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

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.