Abstract
Owing to the absorbing, refracting and scattering effects of the propagation medium, electromagnetic (EM) energy will degrade with the increment of propagation range, and the maximum value exists at the point of the radiating source. Employing this phenomenon, this paper introduces a novel approach to detect the location of EM transmitters in an atmospheric duct environment. Different from previous matched-field processing (MFP) methods, the proposed method determines the source location through reconstructing the forward propagation field pattern by the backward adjoint integration of the parabolic equation (PE) propagation model. With this method, the repeated computations of PE used in the MFP methods are not needed. The performance of the method is evaluated via numerical simulations, where the influences of the measurement noise and the geometry of the receiver array on the localization results are considered.
Highlights
In tropospheric electromagnetic (EM) wave propagations, the issues of determining source locations from range and/or range-difference observations gathered with an array of receivers have been studied a lot due to many important applications, such as surveillance, radio communications, and navigation [1,2,3].Source localization is an inverse problem, and the solution is usually ill-posed, especially for multipath propagations caused by atmospheric duct environments
Owing to the absorbing, refracting and scattering effect of the propagation medium, EM energy will degrade with the increment of the propagation range, and the maximum value exists at the point of the radiating source
This paper proposes a method for source localization using backward propagation of the adjoint integration of the parabolic equation (PE) model
Summary
In tropospheric electromagnetic (EM) wave propagations, the issues of determining source locations from range and/or range-difference observations gathered with an array of receivers have been studied a lot due to many important applications, such as surveillance, radio communications, and navigation [1,2,3]. Source localization is an inverse problem, and the solution is usually ill-posed, especially for multipath propagations caused by atmospheric duct environments Previous studies treated these problems as an optimization problem and solved them by matching the observed signals with the Atmosphere 2015, 6 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.
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