Grace Michael R, Dutton Zachary, Ashok Amit, Guha Saikat
J Opt Soc Am A Opt Image Sci Vis. 2020 Aug 1;37(8):1288-1299. doi: 10.1364/JOSAA.392116.
Passive imaging receivers that demultiplex an incoherent optical field into a set of orthogonal spatial modes prior to detection can surpass canonical diffraction limits on spatial resolution. However, these mode-sorting receivers exhibit sensitivity to contextual nuisance parameters (e.g., the centroid of a clustered or extended object), raising questions on their viability in realistic scenarios where prior information about the scene is limited. We propose a multistage detection strategy that segments the total recording time between different physical measurements to build up the required prior information for near quantum-optimal imaging performance at sub-Rayleigh length scales. We show, via Monte Carlo simulations, that an adaptive two-stage scheme that dynamically allocates recording time between a conventional direct detection measurement and a binary mode sorter outperforms idealized direct detection alone when no prior knowledge of the object centroid is available, achieving one to two orders of magnitude improvement in mean squared error for simple estimation tasks. Our scheme can be generalized for more sophisticated tasks involving multiple parameters and/or minimal prior information.
被动成像接收器在检测之前将非相干光场解复用为一组正交空间模式，其空间分辨率可以超越传统衍射极限。然而，这些模式分选接收器对上下文干扰参数（例如，聚集或扩展物体的质心）敏感，这引发了关于它们在场景先验信息有限的现实场景中的可行性的问题。我们提出了一种多阶段检测策略，该策略在不同物理测量之间分割总记录时间，以在亚瑞利长度尺度上建立实现近量子最优成像性能所需的先验信息。通过蒙特卡罗模拟，我们表明，当没有物体质心的先验知识时，一种在传统直接检测测量和二元模式分选器之间动态分配记录时间的自适应两阶段方案优于单独的理想直接检测，在简单估计任务中均方误差提高了一到两个数量级。我们的方案可以推广到涉及多个参数和/或最少先验信息的更复杂任务。
