Landing State Recognition of Carrier-Based Aircraft Based on Adaptive Feature Enhancement and Fusion - WANG Ke, LIU Yiyang, YANG Jie, LU Aiguo, LI Zhe, XU Mingliang (Shanghai Jiaotong Daxue xuebao, 2025)
The recognition of engagement state aids landing signal officers in formulating command decisions promptly and precisely, which is crucial for guiding carrier-based aircraft landings. A method is proposed for recognizing the engagement state, leveraging adaptive feature enhancement and fusion, which includes an attention mechanism-based feature enhancement module and a multi-scale feature fusion module. The front module enhances visual representation by segmenting feature maps and concatenating spatial and channel domains, and the back module merges high-resolution shallow features with semantically rich deep features to fully utilize contextual information. A prototype system is developed to recognize landing engagement states based on the wearable augmented reality devices. To evaluate the performance of the method proposed, hybrid datasets of landing operations are constructed. The results show that the proposed algorithm outperforms baseline algorithms and meets the application requirements of engagement state recognition.