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郭继坤, 赵清, 陈司晗. 基于相位补偿的矿井超宽带雷达压缩感知成像算法[J]. 煤炭科学技术, 2020, 48(1).
引用本文: 郭继坤, 赵清, 陈司晗. 基于相位补偿的矿井超宽带雷达压缩感知成像算法[J]. 煤炭科学技术, 2020, 48(1).
GUO Jikun, ZHAO Qinɡ, CHEN Sihan. Mine ultra-wide-band radar compression sensing imaging algorithm based on phase compensation[J]. COAL SCIENCE AND TECHNOLOGY, 2020, 48(1).
Citation: GUO Jikun, ZHAO Qinɡ, CHEN Sihan. Mine ultra-wide-band radar compression sensing imaging algorithm based on phase compensation[J]. COAL SCIENCE AND TECHNOLOGY, 2020, 48(1).

基于相位补偿的矿井超宽带雷达压缩感知成像算法

Mine ultra-wide-band radar compression sensing imaging algorithm based on phase compensation

  • 摘要: 基于UWB信号的井下探测成像系统中,根据Nyquist采样定理,提高发射信号的带宽以获取高分辨率,将导致大量的采样数据产生,过大的采样率将会在成像系统的硬件实现上带来很大困难。另一方面,在实际成像过程中,成像数据的完整性决定了最后成像结果的准确性,但由于存在不可避免的误差和噪声影响,以及塌方体阻碍下目标的隐蔽性,这些因素都将使得成像目标的回波数据无法满足成像要求。因此,在对目标回波进行成像处理之前,必须对回波数据进行处理,通过相关算法使回波数据满足理想的成像模型,最后聚焦方位向回波信息得到目标成像结果。为了提高穿透塌方体遮蔽目标成像的分辨率,并解决超宽带信号穿透塌方体成像得到方位向回波数据不足的问题,通过对传统的压缩感知成像算法进行分析介绍,结合井下具体成像环境,提出一种基于相位误差估计的CS成像算法对回波数据进行补偿。该算法的核心思想就是通过对回波数据计算得到相位误差,首先对回波信号的稀疏性进行验证,并构建目标信号的测量矩阵,利用CS成像算法对回波数据重构的同时对数据进行补偿,通过反复迭代误差估计,逐渐提高回波数据量和成像的质量。最后通过不同场景的仿真试验,验证所提算法在回波数据补偿问题上的有效性。

     

    Abstract: In down-hole detection imaging system based on UWB signal, according to Nyquist sampling theorem, increasing bandwidth of the transmitted signal to obtain high resolution will result in a large amount of sampled data. This will bring a lot of difficulty in hardware imaging system. But in actual imaging process,integrity of imaging data determines accuracy of final imaging result, and due to inevitable error and noise effects as well as concealment of target under occlusion, these factors will make echo data of imaging target cannot meet the imaging requirements. Therefore, the echo data must be processed before imaging target echo, which must also meet ideal imaging model by correlation algorithm, and the target imaging result can be finally obtained by focusing the azimuth echo information. In order to improve the resolution of the imaging of the occlusion target, a problem that must be solved is to compensate echo data after penetrating landslide. Based on this, in order to solve the problem of insufficient azimuth echo data obtained by UWB traverse imaging, the traditional compressed sensing imaging algorithm is introduced and analyzed, and combined with the specific imaging environment, a phase error estimation based method is proposed. The core idea of algorithm is to calculate phase error by calculating echo data. Firstly,sparseness of echo signal is verified, and measurement matrix of target signal is constructed. The CS algorithm compensates data while reconstructing echo data. Through repeated iterative error estimation,echo data volume and quality of imaging are gradually improved. Finally, effectiveness of the proposed algorithm in echo data compensation is verified by simulation experiments in several different scenarios.

     

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