Analyzing the Effect of the Intra-Pixel Position of Small PSFs for Optimizing the PL of Optical Subpixel Localization  

作　　者：Haiyang Zhan Fei Xing Jingyu Bao Ting Sun Zhenzhen Chen Zheng You Li Yuan 

机构地区：[1]Department of Precision Instrument,Tsinghua University,Beijing 100084,China [2]State Key Laboratory of Precision Measurement Technology and Instruments,Tsinghua University,Beijing 100084,China [3]Beijing Advanced Innovation Center for Integrated Circuits,Tsinghua University,Beijing 100084,China [4]Joint International Research Laboratory of Advanced Photonics and Electronics,Beijing Information Science and Technology University,Beijing 100192,China [5]Beijing Institute of Control Engineering,Beijing 100190,Chin

出　　处：《Engineering》2023年第8期140-149,共10页工程（英文）

基　　金：the support from the National Natural Science Foundation of China(51827806);the National Key Research and Development Program of China(2016YFB0501201);the Xplorer Prize funded by the Tencent Foundation。

摘　　要：Subpixel localization techniques for estimating the positions of point-like images captured by pixelated image sensors have been widely used in diverse optical measurement fields.With unavoidable imaging noise,there is a precision limit(PL)when estimating the target positions on image sensors,which depends on the detected photon count,noise,point spread function(PSF)radius,and PSF’s intra-pixel position.Previous studies have clearly reported the effects of the first three parameters on the PL but have neglected the intra-pixel position information.Here,we develop a localization PL analysis framework for revealing the effect of the intra-pixel position of small PSFs.To accurately estimate the PL in practical applications,we provide effective PSF(e PSF)modeling approaches and apply the Cramér–Rao lower bound.Based on the characteristics of small PSFs,we first derive simplified equations for finding the best PL and the best intra-pixel region for an arbitrary small PSF;we then verify these equations on real PSFs.Next,we use the typical Gaussian PSF to perform a further analysis and find that the final optimum of the PL is achieved at the pixel boundaries when the Gaussian radius is as small as possible,indicating that the optimum is ultimately limited by light diffraction.Finally,we apply the maximum likelihood method.Its combination with e PSF modeling allows us to successfully reach the PL in experiments,making the above theoretical analysis effective.This work provides a new perspective on combining image sensor position control with PSF engineering to make full use of information theory,thereby paving the way for thoroughly understanding and achieving the final optimum of the PL in optical localization.

关 键 词：Optical measurement Subpixel localization Precision limit optimization Small point spread functions Centroiding Star sensors 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] O439[自动化与计算机技术—计算机科学与技术]