In free-space optical link (FSOL), atmospheric turbulence causes fluctuations in both intensity and phase of the received beam and impairing link performance. The beam motion is one of the main causes for major power loss. This paper presents an investigation on the performance of two types of controller designed for aiming a laser beam to be at a particular spot under dynamic disturbances. The multiple experiment observability nonlinear input-output data mapping is used as the principal components for controllers design. The first design is based on the Taguchi method while the second is artificial neural network method. These controllers process the beam location information from a static linear map of 2D plane: optoelectronic position detector, as observer, and then generate the necessary outputs to steer the beam with a microelectromechanical mirror: fast steering mirror. The beam centroid is computed using monopulse algorithm. Evidence of suitability and effectiveness of the proposed controllers are comprehensively assessed and quantitatively measured in terms of coefficient of correlation, correction speed, control exactness, centroid displacement, and stability of the receiver signal through the experimental results from the FSO link setup established for the horizontal range of 0.5 km at an altitude of 15.25 m. The test field type is open flat terrain, grass, and few isolated obstacles.

Atmospheric parameters strongly affect the performance of free-space optical communication (FSOC) systems when the optical wave is propagating through the inhomogeneous turbulence transmission medium. Developing a model to get an accurate prediction of the atmospheric turbulence strength (C(n)(2)) according to meteorological parameters (weather data) becomes significant to understand the behavior of the FSOC channel during different seasons. The construction of a dedicated free-space optical link for the range of 0.5 km at an altitude of 15.25 m built at Thanjavur (Tamil Nadu) is described in this paper. The power level and beam centroid information of the received signal are measured continuously with weather data at the same time using an optoelectronic assembly and the developed weather station, respectively, and are recorded in a data-logging computer. Existing models that exhibit relatively fewer prediction errors are briefed and are selected for comparative analysis. Measured weather data (as input factors) and C(n)(2) (as a response factor) of size [177,147×4] are used for linear regression analysis and to design mathematical models more suitable in the test field. Along with the model formulation methodologies, we have presented the contributions of the input factors' individual and combined effects on the response surface and the coefficient of determination (R(2)) estimated using analysis of variance tools. An R(2) value of 98.93% is obtained using the new model, model equation V, from a confirmatory test conducted with a testing data set of size [2000×4]. In addition, the prediction accuracies of the selected and the new models are investigated during different seasons in a one-year period using the statistics of day, week-averaged, month-averaged, and seasonal-averaged diurnal Cn2 profiles, and are verified in terms of the sum of absolute error (SAE). A Cn2 prediction maximum average SAE of 2.3×10(-13)  m(-2/3) is achieved using the new model in a longer range of dynamic meteorological parameters during the different local seasons.

A dedicated Free Space Optical Link (FSOL) for the range of 0.5 km at an altitude of 15.25 m is established and explained. The power levels of the received signal with meteorological parameters are continuously measured using the opto-electronic assembly and developed weather station respectively and stored in a computer. The existing models selected for comparative analysis are briefed. Measured meteorological parameters and optical attenuation of size [2000 Â 4] are used for linear regression analysis as well as to design the mathematical models more suitable at the test field. In addition, the prediction accuracy of the proposed and selected models during different seasons in one-year period are investigated and validated in terms of RMSE. The average Root Mean Square Error (RMSE) of 0.041 dB/km for the optical attenuation is achieved in the longer range dynamic of meteorological parameters during different local seasons.

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