PERFORMANCE ANALYSIS OF A MODIFIED CFAR BASED RADAR DETECTOR UNDER PEARSON DISTRIBUTED CLUTTER

An adaptive target detector in radar system is used to extract targets from background in noisy environment of unknown statistics. The constant false alarm rate (CFAR) is well known detection algorithm that is being used in almost every modern radar. The cell averaging CFAR is the optimum detector in homogeneous clutter environment when the refence cells have identically independent and exponentially distributed signals. The performance of CA CFAR degrades seriously when clutter power substantially varies in non-homogeneous background. To overcome the performance degradation, a non-linear compression technique based CFAR has been introduced for adaptive thresholding to meet the challenges of target detection from various degrees of Pearson distributed non-homogeneous clutter. Extensive MATLAB simulations have been done using various levels of clutter input to show the effectiveness of the proposed design. Improvement in Signal-to-Noise ratio (SNR) has been achieved using Swerling I model for Rayleigh fluctuating target in the backdrop of heavy clutter.