Metric analysis

Optimize competitor instrument needs with objective metrics

Source: Journal of Geophysical Research: Biogeosciences

Designing instruments for space missions is an exercise in managing trade-offs. With severe restrictions on power, mass, and volume, space instruments are often compromised in ways that an equivalent laboratory instrument would not. Each instrument also generally supports a certain number of experiments or observation campaigns.

Each potential use of an instrument benefits differently from attributes such as spatial, temporal, and spectral resolution, or signal-to-noise ratio. For example, geological observations may prefer high spatial and spectral resolution, while meteorological experiments may require high rate observations and a good signal-to-noise ratio. Balancing these competing needs is an essential aspect of instrument design.

Cawse-Nicholson et al. propose a new objective metric to optimize the competing needs of instrument users, which they call intrinsic dimensionality (ID). Intrinsic dimensionality quantifies the content of information in a given set of observations by essentially counting the number of significant components in a principal component analysis of the data.

To test their approach, the authors applied ID to the NASA proposal Surface biology and geology spatialship. They identified and processed spectroscopic data sets from existing sources representative of the mission’s projected capabilities. By resampling the input data in different ways, they simulated various possible instrument compromises, calculating the ID for each.

The study finds that intrinsic dimensionality decreases with noisier and lower resolution observations, which is consistent with intuition. However, the scientists note that this metric can be used to quantify intuition to guide trade-offs. They find that the sample scene (eg, desert or forest) has some effect on ID consistency for spatial considerations, but less so for spectral ones. Going forward, they will apply the concept to other areas of instrument and mission design, such as data rates, flight paths and observation schedules. (Journal of Geophysical Research: Biogeosciences, https://doi.org/10.1029/2022JG0068762022)

—Morgan Rehnberg, Science Editor

Quote: Rehnberg, M. (2022), Optimizing Competing Instrument Needs with Objective Metrics, Eos, 103, https://doi.org/10.1029/2022EO220414. Posted August 29, 2022.
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