This study investigates single-frequency GNSS measurements from a commercial nanosatellite constellation for ionospheric mapping. The input data were collected onboard the Astrocast nanosatellite constellation, with each satellite equipped with firmware-modified u-blox M8T single-frequency multi-GNSS receivers. The collected data, sampled at 2 Hz, includes GNSS pseudo range, carrier phase, Doppler, and C/N0 measurements, as well as satellite position and velocity from an onboard navigation solution. Analysis of the measurements reveals that with the backward-looking GNSS antenna, GPS L1 signals can be tracked deep into the atmosphere, providing insight into the ionosphere and, to some extent, the neutral atmospheric composition along the signal paths. A total of 14 hours of raw data were analysed, during which about 1800 radio occultation events were identified. Signal processing was performed using Bernese software v5.4 and the open-source raPPPid software. Data processing involved computing a reduced-dynamic orbit solution from a subset of GNSS raw measurements (above a certain elevation angle) to generate the reference orbits for the Astrocast satellites. The reference orbits and estimated receiver clock offsets were used as input for a refined solution to extract the ionospheric excess phase from the GNSS raw measurements in the form of cleaned post-fit residuals for each radio occultation event. Handling outliers and data gaps in the pseudo range and carrier phase measurements was a crucial aspect of the GNSS signal processing. To reduce noise in the extracted STEC (Slant Total Electron Content) time series, a smoothed pseudo range and a carrier phase solution were tested as alternatives to the navigation solutions. For validation, the STEC retrievals were compared with reference values derived from the TIE-GCM and NeQuick-G models for various local times and tangent point loca-tions. Additionally, simultaneous ionospheric excess phase retrievals from multiple nanosatellite measurements were integrated into a tomographic system, along with ray-traced signal paths, to estimate electron density fields. A key challenge in converting integral measurements into electron density fields is the distribution of observation signals. Therefore, a subset of events with favorable observation geometry was selected to demonstrate the potential of dense nanosatellite formations for estimating 2D elec-tron density fields using tomographic principles. As large satellite constellations of hundreds or even thousands of satellites in low Earth orbit emerge, the results from this demonstration campaign highlight the potential of this technique for comprehensive ionospheric sensing, offering promising prospects for future atmospheric studies and monitoring.