A Technique for Evaluating the Uncertainties in Path Loss Predictions Caused by Sparsely Sampled Terrain Data

Abstract

Radio propagation models provide an estimate of the power loss in a communication link caused by the surface of the ground, atmospheric refraction, foliage, and other environmental factors. Many of the models rely on digital topographic databases to provide information about the terrain, and generally the databases are sparsely sampled relative to the electromagnetic wavelengths used for communication systems. This work primarily develops a technique to evaluate the effects of that sparsity on the uncertainty of propagation models.

That is accomplished by accurately solving the electromagnetic fields over many randomly rough surfaces which pass through the sparse topographic data points, many possible communication links, all of which fit the underlying data, are represented. The power variation caused by the different surface realizations is that due to the sparse sampling. Additionally, to verify that this solution technique is a good model, experimental propagation measurements were taken, and compared to the computations.