erik Blasch, Arlington, VA (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 15/06 (2011.01); G06N 20/00 (2019.01); G06N 5/04 (2006.01);
U.S. Cl.
CPC ...
G06T 15/06 (2013.01); G06N 5/04 (2013.01); G06N 20/00 (2019.01);
Abstract

The present disclosure provides a method for wave propagation prediction based on a 3D ray tracing engine and machine-learning based dominant ray selection. The method includes receiving, integrating, and processing input data. Integrating and processing the input data includes dividing a cone of the original millimeter wave (mmWave) into a plurality of sub cones; determining a contribution weight of rays coming from each sub cone to the received signal strength (RSS) at a receiving end of interest; and determining rays coming from one or more sub cones that have a total contribution weight to the RSS larger than a preset threshold value as dominant rays using a neural network obtained through a machine learning approach. The method further includes performing ray tracing based on the input data and the dominant rays to predict wave propagation.


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