Xuejun Zhang

Title: Xuejun Zhang: Innovator in Space-Based ADS-B Technologies

Introduction

Xuejun Zhang is a prominent inventor based in Beijing, China. He has made significant contributions to the field of aviation technologies, particularly in the development of advanced methods for space-based Automatic Dependent Surveillance–Broadcast (ADS-B). With a total of 7 patents, his work is recognized for its innovative approaches to optimizing signal reception and coverage.

Latest Patents

One of Zhang's latest patents is a "Multi-beamforming optimization method for space-based ADS-B based on coverage matrix." This invention outlines a method that calculates signal-to-noise ratios of received signals using an ADS-B signal model and an air-space channel model. It derives the correct reception probability of ADS-B signals by analyzing decoding and collision probabilities, ultimately establishing a digital multi-beamforming optimization model aimed at minimizing the update interval of position messages.

Another notable patent is the "Coevolution-based multi-beamforming optimizing method for space-based ADS-B." This method employs an adaptive dynamic grouping strategy to enhance algorithm performance and optimization efficiency. By grouping optimization parameters based on the orientation of uncovered regions and aircraft density, the method ensures a full-coverage state is achieved efficiently.

Career Highlights

Xuejun Zhang has worked with esteemed organizations such as Beihang University and PetroChina Company Limited. His experience in these institutions has allowed him to collaborate on various projects that push the boundaries of aviation technology.

Collaborations

Zhang has collaborated with notable colleagues, including Pingyi Wu and Xiaoliang Yuan. Their joint efforts have contributed to the advancement of innovative solutions in the field of space-based surveillance.

Conclusion

Xuejun Zhang's contributions to space-based ADS-B technologies exemplify his commitment to innovation in aviation. His patents reflect a deep understanding of complex systems and a drive to enhance safety and efficiency in air traffic management.