18557849. Cooperative Bistatic Radar Sensing Using Deep Neural Networks simplified abstract (GOOGLE LLC)
Contents
Cooperative Bistatic Radar Sensing Using Deep Neural Networks
Organization Name
Inventor(s)
Jibing Wang of San Jose CA (US)
Erik Richard Stauffer of Sunnyvale CA (US)
Cooperative Bistatic Radar Sensing Using Deep Neural Networks - A simplified explanation of the abstract
This abstract first appeared for US patent application 18557849 titled 'Cooperative Bistatic Radar Sensing Using Deep Neural Networks
Simplified Explanation: The patent application describes techniques and apparatuses for cooperative bistatic radar sensing using deep neural networks. A base station acts as a transmitter, while user equipment functions as a receiver. Both utilize deep neural networks for signal generation and processing, enabling the use of the same hardware for radar sensing and wireless communication.
- Base station and user equipment operate as transmitter and receiver in bistatic radar sensing.
- Deep neural networks are used for signal generation and processing.
- Same hardware is utilized for both radar sensing and wireless communication.
Key Features and Innovation: - Implementation of cooperative bistatic radar sensing using deep neural networks. - Base station and user equipment utilize deep neural networks for signal generation and processing. - Ability to compile explicit information about objects in the operating environment to enhance wireless communication performance.
Potential Applications: - Military surveillance and reconnaissance. - Autonomous vehicles for enhanced object detection. - Industrial applications for monitoring and tracking moving objects.
Problems Solved: - Improved radar sensing capabilities. - Enhanced wireless communication performance. - Utilization of the same hardware for multiple functions.
Benefits: - Increased efficiency in radar sensing. - Enhanced object detection and tracking. - Improved wireless communication performance.
Commercial Applications: Title: Cooperative Bistatic Radar Sensing with Deep Neural Networks Potential commercial uses include: - Security and surveillance systems. - Autonomous vehicle technology. - Industrial automation for object tracking.
Prior Art: Readers can explore prior research on cooperative radar sensing, deep neural networks, and applications in wireless communication to gain a deeper understanding of the technology.
Frequently Updated Research: Stay informed about advancements in deep neural networks for radar sensing and wireless communication to ensure the latest technology is being utilized.
Questions about Cooperative Bistatic Radar Sensing with Deep Neural Networks: 1. How does the use of deep neural networks improve radar sensing in this technology? 2. What are the potential limitations of utilizing the same hardware for both radar sensing and wireless communication?
Original Abstract Submitted
Techniques and apparatuses are described that implement cooperative bistatic radar sensing using deep neural networks. In particular, a base station () operates as a transmitter of the bistatic radar, and the user equipment () operates as a receiver of the bistatic radar. During radar sensing, the base station () and the user equipment () use their respective deep neural networks ( and ) for signal generation and signal processing. The deep neural networks ( and ) also enable the base station () and the user equipment () to utilize the same hardware for both radar sensing and wireless communication. With cooperative bistatic radar sensing, the base station () and the user equipment () can compile explicit information about objects within an operating environment and use this information to improve wireless communication performance.
