Performing tomographic reconstructions from a satellite looking toward Earth. Part 1: implementation and limitations

Area of Science:

• Earth observation science
• Remote sensing technology
• Atmospheric physics

Background:

• Space-based imaging instruments face interference from signals like cloud reflections, ground reflections, and OH-airglow emissions.
• These nuisance signals hinder precise Earth observation tasks.
• Current signal separation methods require refinement for better resolution.

Purpose of the Study:

• To investigate methods for separating nuisance signals in Earth-viewing space imaging.
• To address the challenge of altitude-axis resolution in tomographic reconstructions.
• To analyze the implementation of the maximum likelihood expectation maximization algorithm for signal separation.

Main Methods:

• Utilizing tomographic reconstructions to differentiate between desired signals and interference.
• Exploring various techniques to enhance altitude-axis resolution in imaging data.
• Implementing and evaluating the maximum likelihood expectation maximization (MLEM) algorithm.

Main Results:

• Demonstrated the effectiveness of tomographic reconstruction in separating nuisance signals.
• Identified and discussed methods to improve altitude-axis resolution.
• Provided an analysis of the MLEM algorithm's performance in this context.

Conclusions:

• Tomographic reconstruction is a viable method for mitigating nuisance signals in Earth-viewing space imaging.
• Improving altitude-axis resolution remains a critical area for advancement.
• The MLEM algorithm shows promise for enhancing signal separation accuracy.