Abstract
As a pivotal sensor for battlefield information acquisition, situational awareness, and the guidance of precision-guided weapons on airborne platforms, airborne electro-optical payloads have emerged as indispensable equipment for airborne platforms to achieve "wide-area search, long-range detection, precise positioning, rapid engagement, and real-time assessment." Among the various technologies, LiDAR (Light Detection and Ranging) stands out due to its ability to acquire the information of target distance and the intensity of reflectivity simultaneously. This capability makes it a key player in critical missions such as tracking and localization of targets, situational awareness of battlefield, recognition and detection of targets, and guidance of the weapons. This paper provides a comprehensive review of the application of typical LiDAR technologies in airborne electro-optical payload missions. First, we delve into the technical characteristics of LiDAR, summarizing the features that are crucial for the execution of missions. These include ranging accuracy, wavelength selection, beam characteristics, and detector configuration. A detailed analysis is conducted to highlight how these parameters influence the performance of airborne electro-optical systems in diverse operational scenarios. Next, the current applications of LiDAR technology in tracking and localization of targets, situational awareness of battlefield, and recognition and detection of targets are thoroughly examined. Special attention is given to the process of utilizing the information of target distance and the intensity of reflectivity for precise positioning of targets, recognition and detection of targets and heterogeneous image matching/fusion. By integrating these capabilities, airborne platforms can achieve enhanced operational effectiveness in complex battlefield environments. Finally, we explore the development requirements and future directions of LiDAR technology in airborne electro-optical payload missions, particularly following the integration of intelligent processing algorithms rooted in deep learning. The discussion aims to provide valuable insights for advancing the operational effectiveness of airborne electro-optical payloads in future battlefields. By addressing the challenges and opportunities associated with LiDAR integration, this paper seeks to pave the way for innovations that will further strengthen the role of airborne electro-optical systems in modern warfare.