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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

Joint Inversion of Atmospheric Refractivity Profile Based on Ground-Based GPS Phase Delay and Propagation Loss