基于稀疏和冗余表象的鬼成像雷达研究进展

基于稀疏和冗余表象的鬼成像雷达(Ghost Image via Sparsity Constraints,GISC Lidar)是一种结合光场空间涨落特性和现代信息论的全新雷达成像体制,其成像视场和分辨率无关,由此可在探测时采用大视场凝视成像模式捕捉运动目标以对其进行高分辨率成像探测。与闪光照相雷达需要将目标的反射光信号成像分布在焦平面阵列光电探测器件上相比,GISC雷达只需要一个无空间分辨能力的单像素探测器接收目标场景的全部反射光信号,因此可以极大地提升系统的成像探测灵敏度。此外,GISC雷达在成像探测过程中可以利用图像的各种先验约束,从而突破奈奎斯特采样定理对采样次数的要求,大幅度提高图像的信息获取效率。文中将结合上海光机所将鬼成像技术应用于雷达探测的研究历程,介绍GISC雷达研究进展,并指出GISC雷达工程化实际应用中仍待解决的若干问题。

Research progress of GISC lidar

Ghost Image via Sparsity Constraints(GISC) lidar is a novel image lidar system which combines the light field coherence theory and modern information theory. The field of view(FOV) of GISC lidar is independent from its image resolution, and can obtain high resolution image of moving targets with a large FOV. While flash imaging lidar divides the intensity of target image into many small pixels of array charge-coupled device(CCD) camera on the imaging plane, GISC lidar uses a single pixel detector without spatial resolution to collect the entire reflective light intensity, which can greatly increase its detection sensitivity. Besides, based on various sparsity constraints of the target, GISC lidar can greatly improve imaging speed with much less samples compared to Nyquist Sampling requirement. Current development of GISC lidar based on the research experience of SIOM was introduced. Finally, the topics which need further investigation to improve the performance of GISC lidar in real application were also presented.