17947298. HIGH RESOLUTION RADAR SIMULATION TO TRAIN VEHICLE RADAR SYSTEM NEURAL NETWORK simplified abstract (GM GLOBAL TECHNOLOGY OPERATIONS LLC)
Contents
- 1 HIGH RESOLUTION RADAR SIMULATION TO TRAIN VEHICLE RADAR SYSTEM NEURAL NETWORK
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 HIGH RESOLUTION RADAR SIMULATION TO TRAIN VEHICLE RADAR SYSTEM NEURAL NETWORK - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Unanswered Questions
- 1.11 Original Abstract Submitted
HIGH RESOLUTION RADAR SIMULATION TO TRAIN VEHICLE RADAR SYSTEM NEURAL NETWORK
Organization Name
GM GLOBAL TECHNOLOGY OPERATIONS LLC
Inventor(s)
Oded Bialer of Petach Tikva (IL)
HIGH RESOLUTION RADAR SIMULATION TO TRAIN VEHICLE RADAR SYSTEM NEURAL NETWORK - A simplified explanation of the abstract
This abstract first appeared for US patent application 17947298 titled 'HIGH RESOLUTION RADAR SIMULATION TO TRAIN VEHICLE RADAR SYSTEM NEURAL NETWORK
Simplified Explanation
The abstract describes a system that uses a radar system in a vehicle to detect objects by transmitting and receiving signals, and then enhancing the detection using a trained neural network.
- The system includes a transmitter and receiver for radar signals in a vehicle.
- A processor trains a neural network with reference data from a simulated higher resolution radar system.
- The trained neural network improves object detection in the vehicle.
- Vehicle operations are controlled based on the detection of objects.
Potential Applications
This technology can be applied in autonomous vehicles, collision avoidance systems, and advanced driver assistance systems.
Problems Solved
This technology helps improve object detection and recognition in vehicles, enhancing safety and efficiency in driving.
Benefits
The system enhances the accuracy of object detection in vehicles, leading to improved safety on the road.
Potential Commercial Applications
Commercial applications include integration into autonomous vehicles, automotive safety systems, and transportation infrastructure.
Possible Prior Art
One possible prior art could be radar systems used in vehicles for object detection and collision avoidance.
Unanswered Questions
How does the system handle different weather conditions that may affect radar signals?
The article does not mention how the system adapts to weather conditions that could impact radar signal transmission and reception.
What is the processing time for the neural network to enhance object detection in real-time driving scenarios?
The article does not provide information on the processing time required for the neural network to enhance object detection while the vehicle is in motion.
Original Abstract Submitted
A system includes a transmitter of a radar system to transmit transmitted signals, and a receiver of the radar system to receive received signals based on reflection of one or more of the transmitted signals by one or more objects. The system also includes a processor to train a neural network with reference data obtained by simulating a higher resolution radar system than the radar system to obtain a trained neural network. The trained neural network enhances detection of the one or more objects based on obtaining and processing the received signals in a vehicle. One or more operations of the vehicle are controlled based on the detection of the one or more objects.
