基于峰点相似性拟合的GPR双曲波提取方法

Peak-point similarity fitting-based GPR hyperbola extraction method

在探地雷达应用中,双曲波是地下目标识别以及位置、尺寸等重要参数获取的关键形态特征,由于受到复杂地下杂波因素的影响,双曲波呈现出模糊、混乱和不连续等形态,导致其提取复杂度高,难以统一建模。为了提高双曲波提取的鲁棒性,提出了一种基于峰点相似性拟合的双曲波提取方法(PSFE),针对双曲波时变特性,特别是图像中双曲波形态断裂问题,构造波形聚类模型,利用子波区域的相似性获得感兴趣的峰点集,通过拟合有效地将杂波与目标双曲波分离,降低算法对图像质量的依赖性,进而提高双曲波提取的鲁棒性。在模拟数据集和真实数据集中进行对比实验,以验证在不同类型图像下PSFE算法对双曲波提取的性能。实验表明,在复杂的背景噪声和杂波干扰环境下算法具有较强的可行性和鲁棒性。

In ground-penetrating radar applications,hyperbolic waves are the key morphological features for subsurface target identification,as well as for the acquisition of location,size,and other important parameters.Due to the influence of complex subsurface clutter factors,hyperbolic waves tend to be morphologically blurred,chaotic,and discontinuous,leading to high complexity of hyperbolic wave extraction and difficulty of uniform modeling.To improve the robustness of hyperbolic wave extraction,a hyperbolic wave extraction method based on peak point similarity fitting(PSFE)was proposed.For the time-varying characteristics of hyperbolic waves,especially the problem of hyperbolic waveform breakage in images,a waveform clustering model was constructed to obtain the set of peaks of interest using the similarity of subwave regions.Through the effective separation of the clutter waves from the target hyperbolic waves using the fitting,the dependence of the algorithm on the image quality was reduced,thus enhancing the robustness of hyperbolic wave extraction.Comparative experiments were conducted on simulated and real datasets to verify the performance of the PSFE algorithm for hyperbolic wave extraction for different types of images.The experiments show that the algorithm is of high feasibility and robustness in complex background noises and the clutter interference environment.