This inventor holds 2 USPTO granted patents. Top assignees: Arizona State University, Ford Global Technolgoies, LLC, North Carolina State University. Active years: 2024-2026.
Company Filing History:



Years Active: 2024-2026
Title: Minhan Li - Innovator in Radar Technology
Introduction
Minhan Li is a prominent inventor based in Raleigh, NC (US). He has made significant contributions to the field of radar technology, particularly in the context of autonomous vehicles. His innovative work focuses on enhancing the accuracy of radar measurements through advanced machine learning techniques.
Latest Patents
Minhan Li holds a patent for "Methods and systems for dealiasing radar range rate measurements using machine learning." This patent describes systems that include at least one processor configured to determine a predicted value of an unwrap factor using a trained machine learning model. The model is designed to provide a predicted value of an unwrap factor for dealiasing a measurement of range rate of a target object. The technology aims to dealiase a measurement value of range rate from a radar of an autonomous vehicle (AV) based on the predicted value of the unwrap factor, thereby providing a true value of range rate. This true value is crucial for controlling the operation of the AV in a real-time environment.
Career Highlights
Minhan Li is currently employed at Ford Global Technologies, LLC, where he continues to develop innovative solutions in the automotive sector. His work is instrumental in advancing the capabilities of autonomous vehicles, making them safer and more efficient.
Collaborations
Throughout his career, Minhan Li has collaborated with notable colleagues, including Fnu Ratnesh Kumar and Xiufeng Song. These collaborations have fostered a creative environment that encourages the development of cutting-edge technologies.
Conclusion
Minhan Li's contributions to radar technology and autonomous vehicles exemplify the impact of innovation in modern transportation. His work not only enhances the functionality of AVs but also paves the way for future advancements in the field.