Interpretation target pattern of a buried basic object on Surface Ground Penetrating Radar system

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 tries to enhance GPR capability by representing the visual/pattern of the detected target. 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.

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