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:
May. 20, 2025

Filed:

Apr. 14, 2021
Applicant:

Aptiv Technologies Ag, Schaffhausen, CH;

Inventors:

Kanishka Tyagi, Agoura Hills, CA (US);

Yihang Zhang, Calabasas, CA (US);

John Kirkwood, Playa del Rey, CA (US);

Shan Zhang, Thousand Oaks, CA (US);

Sanling Song, Northport, AL (US);

Narbik Manukian, Los Angeles, CA (US);

Assignee:

Aptiv Technologies AG, Schaffhausen, CH;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06N 3/06 (2006.01); G01S 13/931 (2020.01); G06N 3/063 (2023.01); G06N 3/08 (2023.01); G06N 20/00 (2019.01);
U.S. Cl.
CPC ...
G06N 3/063 (2013.01); G01S 13/931 (2013.01); G06N 3/08 (2013.01); G06N 20/00 (2019.01); G01S 2013/93271 (2020.01);
Abstract

This document describes techniques and systems related to a radar system using a machine-learned model for stationary object detection. The radar system includes a processor that can receive radar data as time-series frames associated with electromagnetic (EM) energy. The processor uses the radar data to generate a range-time map of the EM energy that is input to a machine-learned model. The machine-learned model can receive as inputs extracted features corresponding to the stationary objects from the range-time map for multiple range bins at each of the time-series frames. In this way, the described radar system and techniques can accurately detect stationary objects of various sizes and extract critical features corresponding to the stationary objects.


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