The SNR is a key parameter of satellite sensors because it quantifies how much the signal has been corrupted by noise. Despite advances in satellite sensors, captured data carries enough noise to affect information extraction and scene interpretation. This noise includes a signal-dependent component, called shot noise, and other signal independent components, e.g., thermal noise. The SNR determines the capabilities and the cost of satellite sensors. The reliability of the information delivered by Earth-observation applications highly depends on the quality of the captured data.
Satellite users require data and images with high SNRs to better serve their analysis needs. However, to build a satellite sensor with a high SNR is challenging, potentially expensive, and often constrained by available technology. For satellites already in orbit, users must cope with the low SNR of the images acquired.
A high SNR can be achieved firsthand by adopting some excessive measures in the satellite design and building phases. These include increasing the aperture or lens size of the optical system to capture as much signal as possible, choosing much more sensitive detectors with a larger pitch size to gather more signal, cooling the detectors to extremely low temperatures to lower the noise, and allocating longer integration times to accumulate more signal. These approaches all have a negative impact on the satellite’s mass, power, and cost. Sometimes, the ultimately achievable SNR still does not meet users’ needs due to the constraint of available technology.
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