Generation of synthetic UHF RFI in urban North American environments

Conventional models for representing power spectral densities in the UHF band, and their corresponding co-variance matrices, fall short in characterizing the statistical properties and other features for both the noise and signal bands. This leaves algorithm designers limited resources to perform realistic Monte Carlo analysis. In this paper, we develop a practical technique to generate unique instantiations of UHF radio frequency interference in urban North American environments. Our approach involves use of a two-state Markov chain to represent the allocation of signal and noise bands, which we further modify with statistically representative amplitude properties. Two models are developed and compared against multiple measurement sets that show improvement upon conventional models in the Kullback-Leilber divergence.