Google llc (20240241222). Cooperative Bistatic Radar Sensing Using Deep Neural Networks simplified abstract
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 20240241222 titled 'Cooperative Bistatic Radar Sensing Using Deep Neural Networks
The abstract describes techniques and apparatuses for cooperative bistatic radar sensing using deep neural networks. A base station acts as a transmitter, while user equipment acts as a receiver during radar sensing. Both the base station and user equipment utilize deep neural networks for signal generation and processing, enabling the use of the same hardware for radar sensing and wireless communication. This cooperative approach allows for the compilation of explicit information about objects in the environment to enhance wireless communication performance.
- Base station and user equipment operate as transmitter and receiver in cooperative bistatic radar sensing.
- Deep neural networks are used for signal generation and processing.
- Same hardware is utilized for both radar sensing and wireless communication.
- Explicit information about objects in the environment is compiled to improve wireless communication performance.
Potential Applications: - Enhanced wireless communication performance - Object detection and tracking in various environments - Improved radar sensing capabilities for security and surveillance purposes
Problems Solved: - Utilizing the same hardware for radar sensing and wireless communication - Enhancing communication performance through cooperative radar sensing
Benefits: - Increased efficiency in utilizing hardware for multiple purposes - Enhanced object detection and tracking capabilities - Improved wireless communication performance in challenging environments
Commercial Applications: Title: "Enhanced Wireless Communication Performance through Cooperative Bistatic Radar Sensing" This technology can be applied in industries such as: - Telecommunications - Defense and security - Surveillance systems
Questions about Cooperative Bistatic Radar Sensing: 1. How does the use of deep neural networks improve radar sensing capabilities?
Deep neural networks enhance signal generation and processing, leading to more accurate and efficient radar sensing.
2. What are the advantages of utilizing the same hardware for both radar sensing and wireless communication?
Using the same hardware reduces costs and simplifies system integration, making it more efficient for users.
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.
