It is difficult to exactly detect small objects in complex shallow subsurface. As the energy of backscattered signal from the target is low, backscattered signals from target and ground surface are overlapped. In addition, clutters created by ground surface and movement strongly depress the signaltoclutter ratio when shallowly buried small objects are detected by portable ground penetrating radar (GPR). An algorithm for detection of shallowly buried objects based on principal component analysis (PCA) is thus proposed in this paper. Via PCA decomposition, current Ascan data are projected onto the projecting direction of background data. A set test function is compared with adaptive threshold to decide if current Ascan data are from an object. Detection of shallowly buried small objects can be achieved in combination with background data dynamic updating. The data tested in sand, laterite, clay and lawn were processed, and the results show that shallowly buried objects can be detected using algorithm based on PCA.
冯温雅, 彭正辉, 费翔宇, 应娉. 基于主元分析法的浅地层小目标探测算法[J]. 物探与化探, 2010, 34(4): 493-496.
FENG Wen-Ya, PENG Zheng-Hui, FEI Xiang-Yu, YING Ping. AN ALGORITHM FOR DETECTION OF SHALLOWLY BURIED SMALL
OBJECTS BASED ON PRINCIPAL COMPONENT ANALYSIS. Geophysical and Geochemical Exploration, 2010, 34(4): 493-496.
[1]Daniels D J.Surface penetrating radar[M].London,UK:The Institution of Electrical Engineers,1996.
[2]Xu Xiaoyin,Miller Eric L.Statistical method to detect subsurface objects using array ground penetrating radar data[J].IEEE Trans on Geoscience and Remote Sensing,2002,40(4).
[3]Gamba P,Lossani S.Neural detection of pipe signatures in ground penetrating radar data[J].IEEE Trans on Geoscience and Remote Sensing,2000,38(2).
[4]Ho K C,Paul D.A linear prediction land mine detection algorithm for hand held ground penetrating radar[J].IEEE Trans on Geoscience and Remote Sensing,2002,40(6).