Metasurface Hyperspectral Imaging

Hyperspectral imaging (HSI) for satellite applications is a key technology that reveals hidden spectral information to increase intelligence, surveillance, and reconnaissance (ISR) capabilities. In smaller satellites without sophisticated stabilizing equipment, conventional scanning HSI systems can cause distortions in the hyperspectral datacube (spectral + spatial information). Snapshot HSI reduces the jitter-induced distortions by capturing the entire datacube in a single frame. However, conventional snapshot methods suffer from low-throughput, which decreases signal to noise ratio (SNR) and increases capture latency. In this work, the project team will design a snapshot hyperspectral imager using a combined metasurface-enabled multispectral filter array and computational reconstruction algorithm. Metasurfaces are periodic, two-dimensional arrays with spatially variant subwavelength features that provide arbitrary control of phase, amplitude, and polarization. Additionally, the team will investigate designs for a metasurface primary optic that could reduce size, weight, power, and cost (SWAP-C) of the system. All designs will operate in the short wave infrared (SWIR) and mid-wave infrared (MWIR) bands, which bring unique design and testing challenges compared to visible wavelengths. Downselected designs will be fabricated and characterized to demonstrate manufacturability and validate the model. We will also investigate artificial intelligence models that exploit wavelength diversity and data fusion. By the end of Phase I, we expect to have a demonstrated metasurface concept, allowing us to further develop and experimentally demonstrate this technology in Phase II and beyond.