The ionosphere analysis portion of VLITE is dedicated to the study
of fine-scale (~1-10 km) ionosphere dynamics and the relationship to
larger structures (hundreds of km). The VLA low-band systems have
virtually unmatched sensitivity to fluctuations in the ionosphere
total electron content (TEC), the integrated density of free
electrons along a line of sight. When observing a bright cosmic
source, these systems can be used to characterize TEC fluctuations
more than two orders of magnitude weaker than those detectable with
similar GPS-based methods. Such fluctuations are prevalent on
smaller scales, making the VLA an excellent instrument for probing
fine-scale ionosphere dynamics. Many continuously operating GPS
receivers within New Mexico will also be used to simultaneously study
larger-scale fluctuations. The (nearly) continuous data stream that
will be yielded by VLITE, when combined with this GPS data, will
constitute a singular data set for the study of coupling mechanisms
among fine-, medium-, and large-scale ionosphere dynamics. In
addition, such a continuous flow of data will allow for the
characterization of the fine-scale ionosphere response to relatively
rare atmospheric and/or seismic events such as large storms,
earthquakes, and explosions that would be missed by proposal-based,
low-band observing.
Example of antenna-based TEC gradients from November 11, 2014 observation of the Galaxy cluster
Abell 2052 (A2052). The upper panel shows the δTEC time series for the V1*V4 antenna baseline
(black points) with the values from a polynomial fit to all baselines used to determine
the TEC gradients (red). The north-south and east-west components of the gradient
are shown in the remaining panels for antennas V1 and V4.
The ionosphere pipeline is optimized to sense fluctuations on small temporal (~seconds), spatial
(~few km), and amplitude (~10-3-10-4 TECU km-1) scales.
Because the δTEC values represent antenna-based effects that dominate on short time scales
(~minutes or less), the general approach to signal processing is as follows:
Extract good visibility phases from the raw data, while flagging obviously aberrant data.
Unwrap the phase time series and de-trend to remove slowly varying instrumental and/or source contributions.
Determine and remove contributions from baseline-based errors.
Use final δTEC time series to compute TEC gradients.