Simulation of anisoplanatic lucky look imaging and statistics through optical turbulence using numerical wave propagation

Abstract

This paper investigates anisoplanatic numerical wave simulation in the context of lucky look imaging. We demonstrate that numerical wave propagation can produce root mean square (RMS) wavefront distributions and probability of lucky look (PLL) statistics that are consistent with Kolmogorov theory. However, the simulated RMS statistics are sensitive to the sampling parameters used in the propagation window. To address this, we propose and validate a new sample spacing rule based on the point source bandwidth used in the propagation and the level of atmospheric turbulence. We use the tuned simulator to parameterize the wavefront RMS probability density function as a function of turbulence strength. The fully parameterized RMS distribution model is used to provide a way to accurately predict the PLL for a range of turbulence strengths. We also propose and validate a new parametric average lucky look optical transfer function (OTF) model that could be used to aid in image restoration. Our OTF model blends the theoretical diffraction-limited OTF and the average turbulence short exposure OTF. Finally, we show simulated images for several anisoplanatic imaging scenarios that reveal the spatially varying nature of the RMS values impacting local image quality.

Modeling and simulation of multispectral imaging through anisoplanatic atmospheric optical turbulence

“…The rule proposed by Schmidt 3 and also used in Ref. 22 is E Q -T A R G E T ; t e m p : i n t r a l i n k -; e 0 2 0 ; 1 1 6 ; 6 9 9…”

“…These parameters were chosen because they correspond to wellvalidated simulation results in prior papers. 5,22 Note in Figs. 5(a) and 5(b) that the diffraction OTF is more low pass and has a lower cutoff frequency at λ 2 ¼ 1.50 μm than at λ 1 ¼ 0.88 μm.…”

“…One phase screen parameter that is critical for successful numerical wave propagation is the sample spacing. The selection of this parameter is addressed in detail by Rucci et al 22 In that work, a sampling rule is proposed that sets the phase screen sample spacing as follows:…”

“…The aperture gain is a scalar multiplier that determines the bandwidth of the point source model employed. 3,22 This bandwidth is linked to the camera aperture so that is appropriate for the diffraction-limited optics. The parameter c controls how much the sample spacing is impacted by the level of turbulence.…”

“…Fig.8Phase screen sampling parameters22 as a function of wavelength and the refractive index structure parameter. The sample spacing from Eq.…”