Google llc (20240345212). Detecting a Frame-of-Reference Change in a Smart-Device-Based Radar System simplified abstract
Contents
Detecting a Frame-of-Reference Change in a Smart-Device-Based Radar System
Organization Name
Inventor(s)
Nicholas Edward Gillian of Palo Alto CA (US)
Detecting a Frame-of-Reference Change in a Smart-Device-Based Radar System - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240345212 titled 'Detecting a Frame-of-Reference Change in a Smart-Device-Based Radar System
Simplified Explanation: The patent application describes a radar system that uses machine learning to detect changes in the frame of reference, allowing it to operate as a motion sensor without relying on non-radar-based sensors.
Key Features and Innovation:
- Radar system with a frame-of-reference machine-learned module
- Analyzes complex radar data to detect relative motion of objects
- Operates as a motion sensor without non-radar-based sensors
- Can determine if a gesture is likely to occur and compensate for radar system motion
Potential Applications: This technology can be used in:
- Gesture recognition systems
- Security systems
- Autonomous vehicles
- Robotics
Problems Solved:
- Eliminates the need for additional sensors in motion detection systems
- Improves accuracy and reliability of motion sensing technology
Benefits:
- Enhanced motion detection capabilities
- Reduced reliance on external sensors
- Improved performance in various applications
Commercial Applications: Potential commercial uses include:
- Smart home devices
- Automotive industry for autonomous vehicles
- Security and surveillance systems
Prior Art: Readers can explore prior art related to this technology in the field of radar systems, machine learning, and motion sensing technologies.
Frequently Updated Research: Stay updated on advancements in radar technology, machine learning applications in sensor systems, and motion detection research.
Questions about Radar System with Frame-of-Reference Machine-Learned Module: 1. How does the radar system with a frame-of-reference machine-learned module improve motion detection capabilities? 2. What are the potential commercial applications of this technology in the automotive industry?
Original Abstract Submitted
techniques and apparatuses are described that implement a smart-device-based radar system capable of detecting a frame-of-reference change. in particular, a radar system includes a frame-of-reference machine-learned module trained to recognize whether or not the radar system's frame of reference changes. the frame-of-reference machine-learned module analyzes complex radar data generated from at least one chirp of a reflected radar signal to analyze a relative motion of at least one object over time. by analyzing the complex radar data directly using machine learning, the radar system can operate as a motion sensor without relying on non-radar-based sensors, such as gyroscopes, inertial sensors, or accelerometers. with knowledge of whether the frame-of-reference is stationary or moving, the radar system can determine whether or not a gesture is likely to occur and, in some cases, compensate for the relative motion of the radar system itself.
