The SIMCA algorithm for processing Ground Penetrating Radar data and its use in locating foundations in demolished buildings

摘要

The main challenge of ground penetrating radar (GPR) based foundation detection is to have an accurate image analysis method. In order to solve the detection problem a system level analysis of the issues involved with the recognition of foundations using image reconstruction is required. The SIMCA (‘SIMulated Correlation Algorithm’) is a technique based on an area correlation between the trace that would be returned by an ideal point reflector in the soil conditions at the site and the actual trace. During an initialization phase, SIMCA carries out radar simulation using the design parameters of the radar and soil properties. Then SIMCA takes the raw data as the radar is scanned over the ground and in real-time uses a clutter removal technique to remove various clutter such as cross talk, initial ground reflection and antenna ringing. The trace which would be returned by a target under these conditions is then used to form a correlation kernel. The GPR b-scan is then correlated with the kernel using the Pearson correlation coefficient, resulting in a correlated image which is brightest at points most similar to the canonical target. This image is then raised to an odd power >2 to enhance the target/background separation. To validate and compare the algorithm, photographs of the building before it was demolished along with processed data using the REFLEXW package were used. The results produced by the SIMCA algorithm were very promising and were able to locate some features that the REFLEXW package were not able to identify.