<![CDATA[To operate effectively in complex environments, distributed radar systems re quire a robust constant false alarm rate (CFAR) processor. Conventional distributed cell-averaging (D-CA) CFAR detectors are optimal in homoge neous noise. However, they suffer severe performance degradation in non homogeneous scenarios, specifically under multiple interfering targets and abrupt clutter edges. This study presents a comprehensive performance analysis of distributed order statistics (D-OS) CFAR systems employing the K-out-of-L fusion rule. We derive the exact global detection and false alarm probabilities using the Poisson binomial distribution. These models are implemented via vari able precision arithmetic to ensure numerical stability under extreme masking conditions. Detection thresholds are rigorously calibrated to maintain a fixed global false alarm rate of 10−4 in homogeneous backgrounds. Quantitative re sults demonstrate that D-OS-CFAR significantly outperforms the D-CA-CFAR baseline. It maintains stable detection performance (PD > 0.9) under clutter power variation and suppresses false alarm surges at clutter edges to approxi mately 4.5 × 10−4. The analysis concludes that lower-K rules (e.g., K = 1,2) offer the optimal trade-off, limiting the homogeneous CFAR loss to below 0.5 dB while ensuring stable operation in highly heterogeneous environments.]]>
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