Comparison of Different CFAR Algorithms at Detecting a Target Moving Through a Non-uniform Clutter Environment

Here we investigate different Constant False Alarm Rate (CFAR) algorithms at detecting targets moving along curvilinear trajectories in non-uniform clutter environment of different types. Only primary signal processing is considered. The generalized signal processing model is developed. Statistical simulation is used to evaluate three CFAR algorithms, namely: cell averaging, ordinal statistic, and locally optimal rank. The feature of the developed approach is implementing target detection during its movement along a complex trajectory. The obtained data highlight the effectiveness of rank algorithms.