Parameter Inversion by a Modified Reflected Signal Reconstruction Method for Thin-Layered Media

Parameter estimation of layered media is an important application of ground penetrating radar (GPR). However, in the case of thin-layer detection, the limitation of GPR vertical resolution can lead to overlapping reflected signals, which seriously deteriorates the detection results. To solve this problem, a modified reflected signal reconstruction method based on reflected signal reconstruction is proposed in this letter. First, a forward model of the GPR reflected signal is constructed using the generalized reflection coefficient definition. Then, the parameter inversion is transformed into an optimization problem. The residue cost function is defined as the error square between the model and the actual reflected signal, which is minimized by using genetic algorithm. Furthermore, the generalized reflection coefficient spectrum is feasible to estimate the parameters of each layer as the initial values of the parameters required by the algorithm, thus improving the accuracy and convergence speed of the algorithm. Numerical, experimental, and field tests demonstrate that the method has a high time resolution and antinoise capability in the inversion of layered media parameters.

层状介质的参数估计是探地雷达（GPR）的一项重要应用。然而，在薄层探测的情况下，GPR垂直分辨率的限制会导致反射信号重叠，这严重恶化了探测结果。为解决这一问题，本文提出了一种基于反射信号重构的改进反射信号重构方法。首先，利用广义反射系数定义构建了GPR反射信号的正演模型。然后，将参数反演转化为一个优化问题。将残差代价函数定义为模型与实际反射信号之间的误差平方，并利用遗传算法使其最小化。此外，广义反射系数谱可用于估计各层的参数作为算法所需参数的初始值，从而提高算法的精度和收敛速度。数值、实验和现场测试表明，该方法在层状介质参数反演中具有较高的时间分辨率和抗噪能力。