This paper introduces a robust constant false alarm rate (CFAR) method to detect continuous noise jamming in coherent radar systems with a single antenna having no pattern control. The proposed detector is robust to interfering signals such as strong spikes from neighboring radars and returns from targets of interest and is resistant to land, sea, and weather clutter. The detector operates on data vectors extracted from a real-valued Range-Doppler data matrix generated at the output of Doppler processing for each azimuth cell within the entire scanning sector. Each data vector consists of statistically independent range samples associated with one of the specified Doppler bins. These samples are selected from non-overlapping range intervals allocated within the noise-dominant region in the full range coverage to mitigate the effect of clutter on the detector's performance. To perform jamming detection for each cell under test (CUT) in the current antenna scan, the proposed detector uses the CUT-associated data vectors generated in the current antenna scan and CFAR reference data vectors generated in the previous antenna scan. These reference data vectors are extracted from Range-Doppler data matrices associated with reference azimuth cells uniformly distributed within the entire scanning sector. The proposed detector achieves robustness to interfering signals by using a two-step detection algorithm. The first step performs censored video integration (CVI) for the CUT and reference data vectors and individual adaptive CFAR detection in each specified Doppler bin. The detector applies the "m-of-m" detection strategy to a complete set of decisions declared by the individual CFAR detectors in the second step. This strategy provides immunity to the simultaneous presence of interfering signals in the specified Doppler bins. The robustness of the proposed noise jamming detector is verified using Monte-Carlo simulations.
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