Abstract

Spectroscopic technique based on nanophotonic filters can recover spectral information through compressive sensing theory. The spectral information is encoded by nanophotonic response functions and decoded by computational algorithms. They are generally ultracompact, low in cost, and offer single-shot operation with spectral resolution better than 1 nm. Thus, they could be ideally suited for emerging wearable and portable sensing and imaging applications. Previous work has revealed that successful spectral reconstruction relies on well-designed filter response functions with sufficient randomness and low mutual correlation, but no thorough discussion has been performed on the filter array design. Here, instead of blind selection of filter structures, inverse design algorithms are proposed to obtain a photonic crystal filter array with predefined correlation coefficients and array size. Such rational spectrometer design can perform accurate reconstruction for a complex spectrum and maintain the performance under noise perturbation. We also discuss the impact of correlation coefficient and array size on the spectrum reconstruction accuracy. Our filter design method can be extended to different filter structures and suggests a better encoding component for reconstructive spectrometer applications.

© 2023 Optica Publishing Group

Lightweight computational spectrometer enabled by learned high-correlation optical filters

Zhen Liu, Haojie Liao, Lin Yang, Guiqiang Du, Lei Wei, Yansong Wang, and Yao Chen
Opt. Express 31(14) 23325-23349 (2023)

Miniaturized infrared spectrometer based on the tunable graphene plasmonic filter

Jiduo Dong, Linlong Tang, Binbin Wei, Xiangxing Bai, Qing Zang, Hao Zhang, Chunheng Liu, Haofei Shi, Yang Liu, and Yueguang Lu
Opt. Express 31(2) 1615-1628 (2023)

Design and fabrication of a metallic irregular F–P filter array for a miniature spectrometer

Congcong Liu and Zhijun Sun
Appl. Opt. 60(16) 4948-4953 (2021)

High-resolution on-chip spatial heterodyne Fourier transform spectrometer based on artificial neural network and PCSBL reconstruction algorithm

Xiaojing Long, Zhuili Huang, Ye Tian, Jihe Du, and Yufei Liu
Opt. Express 31(20) 33608-33621 (2023)

InSPECtor: an end-to-end design framework for compressive pixelated hyperspectral instruments

T. A. Stockmans, F. Snik, M. Esposito, C. van Dijk, and C. U. Keller
Appl. Opt. 62(27) 7185-7198 (2023)