Hideki Hayakawa

Radar imaging of underground pipes by automated estimation of velocity distribution versus depth

A method is presented for enhancing GPR images of underground point reflectors, such as buried pipes, by automated estimation of the velocity distribution versus depth. An x-t radar image is first processed by f-k migration for various propagation velocities v. This process is the well-known velocity analysis by diffraction stacking. An x-t-v data matrix is then constructed from these migrated x-t radar images using different propagation velocities v. Next, we simultaneously extract the hyperbolic apex and estimate the propagation velocity of each hyperbola, using the x-t-v data matrix. Interpolating these estimated discrete propagation velocities along the t-axis, we can derive the propagation velocity distribution versus depth. Extracting the image intensity from the x-t-v data matrix along with the derived propagation velocity distribution yields an enhanced reconstructed image of the underground section. The effectiveness of this method is demonstrated by comparing the results of processing experimental GPR data using the automated x-t-v data matrix method with previous methods. This method automatically reconstructs the enhanced underground section at low computing cost.