红外偏振成像在抗干扰目标检测、复杂环境下人造物识别中具有潜在优势, 同时能够获取目标表面理化特性。分时、分振幅、分孔径红外偏振成像方式由于体积、重量、功耗等的不足限制了其应用, 而小型化、集成化、实时成像设备是红外偏振成像广泛应用的前提, 而对于所获取数据的智能分析是其应用的基础。介绍了所研制的红外偏振智能感知系统, 通过分焦平面式成像技术实时采集目标场景的红外偏振数据, 通过深度学习与分焦平面偏振成像紧密融合, 实现高质量偏振图像恢复与典型场景下运动目标的智能感知。

Infrared polarization imaging has potential advantages in anti-jamming target detection and man-made object recognition in complex environment, and can obtain the physical and chemical characteristics of the target surface. The application of division-of-time, division-of-amplitude and division-of-aperture infrared polarization imaging technique is limited to the insufficiency of volume, weight and power consumption. Miniaturization, integration and real-time imaging equipment are the premise of the widespread application of infrared polarization imaging. Intelligent analysis of the acquired data is the basis of its application. In this paper, a new developed infrared polarization intelligent sensing system was introduced, which collected the infrared polarization data of the target scene in real-time by using the division-of-focal-plane imaging technology. By combining the deep learning with the division-of-focal-plane polarization imaging closely, the high quality polarization image restoration and the intelligent sensing of moving target in typical scenes were realized.