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Convex approximation to the likelihood criterion for aperture synthesis imaging
Serge Meimon1, Laurent M Mugnier, Guy Le Besnerais
1Office National d'Etudes et de Recherches Aérospatiales, Département d'Optique Théorique et Appliquée, BP 72, F-92322 Châtillon cedex, France. Serge.Meimon@onera.fr
Summary
Aperture synthesis, used in radio astronomy, can be improved by approximating its noise model. This method optimizes data analysis for higher resolution telescope measurements, validated with simulations and real data.
Area of Science:
- Astronomy and astrophysics
- Signal processing
- Data analysis
Background:
- Aperture synthesis telescopes couple smaller telescopes to achieve higher resolutions.
- Measuring visibility amplitudes and phases separately presents a data-likelihood challenge due to a non-convex noise model.
Purpose of the Study:
- To develop an optimal approximation for the noise model in aperture synthesis.
- To ensure the data-likelihood criterion remains convex for improved estimation.
Main Methods:
- Investigated the estimation problem arising from separate amplitude and phase measurements.
- Developed a method to optimally approximate the non-convex noise model.
- Maintained convexity of the data-likelihood criterion throughout the approximation process.
Main Results:
- Successfully approximated the noise model while preserving criterion convexity.
- Validated the approximation method using simulated data.
- Confirmed the effectiveness of the approximation with experimental astronomical data.
Conclusions:
- The proposed noise model approximation is effective for aperture synthesis.
- This method enhances the accuracy of high-resolution measurements in astronomy.
- The approach is robust, as demonstrated by both simulations and real-world data.