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. 23, 2024

Filed:

Aug. 17, 2023
Applicants:

Zhejiang University, Zhejiang, CN;

Donghai Laboratory, Zhejiang, CN;

Inventors:

Chunyi Song, Zhoushan, CN;

Zhihui Cao, Zhoushan, CN;

Zhiwei Xu, Zhoushan, CN;

Yuying Song, Zhoushan, CN;

Fuyuan Ai, Zhoushan, CN;

Jingxuan Wu, Zhoushan, CN;

Assignees:

ZHEJIANG UNIVERSITY, Zhoushan, CN;

DONGHAI LABORATORY, Zhoushan, CN;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G01S 7/41 (2006.01); G01S 13/53 (2006.01); G01S 13/536 (2006.01); G01S 13/72 (2006.01); G06N 3/084 (2023.01);
U.S. Cl.
CPC ...
G01S 7/417 (2013.01); G01S 13/536 (2013.01); G01S 13/726 (2013.01); G06N 3/084 (2013.01);
Abstract

The embodiment of the present disclosure provides a deep neural network (DNN)-based multi-target constant false alarm rate (CFAR) detection method. The method includes: obtaining target values to be measured based on radar IF (IF) signals to be detected, the target values to be measured including a measured frequency value and a measured intensity value of the radar IF signals; obtaining peak sequences based on the target values to be measured; generating a target detection result by processing the peak sequences based on a DNN detector, the DNN detector being a machine learning model; generating approximated maximum likelihood estimation (AMLE) of a scale parameter based on an approximated maximum likelihood estimator; generating a false alarm adjustment threshold based on a preset false alarm rate and the AMLE; and generating a constant false alarm detection result by processing the target detection result based on the false alarm adjustment threshold.


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