Estimating stochastic noise using in situ measurements from a linear wavefront slope sensor

Area of Science:

• Optical Engineering
• Wavefront Sensing
• Image Processing

Background:

• Wavefront sensors are crucial for adaptive optics and imaging systems.
• Accurate noise estimation is vital for reliable wavefront reconstruction.
• Solenoidal noise is a component of measurement noise in wavefront sensors.

Purpose of the Study:

• To develop a method for estimating total noise variance from wavefront sensor measurements.
• To utilize the solenoidal component of noise for this estimation.
• To establish a generic and straightforward relationship between ensemble and total noise variance.

Main Methods:

• Explicitly estimating the solenoidal noise component from an ensemble of slope measurements.
• Leveraging the orthogonality of solenoidal noise to wavefront reconstruction under low scintillation.
• Developing a relationship between ensemble noise variance and total noise variance using four heuristic constants.

Main Results:

• The solenoidal noise component can be retrieved even with a non-zero slope signal.
• A straightforward relationship is demonstrated between ensemble and total noise variance.
• The proposed method is shown to be generic, applicable to laboratory experiments and numerical simulations.

Conclusions:

• The explicit estimation of solenoidal noise provides a method for determining total noise variance.
• The derived relationship is independent of incoming wavefront statistics.
• The method's generic nature makes it broadly applicable in wavefront sensing.