Abstract
In this paper, we present a new estimation of the atmospheric refractivity profile combining the scattering signal (electromagnetic wave propagation loss) and the direct signal (phase delay). The refractivity profile is modeled using four parameters, i.e., the gradient of the refractivity profile (c1, c2) and the vertical altitude (h1, h2). We apply the NSGA-II (Non-dominated Sorting Genetic Algorithm II), a multiobjective optimization algorithm, to achieve the goals of joint optimization inversion in the inverting process, and compare this method with traditional individual inversion methods. The anti-noise ability of joint inversion is investigated under the noiseless condition and adding noise condition, respectively. The numerical experiments demonstrate that joint inversion is superior to individual inversion. The adding noise test further suggests that this method can estimate synthesized parameters more efficiently and accurately in different conditions. Finally, a set of measured data is tested in the new way and the consequence of inversion shows the joint optimization inversion algorithm has feasibility, effectiveness and superiority in the retrieval of the refractivity profile.
Highlights
The atmospheric duct is a refraction phenomenon that occurs in the atmosphere where there are larger negative refractive gradient values, causing electromagnetic waves to be bent out of the transmitting direction
The inverting refractivity profile can be more perfectly estimated by joint inversion than by using a single observation to retrieve it
Traditional GA is chosen to test the performance of joint inversion in the ideal condition, the Gaussian noise case, and the real situation, respectively
Summary
The atmospheric duct is a refraction phenomenon that occurs in the atmosphere where there are larger negative refractive gradient values, causing electromagnetic waves to be bent out of the transmitting direction. Wu et al [13] tried using the phase delay and bending angle to retrieve the refractivity profile and obtained a relatively accurate result. This method did not highlight the superiority of joint inversion due to the strong correlation between the two observations. The first kind is based on geophysical observation with the same physical characteristics, for example as in the joint inversion with phase delay and bending angle proposed by Wu et al [13]. In this paper, we will propose a new inversion method to retrieve the atmospheric refractivity profile using independent geophysical observations based on the second inversion thought.
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