Gold metasurfaces on GaSb for compressively sensed mid-wave infrared spectral reconstruction

Mid-wave infrared (MWIR) hyperspectral detection enables a significant enhancement in target camouflage recognition capability. Methods based on computational spectroscopy demonstrate absolute predominance in real-time performance, detection range, and spatial resolution. This work presents an MWIR GaSb-substrate metallic metasurface compatible with a single-step lift-off fabrication process for hyperspectral computational spectral imaging. All simulations and experiments in this paper were conducted under the condition of 0° linearly polarized incident light. The finite-difference time-domain (FDTD) method is utilized to simulate the transmission spectra of 36 metasurface unit cells, construct the observation matrices, and analyze their correlation coefficients and energy utilization efficiency. Through a greedy algorithm, 11 low-correlation structures are screened, reducing the average correlation coefficient from 0.539 to 0.376 while boosting the energy utilization efficiency to 63.6%, thereby remarkably enhancing the system's compressive sensing performance. The basis pursuit algorithm is employed for reconstructing Gaussian and complex sparse spectral signals, revealing that the co-design of metasurface structural optimization and compressed sensing algorithms plays a pivotal role in improving the performance of miniature spectrometers. This paper provides a viable pathway for the development of portable spectral imaging systems for complex environments, with extensive application prospects in fields including environmental monitoring, food safety, and biomedical engineering.