Monte Carlo evaluation shows TSNFA detector achieves 99.97-100% detection rate, 100% precision, and zero false-positive clusters per node while classical CFAR and CUSUM variants each fail on at least one performance dimension under Cortex-M0+ constraints.
The Stage 1 median rejects single-frame outliers within each bin; the Stage 2 median tracks slow drift while tolerating contaminated frames in its buffer
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Restoring CFAR Validity for Single-Channel IoT Sensor Streams: A Monte Carlo Comparison of Five Detectors under Cortex-M0+ Constraints
Monte Carlo evaluation shows TSNFA detector achieves 99.97-100% detection rate, 100% precision, and zero false-positive clusters per node while classical CFAR and CUSUM variants each fail on at least one performance dimension under Cortex-M0+ constraints.