Data compression for helioseismology

Více o knize

Efficient data compression is crucial for upcoming space missions focused on helioseismology, particularly the Solar Orbiter mission set to launch in 2018. This mission will feature instruments like the Polarimetric and Helioseismic Imager (PHI), which will generate Doppler velocity images essential for helioseismology. Key challenges include a low telemetry rate and limited observation time. This thesis assesses the impact of lossy data compression on helioseismology, with a focus on the Solar Orbiter. The initial section utilizes simulations of solar surface convection alongside a model of the PHI instrument to evaluate its performance for helioseismology. Results indicate that PHI is well-suited for this purpose. Given the Solar Orbiter's low telemetry rate, significant data compression is necessary for the helioseismic data captured by PHI. The second part of the thesis tests data compression performance using data from the Helioseismic and Magnetic Imager (HMI). Findings reveal that the signal-to-noise ratio of supergranulation in time-distance helioseismology, as well as the accuracy of measuring differential rotation through local correlation tracking of granulation, remain stable despite lossy data compression. This suggests that the low telemetry rate may not pose a significant obstacle for helioseismology.