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:
Nov. 12, 2024

Filed:

Jul. 14, 2021
Applicant:

Intel Corporation, Santa Clara, CA (US);

Inventors:

Chulong Chen, San Jose, CA (US);

Wenling Margaret Huang, Los Altos, CA (US);

Saiveena Kesaraju, Mountain View, CA (US);

Ivan Simões Gaspar, West Linn, OR (US);

Pradyumna S. Singh, San Jose, CA (US);

Biji George, Bangalore, IN;

Dipan Kumar Mandal, Bangalore, IN;

Om Ji Omer, Bangalore, IN;

Sreenivas Subramoney, Bangalore, IN;

Yuval Amizur, Kfar-Saba, IL;

Leor Banin, Petach Tikva, IL;

Hao Chen, Owing Mills, MD (US);

Nir Dvorecki, Herzeliya, IL;

Shengbo Xu, Newark, CA (US);

Assignee:

Intel Corporation, Santa Clara, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G01S 7/41 (2006.01); G01S 7/40 (2006.01); G01S 13/58 (2006.01); G01S 13/89 (2006.01); H01Q 15/02 (2006.01); H01Q 21/06 (2006.01);
U.S. Cl.
CPC ...
G01S 7/417 (2013.01); G01S 7/40 (2013.01); G01S 13/584 (2013.01); G01S 13/89 (2013.01); H01Q 21/06 (2013.01); H01Q 15/02 (2013.01);
Abstract

According to various embodiments, a radar device is described comprising a processor configured to generate a scene comprising an object based on a plurality of receive wireless signals, generate a ground truth object parameter of the object and generate a dataset representative of the scene and a radar detector configured to determine an object parameter of the object using a machine learning algorithm and the dataset, determine an error value of the machine learning algorithm using a cost function, the object parameter, and the ground truth object parameter and adjust the machine learning algorithm values to reduce the error value.


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