{"title":"基于图像空间自回归的高分辨率SAR图像分析","authors":"L. Savy, C.A. Moal","doi":"10.1109/RADAR.2000.851882","DOIUrl":null,"url":null,"abstract":"Classical high resolution (HR) methods become unrealizable when applied to large SAR images, due to memory size and computational time requirements. In this paper, a new HR spectral analysis method, called \"image space\", derived from autoregressive (AR) spectral analysis, is proposed for large-image SAR processing. Simulations and real data processing results are provided, and demonstrate resolution improvement as well as \"good\" behavior on clutter.","PeriodicalId":286281,"journal":{"name":"Record of the IEEE 2000 International Radar Conference [Cat. No. 00CH37037]","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2000-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"High resolution SAR image analysis by new autoregressive algorithm in image space\",\"authors\":\"L. Savy, C.A. Moal\",\"doi\":\"10.1109/RADAR.2000.851882\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Classical high resolution (HR) methods become unrealizable when applied to large SAR images, due to memory size and computational time requirements. In this paper, a new HR spectral analysis method, called \\\"image space\\\", derived from autoregressive (AR) spectral analysis, is proposed for large-image SAR processing. Simulations and real data processing results are provided, and demonstrate resolution improvement as well as \\\"good\\\" behavior on clutter.\",\"PeriodicalId\":286281,\"journal\":{\"name\":\"Record of the IEEE 2000 International Radar Conference [Cat. No. 00CH37037]\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-05-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Record of the IEEE 2000 International Radar Conference [Cat. No. 00CH37037]\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RADAR.2000.851882\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Record of the IEEE 2000 International Radar Conference [Cat. No. 00CH37037]","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RADAR.2000.851882","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
High resolution SAR image analysis by new autoregressive algorithm in image space
Classical high resolution (HR) methods become unrealizable when applied to large SAR images, due to memory size and computational time requirements. In this paper, a new HR spectral analysis method, called "image space", derived from autoregressive (AR) spectral analysis, is proposed for large-image SAR processing. Simulations and real data processing results are provided, and demonstrate resolution improvement as well as "good" behavior on clutter.
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