Sensing-assisted user equipment to object association
US-2024214979-A1 · Jun 27, 2024 · US
Methods and Systems for Processing Radar Sensor Data
US2023120299A1 · US · A1
| Field | Value |
|---|---|
| Publication number | US-2023120299-A1 |
| Application number | US-202218047105-A |
| Country | US |
| Kind code | A1 |
| Filing date | Oct 17, 2022 |
| Priority date | Oct 20, 2021 |
| Publication date | Apr 20, 2023 |
| Grant date | — |
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Abstract
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This disclosure describes systems and techniques for processing radar sensor data. The systems and techniques include acquiring radar sensor data from a radar sensor and processing the radar sensor data by, for example, an artificial neural network to obtain at least one of range radar data or Doppler radar data.
First claim
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What is claimed is: 1 . A computer-implemented method for processing radar sensor data, the computer-implemented method comprising: acquiring radar sensor data from a radar sensor; and processing the radar sensor data by an artificial neural network to obtain at least one of range radar data or Doppler radar data. 2 . The computer-implemented method of claim 1 , wherein the artificial neural network resembles at least one Fourier transform. 3 . The computer-implemented method of claim 2 , wherein the at least one Fourier transform comprises a fast time Fourier transform. 4 . The computer-implemented method of claim 2 , wherein the at least one Fourier transform comprises a slow time Fourier transform. 5 . The computer-implemented method of claim 1 , wherein the artificial neural network is configured to resemble Fourier transform sample data. 6 . The computer-implemented method of claim 1 , wherein the artificial neural network is trained using random initialization and pretraining. 7 . The computer-implemented method of claim 1 , wherein the artificial neural network comprises a deep neural network. 8 . The computer-implemented method of claim 1 , further comprising: evaluating an angle-finding artificial neural network for angle finding. 9 . The computer-implemented method of claim 1 , further comprising: evaluating an object detection artificial neural network for object detection. 10 . The computer-implemented method of claim 1 , further comprising: evaluating an object tracking artificial neural network for object tracking. 11 . The computer-implemented method of claim 1 , wherein the artificial neural network is trained end-to-end. 12 . The computer-implemented method of claim 1 , wherein the radar sensor data comprises analog radar sensor data. 13 . A system comprising one or more processors and memory coupled to the one or more processors, the memory storing one or more programs configured to be executed by the one or more processors, the one or more programs including instructions for: acquiring radar sensor data from a radar sensor; and processing the radar sensor data by an artificial neural network to obtain at least one of range radar data or Doppler radar data. 14 . The system of claim 13 , wherein the artificial neural network resembles at least one Fourier transform. 15 . The system of claim 14 , wherein the at least one Fourier transform comprises a fast time Fourier transform. 16 . The system of claim 14 , wherein the at least one Fourier transform comprises a slow time Fourier transform. 17 . The system of claim 13 , wherein the artificial neural network is configured to resemble Fourier transform sample data. 18 . The system of claim 13 , wherein the artificial neural network is trained using random initialization and pretraining. 19 . The system of claim 13 , wherein the artificial neural network comprises a deep neural network. 20 . The system of claim 13 , further comprising at least one of: evaluating an angle-finding artificial neural network for angle finding; evaluating an object detection artificial neural network for object detection; or evaluating an object tracking artificial neural network for object tracking.
Assignees
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Classifications
using Doppler effect for determining closest range to a target or corresponding time, e.g. miss-distance indicator · CPC title
involving particularities of FFT processing · CPC title
of land vehicles · CPC title
using sawtooth modulation · CPC title
- G01S7/417Primary
involving the use of neural networks · CPC title
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Frequently asked questions
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- What does patent US2023120299A1 cover?
- This disclosure describes systems and techniques for processing radar sensor data. The systems and techniques include acquiring radar sensor data from a radar sensor and processing the radar sensor data by, for example, an artificial neural network to obtain at least one of range radar data or Doppler radar data.
- Who is the assignee on this patent?
- Aptiv Tech Ltd
- What technology area does this patent fall under?
- Primary CPC classification G01S7/417. Mapped technology areas include Physics.
- When was this patent published?
- Publication date Thu Apr 20 2023 00:00:00 GMT+0000 (Coordinated Universal Time) (A1). Legal status and post-grant events are not shown on this page.
- What related patents are in patentsdb?
- We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).