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Compact adaptive spectral imager enabled by MEMS Fabry-Perot filtering chip in longwave infrared

  • Kui Zhou
  • , Xiaodong Wang
  • , Geng Tong
  • , Xingchen Xiao
  • , Jiancun Zhao
  • , Xiaochang Yu
  • , Yiting Yu
  • Northwestern Polytechnical University Xian
  • Key Laboratory of Optical Microsystems and Application Technologies of Ningbo City

Research output: Contribution to journalArticlepeer-review

Abstract

Longwave infrared (LWIR) spectral imaging offers unique capabilities for gas/liquid detection, mineral exploration, environmental monitoring, and military security applications. Conventional LWIR spectral imagers, however, are hampered by reliance on existing dispersion elements, resulting in inflexible operation, limited spectral channels, and excessive bulk, which preclude deployment in intelligent, multi-scenario settings. To address such an issue, we introduce a compact adaptive spectral imager (CASI) leveraging a LWIR large-aperture micro-electro-mechanical systems based Fabry-Perot filtering chip (MEMS-FPFC). A modular chip-front optical architecture yields an ultra-compact volume (150 × 77 × 88 mm³), low-weight (1.11 kg), and “plug-and-play” operation. A synergistic adaptation control system exploits the intrinsic programmability of the MEMS-FPFC to enable diverse adaptive imaging modes-including programmable spectral acquisition spanning global coarse/fine scans, localized fine scans, and arbitrary spectral band combinations-tailored to specific application demands. This adaptability, coupled with spectral channel selection and image fusion algorithms, facilitates efficient and precise target identification. The CASI’s compactness and programmability enable integration onto small unmanned platforms, advancing intelligent LWIR spectral imaging for field-deployable applications in industrial pollution monitoring, mineral prospecting, and security. (Figure presented.)

Original languageEnglish
Article number207
JournalMicrosystems and Nanoengineering
Volume12
Issue number1
DOIs
StatePublished - Dec 2026

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