Abstract
The coal mining research technology is gaining popularity in terms of thickness measurement of coal mining horizon. The main challenge is to improve a robust sensing method for estimating the coal layer thickness left on mine-haulage way roofs for mine safety. This study addresses this challenge by step frequency continuous wave ground penetrating radar (GPR), whose resolution is dependent on bandwidth. To improve the time resolution of GPR signal, this study adopted four high-resolution algorithms, which are also known as subspace methods, namely, estimation of signal parameter via rotational invariance techniques, multiple-signal classification (MUSIC) algorithm, polynomial version of MUSIC, i.e. root-MUSIC and root-Min-Norm. The performance of all these algorithms is compared with synthetic data generated by the plane wave model and full wave model. The results are presented in terms of resolution power as well as relative root-mean-square error on the estimated thickness.
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