Intelligent target recognition method for infrared/laser composite fuze

Abstract In the context of complex environment, the intelligent target recognition method for infrared/laser composite imaging fuze encounters the following challenges: 1) The dearth of infrared/laser composite imaging fuze data hampers the advancement and implementation of deep learning technology in fuze target recognition; 2) The extant infrared/laser composite imaging fuze target recognition methods exhibit suboptimal recognition accuracy in complex terrain and ground conditions, which predisposes them to early or false explotions. To address the aforementioned issues, we have constructed infrared/laser composite imaging target and background dataset in diverse scenes, terrains and features, which provides effective data support for the intelligent recognition of composite imaging fuze. Additionally, we have designed a cross-modal fusion attention mechanism and an invariant feature learning method. The method facilitates the fusion of multimodal complementary information and the intelligent recognition of multi-scale and multi-morphology targets in complex scenes. Furthermore, they enhance the accuracy of the composite imaging fuze, enabling it to adapt to complex terrains. This enhances the combat effectiveness of composite imaging fuze in complex environments, while also offering technical support for the intelligentization of target recognition systems in future ballistic fuze.