A low complexity ground-penetrating radar (GPR) clutter removal method based on lattice filter (LF) decomposition is proposed. The GPR image is decomposed into several levels by LF where each level contains approximation and directional subbands. Due to its horizontal structure, the clutter is contained in a horizontal subband, while vertical and diagonal subbands represent the target information. Although the proposed approach seems similar to the classical undecimated wavelet decomposition, the whole process is accomplished in the spatial domain by simple mathematical operations and time delays, thus it has less complexity compared to the wavelet transform which needs the use of fast Fourier transform operations. Moreover, due to the recursive nature of the LFs, the proposed method is more robust to noise. It presents a better detection performance as indicated by the quantitative results. Our method is also compared with the conventional subspace–based methods for both simulated and real datasets, and visual and quantitative results validate the superiority of our proposed method.

提出了一种基于格点滤波分解的低复杂度探地雷达杂波去除方法。GPR图像被LF分解为几个级别，其中每个级别都包含近似和方向子带。由于其水平结构，杂波包含在水平子带中，而垂直和对角子带则代表目标信息。尽管所提出的方法看起来与经典的未抽取小波分解相似，但整个过程是通过简单的数学运算和时间延迟在空间域中完成的，因此，与需要使用快速傅立叶变换操作的小波变换相比，它的复杂度更低。而且，由于LF的递归性质，所提出的方法对噪声更鲁棒。如定量结果所示，它具有更好的检测性能。我们的方法也与传统的基于子空间的方法进行了模拟和真实数据集的比较，并且视觉和定量结果验证了我们提出的方法的优越性。