Evaporation Duct Height Estimation and Source Localization From Field Measurements at an Array of Radio Receivers

Abstract

Remote sensing of the atmospheric refractivity structure using signal strength measurements from a single emitter to an array of radio receivers has been proposed as a promising way for refractivity estimation. As a complement to the pioneers' published works, this paper focuses on addressing the problem of simultaneously estimating the evaporation duct height and localizing the source's position. The problem is organized as a multi-parameter optimization issue and genetic algorithm is adopted to search for the optimal solution from various trial parameters. The performance is determined via numerical simulations and mainly evaluated as a function of: 1) the geometry of the receiver array; 2) the transmitting frequency; and 3) the noise in the measurements.

A Subspace Pursuit Method to Infer Refractivity in the Marine Atmospheric Boundary Layer

“…The most important feature of this method is that it is able to overcome the highly multimodal behavior associated with the physics of EM wave propagation. This allows the use a local optimization method instead of a global optimization method which is typically used in the literature (such as genetic algorithms in, for example, [3], [19], [23], [27], [35]). As this method is able to cheaply find an estimate of the refractivity profile using local optimization, it could also be used to warm-start a different method which would typically require a global optimization method.…”

Impact of Radar Data Sampling on the Accuracy of Atmospheric Refractivity Inversions Over Marine Surfaces

“…Bistatic radar inversion approaches utilize radio frequency (RF) data from separated receivers and transmitters to invert for atmospheric refractivity parameters (Gerstoft et al, 2000;Gingras et al, 1997;Penton & Hackett, 2018;Pozderac et al, 2018;Tabrikian & Krolik, 1999;Wagner et al, 2016;Zhang & Yang, 2018;Zhao, 2012;Zhao et al, 2011). There are numerous factors that can impact the accuracy of an inversion using bistatic radar including forward scattering and multipath from the sea surface (Penton & Hackett, 2018); RF measurement quantity, location, and uncertainty (Zhao, 2012); lateral inhomogeneity of the atmosphere (Goldhirsh & Dockery, 1998); and atmospheric turbulence (Wagner et al, 2016).…”

“…In contrast, Zhao et al (2011) performed inversions using a simulated 400-m coverage vertical array but varied the vertical resolution of the array between approximately 2-to 10m array element spacing and found differences in the accuracy of recovered refractivity profiles based on the different sampling resolutions. Different positioning of the same array can also yield different results as shown by Zhao (2012), where results improved when the same array covered 21-30 m versus 1-10 m, but was otherwise identical. Because inversion methods utilize the measured RF data to optimize the refractivity parameters, data density and location are a critical aspect of the approach as has been demonstrated with these aforementioned numerical studies.…”

Source Localization in the Duct Environment with the Adjoint of the PE Propagation Model

“…Previous studies treated these problems as an optimization problem and solved them by matching the observed signals with the OPEN ACCESS predicted fields through the construction of an appropriate cost function [4][5][6]. Using these matching methods, repeated computations of a forward propagation model cannot be helped.…”