LWIR, photovoltaic, Hg1-xCdxTe, and FPA performance for remote sensing applications

2001 
Focal plane arrays (FPA's), used for remote sensing applications, are required to operate at high temperatures and are subject to high terrestrial background fluxes. Typical remote sensing applications like cloud/weather imagery, sea- surface temperature measurements, ocean color characterization, and land-surface vegetation indices also require FPAs that operate from the visible through the LWIR portion of the spectrum. This combination of harsh requirements have driven the design of a unique LWIR FPA, that operates at 80 K under 300 K background conditions, with an operating spectral range from 11.5 micrometers to 12.5 micrometers , and a spectral cutoff of 13.5 micrometers . The FPA consists of 2 side by side arrays of 1 X 60 HgCdTe, (grown by molecular beam epitaxy) photovoltaic, detector arrays bump bonded to a custom CMOS Si readout. The 2 arrays are completely independent, and can be operated as such. The readout unit cell uses two, current-mode, analog building blocks; a Current Conveyor (CC1) and a dynamic current mirror. The CC1 has input impedance below 300 Ohms and an injection efficiency that is independent of the detector characteristics. This combination extracts high performance and excellent sensitivity from detectors whose average RoA values are approximately 1.7 Ohm-cm 2 at T equals 80 K. The dynamic current mirror is used to subtract high background photocurrent while preserving excellent dynamic range. In addition to the performance enhancing readout, the detectors are manufactured with integral microlenses and operated in reverse bias to take advantage of their increased dynamic impedance. The dark currents associated with reverse bias operation are subtracted along with the background photocurrents by the dynamic current mirror. The expected and measured LWIR FPA performance will be presented. Measurements were performed on an LWIR FPA. Expected and measured FPA results are shown in the table below. The expected data are calculated from FPA models and compared to the measured values.
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