Abstract
Surface Ground Penetrating Radar (GPR) is the one of Radar technology that is widely used on many applications. It is non-destructive remote sensing method to detect underground buried objects. However, the output target is only hyperbolic representation. This research develops a system to identify a buried object on surface GPR based on decision tree method. GPR data of many basic objects (with circular, triangular and rectangular cross-section) are classified and extracted to generate data training model as a unique template for each type basic object. The pattern of object under test will be known by comparing its data with the training data using a decision tree method. A simple powerful algorithm to extract feature parameters of object which based on linier extrapolation is proposed. The result shown that tested buried basic objects can be correctly interpreted and the developed system works properly.
Published Version
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