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Compact infrared cryogenic wafer-level camera: design and experimental validation.

Florence de la Barrière¹, Guillaume Druart, Nicolas Guérineau

¹ONERA, The French Aerospace Laboratory, Palaiseau, France. florence.de_la_barriere@onera.fr

|March 14, 2012

Summary

We developed a compact infrared cryogenic camera with a wide field of view. Cooling the optics achieved a very low noise equivalent temperature difference (NETD) of 15 mK, outperforming traditional infrared cameras.

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Area of Science:

Optics and Photonics
Infrared Technology
Cryogenic Systems

Background:

Traditional infrared cameras face limitations in field of view and sensitivity.
Developing compact, high-performance infrared cameras for cryogenic applications is challenging.
Wafer-level fabrication offers potential for miniaturization and cost reduction.

Purpose of the Study:

To design, fabricate, and characterize a compact infrared cryogenic multichannel camera.
To achieve a wide field of view (120°) and high thermal sensitivity.
To explore the integration of optics and detectors for cryogenic compatibility and wafer-level fabrication.

Main Methods:

A novel camera design merging optics with the detector for cryogenic compatibility.
Wafer-level fabrication techniques for integrated optical and detector components.

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Characterization using modulation transfer function (MTF) and noise equivalent temperature difference (NETD) measurements.

Development and validation of a postprocessing algorithm for image reconstruction.

Main Results:

The developed infrared camera features a compact design and a 120° field of view.
Optical system performance is diffraction-limited.
Achieved a record low noise equivalent temperature difference (NETD) of 15 mK due to optic cooling.
A postprocessing algorithm successfully reconstructed well-sampled images from undersampled data.

Conclusions:

The integrated optics-detector approach is suitable for cryogenic infrared camera development.
The camera offers superior thermal sensitivity compared to conventional infrared systems.
The proposed postprocessing algorithm enhances image quality for undersampled data.