A Model for Generating Synthetic VHF SAR Forest Clutter Images
We propose a model for generating low-frequency synthetic aperture radar (SAR) clutter that relates model parameters to physical characteristics of the scene. The model includes both distributed scattering and large-amplitude discrete clutter responses. The model also incorporates the SAR imaging pr...
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Veröffentlicht in: | IEEE transactions on aerospace and electronic systems 2009-07, Vol.45 (3), p.1138-1152 |
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description | We propose a model for generating low-frequency synthetic aperture radar (SAR) clutter that relates model parameters to physical characteristics of the scene. The model includes both distributed scattering and large-amplitude discrete clutter responses. The model also incorporates the SAR imaging process, which introduces correlation among image pixels. The model may be used to generate synthetic clutter for a range of environmental operating conditions for use in target detection performance evaluation of the radar and automatic target detection/recognition algorithms. We derive a statistical representation of the proposed clutter model's pixel amplitudes and compare with measured data from the CARABAS-II SAR. Simulated clutter images capture the structure and amplitude responses seen in the measured data. A statistical analysis shows an order of magnitude improvement in model fit error compared with standard maximum-likelihood (ML) density fitting methods. |
doi_str_mv | 10.1109/TAES.2009.5259189 |
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A statistical analysis shows an order of magnitude improvement in model fit error compared with standard maximum-likelihood (ML) density fitting methods.</description><identifier>ISSN: 0018-9251</identifier><identifier>EISSN: 1557-9603</identifier><identifier>DOI: 10.1109/TAES.2009.5259189</identifier><identifier>CODEN: IEARAX</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithms ; Amplitudes ; Character generation ; Clutter ; Density ; Layout ; Object detection ; Pixel ; Pixels ; Radar clutter ; Radar imaging ; Radar polarimetry ; Radar scattering ; Synthetic aperture radar ; Target detection ; Target recognition</subject><ispartof>IEEE transactions on aerospace and electronic systems, 2009-07, Vol.45 (3), p.1138-1152</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. 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A statistical analysis shows an order of magnitude improvement in model fit error compared with standard maximum-likelihood (ML) density fitting methods.</description><subject>Algorithms</subject><subject>Amplitudes</subject><subject>Character generation</subject><subject>Clutter</subject><subject>Density</subject><subject>Layout</subject><subject>Object detection</subject><subject>Pixel</subject><subject>Pixels</subject><subject>Radar clutter</subject><subject>Radar imaging</subject><subject>Radar polarimetry</subject><subject>Radar scattering</subject><subject>Synthetic aperture radar</subject><subject>Target detection</subject><subject>Target recognition</subject><issn>0018-9251</issn><issn>1557-9603</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2009</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNp9kE1Lw0AQhhdRsFZ_gHhZPIiX1P1Mdi9CKf2CimCr12WbzNaUNKm7yaH_3oRWDx48DcM87zDzIHRLyYBSop9Ww_FywAjRA8mkpkqfoR6VMol0TPg56hFCVaSZpJfoKoRt2woleA89D_FLlUGBXeXxFErwts7LDV4eyvoT6jzFH7MJXg7f8KTyEGo8Kpq6Bo_nO7uBcI0unC0C3JxqH71PxqvRLFq8Tuej4SJKuYzrKM2AxJxZnpF17KROlGUylZpxq7gkxGZWOcgYQMaF1EQyS9fOCueAJZYq3kcPx717X3017R1ml4cUisKWUDXB8HZ7wgRvwcd_QcqFFoLGQrbo_R90WzW-bN8wKqY0oSrpIHqEUl-F4MGZvc931h8MJaYzbzrzpjNvTubbzN0xkwPAL_8z_QaJ0Hy9</recordid><startdate>200907</startdate><enddate>200907</enddate><creator>Jackson, J.A.</creator><creator>Moses, R.L.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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subjects | Algorithms Amplitudes Character generation Clutter Density Layout Object detection Pixel Pixels Radar clutter Radar imaging Radar polarimetry Radar scattering Synthetic aperture radar Target detection Target recognition |
title | A Model for Generating Synthetic VHF SAR Forest Clutter Images |
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