Abstract: 

Multi-source fusion array signal processing focuses on integrating signals from multiple sensor arrays to enhance detection, estimation, and interpretation accuracy. An array, typically composed of multiple sensors or antennas, collects signals from different sources, spatial locations, or frequencies. The processing techniques aim to fuse this multi-dimensional data in order to improve signal quality by reducing noise, compensating for missing information, and maximizing the signal-to-noise ratio. In practical applications like radar, sonar, and communication systems, array-based signal processing enables more accurate and robust performance. By combining data from multiple sensor arrays, it ensures higher resolution, better interference rejection, and more precise tracking and localization. This approach is particularly crucial in fields like defense, telecommunications, and environmental monitoring, where high-performance and real-time decision-making are essential.

Session Chairs: 

Prof. Yan Wang (Beijing Institute of Technology, China), 

Dr. Guangbin Zhang (Beijing Institute of Technology, China)