Determining the imaging plane of a retinal capillary layer in adaptive optical imaging

Even in the early stage,endocrine metabolism disease may lead to micro aneurysms in retinal capillaries whose diameters are less than 10 μm.However,the fundus cameras used in clinic diagnosis can only obtain images of vessels larger than 20 μm in diameter.The human retina is a thin and multiple layer tissue,and the layer of capillaries less than10 μm in diameter only exists in the inner nuclear layer.The layer thickness of capillaries less than 10 μm in diameter is about 40 μm and the distance range to rod＆cone cell surface is tens of micrometers,which varies from person to person.Therefore,determining reasonable capillary layer（CL） position in different human eyes is very difficult.In this paper,we propose a method to determine the position of retinal CL based on the rod＆cone cell layer.The public positions of CL are recognized with 15 subjects from 40 to 59 years old,and the imaging planes of CL are calculated by the effective focal length of the human eye.High resolution retinal capillary imaging results obtained from 17 subjects with a liquid crystal adaptive optics system（LCAOS） validate our method.All of the subjects＇ CLs have public positions from 127 μm to 147 μm from the rod＆cone cell layer,which is influenced by the depth of focus.

A new SINS/GPS sensor fusion scheme for UAV localization problem using nonlinear SVSF with covariance derivation and an adaptive boundary layer

The state estimation strategy using the smooth variable structure filter （SVSF） is based on the variable structure and sliding mode concepts. As presented in its standard form with a fixed boundary layer limit, the value of the boundary layer width is not precisely known at each step and may be selected based on a priori knowledge. The boundary layer width reflects the level of uncertainty in the model parameters and disturbance characteristics, where large values of the boundary layer width lead to robustness without optimality and small values of the boundary layer width provide optimality with poor robustness. As a solution and to overcome these limitations, an adaptive smoothing boundary layer is required to achieve greater robustness and suitable accuracy. This adapted value of the boundary layer width is obtained by minimizing the trace of the a posteriori covariance matrix. In this paper, the proposed new approach will be considered as another alternative to the extended Kalman filters （EKF）, nonlinear H∞ and standard SVSF-based data fusion techniques for the autonomous airborne navigation and self-localization problem. This alternative is based on strapdown inertial navigation system （SINS） and GPS data using the nonlinear SVSF with a covariance derivation and adaptive boundary layer width. Furthermore, the full mathematical model of the SINS/GPS navigation system considering the unmanned aerial vehicle （UAV） position, velocity and Euler angle as well as gyro and accelerometer biases will be used in this paper to estimate the airborne position and velocity with better accuracy.

Prototype of solar ground layer adaptive optics at the 1 m New Vacuum Solar Telescope

A prototype of a solar ground-layer adaptive optics （GLAO） system, which consists of a multi-direction corre- lating Shack-Hartmann wavefront sensor with 30 effective subapertures and about a 1 arcmin field of view （FoV） in each subaperture, a deformable mirror with 151 actuators conjugated to the telescope entrance pupil, and a custom-built real-time controller based on field-programmable gate array and multi-core digital signal processor （DSP）, is implemented at the 1 m New Vacuum Solar Telescope at Fuxian Solar Observatory and saw its first light on January 12th, 2016. The on-sky observational results show that the solar image is apparently improved in the whole FoV over 1 arcmin with the GLAO correction.