18113950. METHOD AND APPARATUS FOR GNSS NAVIGATION simplified abstract (SAMSUNG ELECTRONICS CO., LTD.)
Contents
- 1 METHOD AND APPARATUS FOR GNSS NAVIGATION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 METHOD AND APPARATUS FOR GNSS NAVIGATION - 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 How does this technology handle complex movements involving multiple objects connected to the body?
- 1.11 What is the accuracy of the velocity estimation generated by this system compared to traditional motion tracking methods?
- 1.12 Original Abstract Submitted
METHOD AND APPARATUS FOR GNSS NAVIGATION
Organization Name
Inventor(s)
William Bradley Stewart of Monte Sereno CA (US)
METHOD AND APPARATUS FOR GNSS NAVIGATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 18113950 titled 'METHOD AND APPARATUS FOR GNSS NAVIGATION
Simplified Explanation
The abstract of the patent application describes a system and method for tracking the position of a body by receiving combined movement data, transforming the data using different techniques, determining a velocity estimation bias, and generating a velocity estimation of the body.
- The system and method track the position of a body by receiving combined movement data, including first movement data of the body and second movement data of an object connected to the body.
- The first movement data is transformed using a first transformation technique, while the second movement data is transformed using a different second transformation technique.
- A velocity estimation bias of the body is determined based on a combination of the transformed first and second movement data.
- Finally, a velocity estimation of the body is generated with the determined velocity estimation bias.
Potential Applications
This technology can be applied in various fields such as sports performance analysis, physical therapy monitoring, and virtual reality gaming.
Problems Solved
This technology solves the problem of accurately tracking the position and movement of a body in real-time, especially when there are multiple objects connected to the body that are moving simultaneously.
Benefits
The benefits of this technology include improved accuracy in tracking body movement, enhanced data analysis for performance optimization, and potential for creating immersive virtual reality experiences.
Potential Commercial Applications
Potential commercial applications of this technology include sports training equipment, healthcare monitoring devices, and entertainment systems for virtual reality gaming.
Possible Prior Art
One possible prior art for this technology could be motion capture systems used in the entertainment industry for creating realistic animations in movies and video games.
Unanswered Questions
How does this technology handle complex movements involving multiple objects connected to the body?
The system's ability to differentiate and track movements of multiple objects connected to the body simultaneously is not explicitly mentioned in the abstract. Further details on this aspect would be beneficial for understanding the system's capabilities in real-world scenarios.
What is the accuracy of the velocity estimation generated by this system compared to traditional motion tracking methods?
The abstract mentions generating a velocity estimation of the body, but it does not provide information on the accuracy or precision of this estimation. Understanding the system's performance metrics in terms of velocity estimation accuracy would be crucial for evaluating its effectiveness in practical applications.
Original Abstract Submitted
A system and a method are disclosed for tracking a position of a body. The system and method including the steps of receiving combined movement data, the combined movement data including first movement data of the body and second movement data of an object connected to the body, wherein the second movement data is data of a movement occurring relative to the body; transforming the first movement data using a first transformation technique; transforming the second movement data using a second transformation technique that is different than the first transformation technique; determining a velocity estimation bias of the body based on a combination of the transformed first movement data and the transformed second movement data; and generating a velocity estimation of the body with the determined velocity estimation bias of the body.
