Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/224280
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dc.coverage.spatial
dc.date.accessioned2018-12-24T06:07:29Z-
dc.date.available2018-12-24T06:07:29Z-
dc.identifier.urihttp://hdl.handle.net/10603/224280-
dc.description.abstractThe objective of the research is to study the usability of Compact Polarimetry mode CTLR and evaluate the potential in improving the accuracy of the ship detection algorithms covering wider swath with reasonable degree of False Alarm (FA). The research limits use of SAR (RISAT-1 CFRS and MRS data, Sentinel 1A GRDH and IW data) and software tools, such as, ERDAS Imagine, Matlab and Exelis ENVI for analysis. The observation of maritime activity is the need of time which has improved since inception of Synthetic Aperture Radar (SAR) imagery from space and aerial platforms. However the large amounts of modern SAR systems image data generate are capable of quickly overburdening a human observer. Conventionally EO image interpretation is done manually is accurate but has got limitations of high processing cost and time besides being in-efficient in adverse weather conditions like fog or clouding. However Microwave SAR remote sensing offers cost-effectiveness with better efficiency and flexibility for the identification of ship under all weather conditions. This research has taken the problem of ship detection and aimed to solve it using advanced computational techniques. The research also discusses techniques which can be adapted for better visualization and classification of image in systematic coverage for ship detection which both Sentinel-1A and Risat-1 has been analysed. Support Vector Machine (SVM) has been used to analyse systematic coverage Medium Resolution to Fine Resolution data and improvised the various techniques for image analysis that could be used for Ship detection problem. An addition paradigm to the Ship Detection and capability enhancement is attempted by proposal of a robust empirical model based classification that can be utilised with limited knowledge of the environment. The various decomposition techniques and classification techniques has been used to derive the target signatures of target using Hybrid Polarimetry to enhance the ship detection algorithms.
dc.format.extent130p.
dc.languageEnglish
dc.relation
dc.rightsuniversity
dc.titleCapability Enhancement of Ship Detection Algorithms by Usage of Circular Transmit Linear Receive Mode of RISAT 1 SAR Data
dc.title.alternative
dc.creator.researcherSenthil Kumar, S
dc.subject.keywordEngineering and Technology,Engineering,Engineering Aerospace,Synthetic Aperture Radar,SAR systems
dc.description.note
dc.contributor.guideSrivastava, Pankaj Kumar and Anasuya Devi, H K
dc.publisher.placeDehradun
dc.publisher.universityUniversity of Petroleum and Energy Studies (UPES)
dc.publisher.institutionDepartment of Aerospace Engineering
dc.date.registered7/1/2012
dc.date.completed7/1/2017
dc.date.awarded24/11/2018
dc.format.dimensions
dc.format.accompanyingmaterialDVD
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Department of Aerospace Engineering

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01_title.pdfAttached File8.95 kBAdobe PDFView/Open
02_acknowledgement.pdf11.96 kBAdobe PDFView/Open
03_declaration.pdf9.52 kBAdobe PDFView/Open
04_certificate.pdf143.58 kBAdobe PDFView/Open
05_abstracts.pdf9.07 kBAdobe PDFView/Open
06_contents.pdf18.57 kBAdobe PDFView/Open
07_list of tables.pdf5.03 kBAdobe PDFView/Open
08_list of figures.pdf10.41 kBAdobe PDFView/Open
09_list of abbreviations.pdf5.42 kBAdobe PDFView/Open
10_chapter1.pdf33.54 kBAdobe PDFView/Open
11_chapter2.pdf147.94 kBAdobe PDFView/Open
12_chapter3.pdf18.21 kBAdobe PDFView/Open
13_chapter4.pdf403.08 kBAdobe PDFView/Open
14_chapter5.pdf3.93 MBAdobe PDFView/Open
15_chapter6.pdf23.94 kBAdobe PDFView/Open
16_references.pdf41.67 kBAdobe PDFView/Open
17_appendices.pdf114.96 kBAdobe PDFView/Open


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