Validating instrument models through the calibration process

G. E. Bingham; J. J. Tansock

doi:10.1117/12.684348

8 September 2006 Validating instrument models through the calibration process

G. E. Bingham, J. J. Tansock

Proceedings Volume 6297, Infrared Spaceborne Remote Sensing XIV; 62970O (2006) https://doi.org/10.1117/12.684348
Event: SPIE Optics + Photonics, 2006, San Diego, California, United States

Abstract

The performance of modern IR instruments is becoming so good that meeting science requirements requires an accurate instrument model be used throughout the design and development process. The huge cost overruns on recent major programs are indicative that the design and cost models being used to predict performance have lagged behind anticipated performance. Tuning these models to accurately reflect the true performance of target instruments requires a modeling process that has been developed over several instruments and validated by careful calibration. The process of developing a series of Engineering Development Models is often used on longer duration programs to achieve this end. The accuracy of the models and their components has to be validated by a carefully planned calibration process, preferably considered in the instrument design. However, a good model does not satisfy all the requirements to bring acquisition programs under control. Careful detail in the specification process and a similar, validated model on the government side will also be required. This paper discusses the model development process and calibration approaches used to verify and update the models of several new instruments, including Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) and Far Infrared Spectroscopy of the Troposphere (FIRST).

Citation Download Citation

G. E. Bingham and J. J. Tansock "Validating instrument models through the calibration process", Proc. SPIE 6297, Infrared Spaceborne Remote Sensing XIV, 62970O (8 September 2006); https://doi.org/10.1117/12.684348

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KEYWORDS

Calibration

Sensors

Instrument modeling

Performance modeling

Process modeling

Sensor performance

Atmospheric modeling

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