The ability of the International Monitoring System (IMS) infrasound network to detect atmospheric nuclear explosions and other signals of interest is strongly dependent on station-specific ambient noise. This ambient noise includes both incoherent wind noise and real coherent infrasonic waves. Previous ambient infrasound noise models have not distinguished between incoherent and coherent components. We present a first attempt at statistically and systematically characterizing coherent infrasound recorded by the IMS. We perform broadband (0.01–5 Hz) array processing with the IMS continuous waveform archive (39 stations from 1 April 2005 to 31 December 2010) using an implementation of the Progressive Multi-Channel Correlation algorithm in log-frequency space. From these results, we estimate multi-year 5th, 50th, and 95th percentiles of the RMS pressure of coherent signals in 15 frequency bands for each station. We compare the resulting coherent infrasound models with raw power spectral density noise models, which inherently include both incoherent and coherent components. Our results indicate that IMS arrays consistently record coherent ambient infrasound across the broad frequency range from 0.01 to 5 Hz when wind noise levels permit. The multi-year averaging emphasizes continuous signals such as oceanic microbaroms, as well as persistent transient signals such as repetitive volcanic, surf, thunder, or anthropogenic activity. Systematic characterization of coherent infrasound detection is important for quantifying a station's recording environment, signal-to-noise ratio as a function of frequency and direction, and overall performance, which all influence the detection probability of specific signals of interest.