Adaptive Thresholding using Improvised CFAR Algorithm for Wind Turbine Clutter Mitigation in Homogeneous Environment

Abstract

In this decade, wind farms have piqued the interest of a significant number of scholars and policymakers all around the world. At the dawn of 21^st century, researchers especially environmentalist are concerned about global warming, deterioration of climate, particularly ozone layer thinning. Today green energy is a need of hour. Quest for green energy has caused rapid growth of wind farm installations all over the world. Installations of wind farms obstructing line of sight of communication systems causes interference to receiver. The interference due to Doppler shift generated by the wind Farm having thousands of wind mills are a cause of concern for Communication systems. Specifically, wind turbines and its rotating blades cause adverse effects on the performance of such devices particularly radar. It can cause receiver saturation. The secondary data derived using primary measurement can go erroneous if primary data i.e. Doppler data is not corrected. It is pertinent to design a detector having robustness to interference. In this work, various thresholding algorithms are experimented and novel CFAR architecture is proposed and results are discussed. The performance of variability index CFAR and ordered statistics CFAR method are analyzed. Comparative analysis through the Receiver Operating Characteristics (ROC) is presented to understand the superiority of OS CFAR in the context of mitigation of interference caused by wind turbines /wind farms. Novel strategies for detecting and mitigating wind turbine clutter are addressed in this research article. Results are discussed in detail in further sections.