An adaptive GPR imaging algorithm with dimension reduction based on RCB theory

摘要

The conventional Ground Penetrating Radar (GPR) imaging algorithms will cause lots of interference such as sidelobes and clutters in the imaging results. An adaptive GPR imaging algorithm is proposed for GPR imaging by using the theory of Robust Capon Beamforming (RCB). The proposed algorithm is adaptive and with remarkable capability of interference suppression. The dimensionality of the covariance matrix is reduced to improve the calculation speed of the proposed algorithm. Two field experiments have been performed to verify the validity of the proposed algorithm. The sidelobes and clutters are dramatically suppressed, as well as the imaging resolution improves slightly.