目前，煤矿在我国的能源体系中仍占据主导地位。开采掘进方向煤层中存在的采空区、富水区及陷落柱等不良地质异常体构造为煤矿开采带来了极大的安全隐患。探地雷达作为一种安全高效的无损检测勘探技术，被广泛应用于井下掘进面前方地质构造的超前探测。针对传统井下单发单收探测雷达存在的探测分辨率低、获取数据信息量少的问题，提出将多输入多输出体制下的空间步进频雷达用于井下探测。

本文主要围绕着空间步进频信号在掘进方向煤层构造中的传播情况进行研究。首先，利用中心差分思想，推导时域有限差分算法，并对算法的稳定性条件与吸收边界条件进行了研究。然后，针对煤矿开采掘进方向煤层中存在异常构造的问题，建立井下煤层异常体探测模型，利用时域有限差分算法对所建模型进行正演模拟，探究空间步进频信号在掘进方向煤层中的传播规律。根据煤矿井下小构造环境构建模型，对煤层异常体形状不同、介质不同以及埋藏深度不同的三种情况进行正演模拟。实验结果表明，随着煤层中异常体的相对介电常数增大，反射回波波幅增大；信号在煤层中传播进入水和岩石后回波相位发生反向变化，进入空气则保持原相位；相同介质的情况下随着深度的增加，反射回波幅值减小。根据层状地质环境建立煤层采空区、富水区及两种岩石区模型，正演结果表明，采空区与岩层均可观测到前、后表面产生的反射回波，富水区仅可观察到前表面的反射回波。通过模拟验证空间步进频信号可对煤层异常体进行检测。

正演数据预处理过程中，针对模拟结果中存在直耦波的问题，采用减对空信号方法对其去除；针对结果中存在煤体表面直达波问题，提出SVD平均抵消融合算法对直达波滤除，并通过实验验证其有效性；采用增益调节的方法对煤层内部异常体回波信号增强。数据预处理后直耦波与直达波的干扰降低，异常体回波清晰可辩。通过利用正演模拟结果对模型厚度参数进行验证并实现异常体区域的成像。

At present, coal mines still occupy a dominant position in China's energy system. The unfavorable geological anomaly structures such as mine goafs, water-rich areas, and collapse columns in the coal body in front of mining and tunneling have brought great safety hazards to coal mining. As a safe and efficient non-destructive detection and exploration technology, ground penetrating radar is widely used in advanced detection of geological structures in front of underground tunneling. Aiming at the problems of low detection resolution and small amount of acquired data in traditional underground single-transmit and single-receive detection radars, it is proposed to use the spatial stepped frequency radar under the multiple-input multiple-output system for underground detection.

This article mainly focuses on the propagation of the spatial stepped frequency signal in the coal seam structure in the direction of driving. Firstly, using the central difference theory, the finite-difference time-domain algorithm is derived, and the stability conditions and absorption boundary conditions of the algorithm are studied. Then, aiming at the problem of abnormal structure in the coal seam in the heading direction of coal mining, the abnormal body detection model of coal seam was established. The FDTD algorithm was used to carry out forward simulation on the established model to explore the propagation law of spatial stepping frequency signal in the coal seam in the heading direction. According to the small structural environment of underground coal mine, the forward modeling is carried out for the three situations of different shapes of abnormal bodies in coal seam, different media and different burial depths. The experimental results show that with the increase of relative dielectric constant of abnormal body in coal seam, the amplitude of reflected echo increases. When the signal propagates in coal seam and enters water and rock, the phase of echo changes in reverse, while when it enters air, it remains the original phase. With the increase of depth in the same medium, the amplitude of reflected wave decreases. According to the stratified geological environment, the model of coal seam goaf, water-rich area and two kinds of rock area is established. The forward modeling results show that the reflection echoes from the front and back surface can be observed in both the goaf and the rock layer, and only one reflection echo from the upper surface can be observed in the water-rich area. The simulation proves that the spatial stepping frequency signal can detect the abnormal body of coal seam.

In the process of forward data preprocessing, in view of the direct coupling wave in the simulation result, the method of reducing the air-to-air signal is used to remove it; in view of the direct wave problem on the coal surface, the SVD average cancellation fusion algorithm is proposed to filter the direct wave. In addition, its effectiveness is verified through experiments; the method of gain adjustment is used to enhance the echo signal of abnormal bodies inside the coal seam. After the data is preprocessed, the interference between the direct coupling wave and the direct wave is reduced, and the echo of the abnormal body is clear and distinguishable. Through the use of forward simulation results to verify the model thickness parameters and achieve effective imaging of abnormal body regions.

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