A theoretical model for the edge image waviness effect is developed for the ground-to-ground imaging scheme and validated by use of IR imagery data collected at the White Sands Missile Range. It is shown that angle-of-arrival (AA) angular anisoplanatism causes the phenomenon of edge image waviness and that the AA correlation scale, not the isoplanatic angle, characterizes the edge image waviness scale. The latter scale is determined by the angular size of the imager and a normalized atmospheric outer scale, and it does not depend on the strength of turbulence along the path.
View Article and Find Full Text PDFA method is presented for sensing atmospheric wave-front tilt from a laser guide star (LGS) by observing a laser beacon with auxiliary telescopes. The analysis is performed with a LGS scatter model and Zernike polynomial expansion of wave-front distortions. It is shown that integration of the LGS image over its angular extent and the position of the auxiliary telescope in an array reduce the tilt sensing error associated with the contribution from the downward path.
View Article and Find Full Text PDFWe have experimentally demonstrated for what is believed to be the first time a method for sensing wave-front tilt with a laser guide star (LGS). The tilt components of wave fronts were measured synchronously from the LGS by use of a telescope with a 0.75-m effective aperture and from the star Polaris by use of a 1.
View Article and Find Full Text PDFWe have experimentally validated the concept of a differential image motion (DIM) lidar for measuring vertical profiles of the refractive-index structure characteristic C(n)(2) by building a hard-target analog of the DIM lidar and testing it against a conventional scintillometer on a 300-m horizontal path throughout a range of turbulent conditions. The test results supported the concept and confirmed that structure characteristic C(n)(2) can be accurately measured with this method.
View Article and Find Full Text PDFJ Opt Soc Am A Opt Image Sci Vis
May 2004
A method of image recovery using noniterative phase retrieval is proposed and investigated by simulation. This method adapts the Cauchy-Riemann equations to evaluate derivatives of phase based on derivatives of magnitude. The noise sensitivity of the approach is reduced by employing a least-mean-squares fit.
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