Multiple Constant False Alarm Rate (CFAR) Detection Algorithms

The text mentions that many Constant False Alarm Rate (CFAR) detection algorithms rely on the Cell Averaging (CA) method, which demands substantial computational power. This program implements an Order Statistic (OS)-based CFAR detection algorithm to overcome the shortcomings of CA-CFAR approaches. The implementation includes key functions for sorting reference window samples and calculating adaptive thresholds based on ordered statistics rather than arithmetic means. Additionally, it provides detection images and experimental results from my Master's thesis, which serve as valuable reference material. By incorporating the order statistic method, the CFAR algorithm demonstrates improved handling of false alarm issues under various conditions, enhancing detection accuracy and reliability. The experimental results showcase the algorithm's performance across different scenarios with comparative analysis. These materials offer beneficial insights for researchers and professionals working in related fields, particularly those implementing radar signal processing or target detection systems where computational efficiency and false alarm control are critical considerations.