Ordered Statistics Constant False Alarm Rate (OS-CFAR) Detection Algorithm

In constant false alarm rate detection technology, the conventional OS-CFAR method represents an effective approach. This technique enables theoretical derivation of detection probabilities with mathematical formulas across diverse environments including homogeneous backgrounds, clutter edges, and multiple interfering targets, though the formulas themselves are relatively complex. To better demonstrate the method's performance characteristics, this paper conducts OS-CFAR simulations using MATLAB under different environmental conditions and analyzes the resulting performance metrics. The simulation framework incorporates key algorithm components such as reference window configuration, ordered statistics sorting routines, and adaptive threshold calculation functions. Various interfering factors including multipath effects and clutter disturbances are implemented through specialized signal processing modules to ensure methodological robustness and reliability. The implementation includes performance evaluation metrics such as probability of detection (Pd) and false alarm rate (Pfa) calculations. Ultimately, our findings confirm that OS-CFAR maintains excellent performance across diverse operational environments, establishing a solid foundation for its practical application in real-world systems. The MATLAB code structure features modular design with separate functions for signal generation, CFAR processing, and result visualization, allowing for flexible parameter adjustments and scenario configurations.