期刊名称：International Journal on Electrical Engineering and Informatics
印刷版ISSN：2085-6830
出版年度：2009
卷号：1
期号：1
出版社：School of Electrical Engineering and Informatics
摘要：Surface Ground Penetrating Radar (GPR) is the one of Radar technology that is widely used on many applications. It is non-destructive remote sensing metho d to detect undergro und 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 (wit h circular, triangular and rectangular cross-sect ion) 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
