THE FASTEST AND LOWEST NOISE MCT CAMERA FOR SWIR IMAGING
The project leading to this application has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 673944
THEORY OF OPERATION
The discovery of electron initiated avalanche photodiodes (e-APD) using mercury cadmium telluride (MCT) semiconductor materials permitted a significant breakthrough in SWIR imaging.
C-RED One is using a unique 320 x 256 pixels HgCdTe e-APD array with 24 μm pixel pitch. The sensor allows sub-electron readout noise, taking advantage of the e-APD noise free multiplication gain and non-destructive readout ability.
C-RED One is also capable of multiple regions of interest (ROI) readout allowing faster image rate (10’s of KHz) while maintaining unprecedented sub-electron readout noise.
The sensor is cooled down to cryogenic temperature (80 K) using an integrated pulse tube with a high reliability.
C-RED One is opening a new era in terms of sensitivity and speed in the SWIR scientific cameras domain.
- Long range surveillance and Tracking
- OCT Imaging
- Hyperspectral Imaging
- Fluorescence Microscopy
- Cellular Imaging
- Speckle interferometry
- Space Debris Tracking
- Secure Laser Communication
- Fringe Tracking
- Exo-planets research
- Astronomical Observations
- Adaptive Optics
- < 1 electron RON + dark
- Up to 3500 FPS full frame
- Multiple readout modes (Global Reset, Rolling reset, Single read, CDS or non-destructive reads)
- 80K Operation with integrated pulse tube cooling
- 320 x 256 pixels revolutionary Avalanche Photodiode Detector (e-APD)
- 60% QE flat from 1.1 to 2.4 µm (J,H,K)
- 24 µm pixels pitch
- 16 bits precision A/D converter
- Ultra Low Latency CameraLink™ full interface
- Clock & trigger imput / output for synchronous operation
- T-Mount optical interface
- Available in H band configuration (0.8 – 1.75 μm) with f/4 baffle
- Available in K band configuration (0.8 – 2.43 μm) with f/20 baffle
- Embedded cold blocking filters
- SWaP: H 238 x W 180 x L 365 mm, 19.4 kg, up to 300 W
First Light Vision
SDK (C, C++, Python) / LabVIEW / μManager / MatLab
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