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An Adaptive Adjustment Algorithm for Scattering Units of GNSS Ocean Reflected Signals

机译:用于GNSS海洋反射信号的散射单元自适应调整算法

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The Global Navigation Satellite System (GNSS) reflected signals change with the physical characteristics of the reflected surface, which are different from GNSS signals. Therefore, the reflected signals are suitable in remote sensing field. The simulation of GNSS reflected signals is a branch of GNSS Reflectometry (GNSS-R). In most of the previous studies, the scattering area is solidified and equally spaced and the amount of calculation will increase. In this paper, the influence of different scene configurations on the size of the scattering unit is analyzed, and an adaptive adjustment algorithm for the scattering unit is proposed by using RBF neural network model, which can adjust adaptively according to the scene configuration parameters. The proposed algorithm meets the requirements in accuracy and takes only 0.09 of the theoretical model time. On the basis of ensuring the simulation accuracy of the model, the calculation efficiency is greatly improved.
机译:全局导航卫星系统(GNSS)反射信号随着来自GNSS信号的不同的反射表面的物理特性而改变。因此,反射信号适用于遥感场。 GNSS反射信号的模拟是GNSS反射测量法(GNSS-R)的分支。在以前的大多数研究中,散射区域凝固并同样间隔,并且计算量将增加。在本文中,分析了不同场景配置对散射单元的尺寸的影响,并且通过使用RBF神经网络模型提出了一种散射单元的自适应调整算法,其可以根据场景配置参数自适应地调整。所提出的算法精确符合要求,只需要0.09的理论模型时间。在确保模型的仿真精度的基础上,计算效率大大提高。

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