随着社会经济的不断发展，所需要的能源消耗也越发增加，煤炭资源作为重要的社会资源消耗之一，其开采的安全性和有效性越来越受到关注，在开采过程中能够及时得到煤层中物质信息可以有效的提高开采的安全性和有效性。探地雷达具有较好的穿透性和较快的探测速度，被广泛的用于井下煤层探测。传统的冲激脉冲雷达和单站时间步进频连续波雷达在煤层异质体探测中存在空间分辨率差、时间利用率低的问题，而多输入多输出的空间步进频雷达在接收端可以获得较大的带宽和孔径，具有较高的空间分辨率，因此，研究多输入多输出空间步进频雷达应用于煤层介质中的异质体探测具有十分重要的意义。

论文首先研究了空间步进频雷达的远场信号模型，利用发射信号的正交特性在接收端通过匹配分离将发射的各频点信号分离，建立接收信号模型。然后在煤层介质的基础上，根据近场模型的几何形状计算异质体相对于阵列的位置关系，得到距离和角度联合的近场等效接收信号模型。进一步，针对煤层异质体在少快拍和低信噪比情况下估计精度较低的问题，提出了基于2D-l_q-SAMV稀疏恢复算法的距离-角度二维功率谱估计方法。仿真结果表明，所提的2D-l_q-SAMV算法能准确的实现目标距离-角度的二维参数估计，相对于2D-MUSIC、NF-IAA和2D-SAMV算法，该方法在少快拍和低信噪比情况下具有较高的估计精度。

最后，针对煤层介质中存在邻近强弱不同异质体时估计性能下降的问题，提出了2D-l_q-SAMV-CRELAX联合算法实现邻近强弱异质体的二维参数联合估计。仿真结果表明，相比于2D-RELAX算法，所提的2D-l_q-SAMV-CRELAX算法能够有效的改善邻近强弱异质体的参数估计性能，更好的提高弱目标的参数估计准确度。

With the continuous development of social economy, the energy consumption is also increasing. As one of the important social resource consumption, the safety and effectiveness of coal mining have attracted more and more attention. The timely acquisition of material information in the coal seam during the mining process can effectively improve the safety and effectiveness of mining. Ground penetrating radar (GPR) has good penetrability and fast detection speed, which is widely used in underground coal seam detection. The traditional impulse radar and single station time stepped frequency continuous wave radar have the problems of poor spatial resolution and low time utilization in the detection of heterogeneous objects in coal seam. The spatial stepped frequency radar with multiple-input and multiple-output (MIMO) can obtain larger bandwidth and aperture at the receiving end, and has higher spatial resolution. Therefore, it is of great significance to study the application of multi-input and multi-output spatial stepped frequency radar to heterogeneous body detection in coal seam media.

In this paper, the far-field signal model of spatial stepped frequency radar is studied firstly. By using the orthogonality of the transmitted signal, the transmitted signals of each frequency point are separated by matching separation at the receiving end, the receiving signal model is established. Then, based on the coal seam medium, the position relationship between the heterogeneous body and the array is calculated according to the geometry of the near-field model, and the near-field equivalent received signal model with joint range and angle is obtained. Furthermore, to solve the problem of low estimation accuracy of coal seam heterogeneous bodies in the case of few snapshots and low signal-to-noise ratio, a range-angle two-dimensional power spectrum estimation method based on 2D-l_q-SAMV sparse recovery algorithm is proposed. The simulation results show that the proposed 2D-l_q-SAMV algorithm can accurately estimate the range-angle parameters of the target. Compared with 2D-MUSIC, NF-IAA and 2D-SAMV, the proposed method has higher estimation accuracy in the case of less snapshots and low signal-to-noise ratio.

Finally, in view of the problem that the estimation performance is degraded when there are adjacent strong and weak heterogeneous bodies in coal seam media, the 2D-l_q-SAMV-CRELAX joint algorithm is proposed to realize the joint estimation of two-dimensional parameters of adjacent strong and weak heterogeneous bodies. Simulation results show that, compared with 2D-RELAX algorithm, the proposed 2D-l_q-SAMV-CRELAX algorithm can effectively improve the parameter estimation performance of adjacent strong and weak heterogeneous bodies, and better improve the parameter estimation accuracy of weak targets.

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