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dc.contributor.authorGhanshyam-
dc.date.accessioned2014-12-05T05:02:50Z-
dc.date.available2014-12-05T05:02:50Z-
dc.date.issued2012-
dc.identifierM.Techen_US
dc.identifier.urihttp://hdl.handle.net/123456789/13076-
dc.guideSingh, Dharmendra-
dc.description.abstractGround Penetrating Radar (GPR) is considered as an environmental tool because of its non-destructive uses in many applications like defining landfills, contaminant plumes and many others. Due to their system complexity and high component cost, it was harder to use it. However, over the last decade the cost of RF technologies has decrease considerably, making it more feasible to make step frequency continuous wave radar (SFCW) based GPR. SFCW based radar is better to other types of radar because of its large effective bandwidth which results in a high resolution radar. The basic concept of SFCW based GPR are introduced here. To improve the GPR, a TEM Horn antenna is designed and fabricated for a frequency range 700 MHz to 2000 MHz. Further, to increase the range of antenna an amplifier and a circulator are added to the GPR system. Four targets- two air cavity, a metal sheet and a water bottle were buried at different depth and moisture conditions which were tried to detect and identify with the designed GPR. By the application of preprocessing techniques like Hamming Window Filtering, Median Filtering a B-scan image is constructed. To remove clutter from the image, Independent component analysis (ICA) and Singular value decomposition (SAID) clutter removal techniques were applied on,B-scan images which is generated by summing 40 A-scans data. The obtained B-scan image has capability to check the presence of targets. Once presence of targets was detected, classification and identification of targets were carried out. Three different techniques were applied for classifying and identifying the targets. First, targets were classified using time-frequency analysis. Second, targets were identified using a contextual masking technique which is based on intensity of reflected signal. In the last, probability density function (PDF) based classification was applied. It is observed that the designed SFCW based GPR has a good capability to detect and classify various considered targets upto the depth of 50 cm with moisture level 15%.en_US
dc.language.isoenen_US
dc.subjectELECTRONICS AND COMPUTER ENGINEERINGen_US
dc.subjectR SFCWen_US
dc.subjectENVIRONMENTAL TOOLen_US
dc.subjectCONTAMINANTen_US
dc.titleIDENTIFICATION OF VARIOUS TARGETS FOR SFCW BASED GPRen_US
dc.typeM.Tech Dessertationen_US
dc.accession.numberG21468en_US
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