Abstract
In efforts to structure an expression for wave attenuation under a sand/dust storm, most established calculations pronounce optical visibility as an essential parameter. Although visibility information can be retrieved from weather stations, other commonly encountered sources may present it differently, i.e., as total suspended particles (TSP). Consequently, several empirical equations linking visibility to TSP concentrations were evaluated to address offset tendencies in estimations. In addition to substantiating specific equations, the results revealed that averaging a pair of equations has a 46.09% chance of estimating visibilities with a probability of 37.27%, a relatively low error compared to that achieved by employing single equations, which were found to have a probability of 28.93% with a lesser chance (29.58%) of a low estimation error for the same set of data. The resulting enhancement was evaluated by considering a study on a wireless sensor network’s (WSN’s) signal performance under vaguely labelled meteorological conditions. The meteorological conditions were converted to visibility using the results’ suggestions and were found to be in good agreement with an observation standard set by the China Meteorological Administration (CMA) for sand/dust storm outbreak classifications.
Highlights
The effect of sand storms, among other phenomena, on signal propagation has gathered notable attention from many studies as communication and distant sensing are being utilized by many civil applications
This paper aimed to address the claims of visibility over- and under-estimation tendencies resulting from existing empirical equations
An algorithm was developed to assist in processing various data sets of total suspended particles (TSP) and recorded visibilities, and output the best fitting results in terms of equation recurrences accompanied by their estimation percentage of error
Summary
The effect of sand storms, among other phenomena, on signal propagation has gathered notable attention from many studies as communication and distant sensing are being utilized by many civil applications. As sand storms are a common meteorological phenomenon that will interfere with the highly anticipated advantages of wireless connectivity, different authors have attempted to structure mathematical representations of path attenuation to estimate the loss of signal energy, when under unique environments. Chu [1] developed the first known attenuation coefficient (A) expression for propagating waves in dust or sand storms by employing related scattering theories and assuming a monodispersive particle. Following a series of assumptions, derivations, and substitutions, the author arrived at a general model containing the following parameters: 2π ε−1
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