Multiscale Decomposition Prediction of Propagation Loss in Oceanic Tropospheric Ducts

Abstract

The oceanic tropospheric duct is a structure with an abnormal atmospheric refractive index. This structure severely affects the remote sensing detection capability of electromagnetic systems designed for an environment with normal atmospheric refraction. The propagation loss of electromagnetic waves in the oceanic duct is an important concept in oceanic duct research. Owing to the long-term stability and short-term irregular changes in marine environmental parameters, the propagation loss in oceanic ducts has nonstationary and multiscale time characteristics. In this paper, we propose a multiscale decomposition prediction method for predicting the propagation loss in oceanic tropospheric ducts. The prediction performance was verified by simulating propagation loss data with noise. Using different evaluation criteria, the experimental results indicated that the proposed method outperforms six other comparison methods. Under noisy conditions, ensemble empirical mode decomposition effectively disassembles the original propagation loss into a limited number of stable sequences with different scale characteristics. Accordingly, predictive modeling was conducted based on multiscale propagation loss characteristic sequences. Finally, we reconstructed the predicted result to obtain the predicted value of the propagation loss in the oceanic duct. Additionally, a genetic algorithm was used to improve the generalization ability of the proposed method while avoiding the nonlinear predictor from falling into a local optimum.

Joint Inversion of Evaporation Duct Based on Radar Sea Clutter and Target Echo Using Deep Learning

“…is the wavelength, is the RCS of the target, and L is the loss in the propagation of electromagnetic waves. In general, the propagation loss L arising from the propagation of electromagnetic waves in tropospheric duct can be expressed as: (3) where f is frequency, and F represents the propagation factor. The propagation factor takes into account the influence of the atmospheric refractivity in the tropospheric duct and the parameters of the radar system on the propagation of electromagnetic waves.…”

“…Combining the simulation data in this paper, according to the modeling process, the following set of parameters for configurations is obtained through certain prior knowledge and a large number of computer experiments. In the parameter adjustment experiments, we explore the following parametric ranges: the number of epoch (1-1000), the batch size (2-256) and the number of hidden layers (1)(2)(3)(4)(5)(6)(7)(8). Finally, we choose a set of parameters as follows-epoch: 1000, batch size: 32 and hidden layers: 5.…”

“…The MABL frequently occurs when temperature and humidity are distributed abnormally across the vertical gradient, and this abnormal environment can affect the atmospheric refractivity, which will influence the propagation path and attenuation features of electromagnetic waves in the atmosphere [2]. This type of phenomenon, which is called tropospheric duct, causes electromagnetic waves to be trapped within it, affecting the electromagnetic wave distribution in the area above the duct layer, and creating unexpected voids and target identification errors, to affect radar performance [3]. The main effects of tropospheric duct on radar performance are shown in Figure 1.…”

Beyond the Horizon, Backhaul Connectivity for Offshore IoT Devices

“…In addition, many articles are published on ED based measurements and predictions to establish a long-range radio link using ED [13][14][15]. Limited measurements in ED are also performed and path loss variations are predicted through machine learning algorithms [16,17]. The climatology of ED and its percentage of occurrence is important for the signal propagation in ED.…”

Editorial for the Special Issue “Advanced Artificial Intelligence and Deep Learning for Remote Sensing”

“…Owing to the long-term stability and short-term irregular changes in marine environmental parameters, the propagation loss in oceanic ducts has nonstationary and multiscale time characteristics. In the contribution by Dang et al [3] "Multiscale Decomposition Prediction of Propagation Loss in Oceanic Tropospheric Ducts", the authors propose a multiscale decomposition prediction method for predicting the propagation loss in oceanic tropospheric ducts. The prediction performance was verified by simulating propagation loss data with noise.…”