实际需求导向的多源信息融合相关数学基础理论和优化算法

Key Points

• The aim is to address challenges in classical information fusion theories due to evolving sensors and communication networks.
• Review advancements from the Sichuan University Information Fusion Team over 30 years.
• Establish distributed optimal estimation theory and efficient algorithms under noisy conditions.
• Develop robust fusion frameworks addressing second-order statistical challenges with practical applications.
• The new frameworks and algorithms have been validated in engineering equipment, showing clear advantages.
• Global robust concepts and optimization criteria were proposed for various communication structures and scenarios.