Location History:
- Shaanxi, CN (2022)
- Xi'an, CN (2022)
Company Filing History:
Years Active: 2022
Title: Innovations by Hao Lv in Non-Contact Detection Technologies
Introduction
Hao Lv is an accomplished inventor based in Shaanxi, China. He has made significant contributions to the field of radar technology, particularly in non-contact detection methods. With a total of two patents to his name, his work focuses on innovative solutions for distinguishing between humans and animals using advanced radar signals.
Latest Patents
Hao Lv's latest patents include a non-contact method for detecting and distinguishing humans and animals based on IR-UWB bio-radar signals. This method involves several steps, starting with the transmission of a radar pulse to a target and obtaining a radar echo signal generated from the reflected pulse. The process includes signal preprocessing, removing direct waves, and calculating peak-to-background ratios to determine the type of target.
Another notable patent is a multi-target life detection method based on radar signals. This method performs time accumulation on preprocessed echo signals and utilizes envelope extraction to identify living targets at specific radar detection distances. The normalization of signal amplitudes in the fast time dimension enhances the accuracy of detection.
Career Highlights
Hao Lv is affiliated with the Air Force Medical University, where he applies his expertise in radar technology to advance medical and detection applications. His innovative approaches have the potential to improve safety and efficiency in various fields.
Collaborations
Hao Lv has collaborated with notable colleagues, including Yang Zhang and Jianqi Wang. Their combined efforts contribute to the advancement of radar technology and its applications in life detection.
Conclusion
Hao Lv's contributions to non-contact detection technologies demonstrate his innovative spirit and commitment to advancing radar applications. His patents reflect a deep understanding of radar signals and their potential to enhance detection methods.
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