海军航空大学学报2024，Vol.39Issue(2)：215-223,9.DOI:10.7682/j.issn.2097-1427.2024.02.004
基于双边截断的双参数海上风电站SAR图像CFAR检测
Two-Parameter CFAR Detectionin of Offshore Wind Farms SAR Images Based on Dual Truncated Clutter Statistics
摘要
Abstract
A dual-truncated-clutter-statistics two-parameter CFAR(DTCS-TPCFAR)detector for offshore wind farms in SAR images is proposed.The aim of DTCS-TPCFAR is to improve the detection performance of offshore wind farms in environments such as complex areas with multiple targets and oil spill areas.The proposed method of dual-truncated clut-ter in DTCS-TPCFAR can simultaneously eliminate interference from both high-intensity and low-intensity outliers while preserving true clutter samples.By using maximum likelihood estimation to calculate the mean and standard deviation of the truncated samples,the truncation threshold is computed based on these two estimated parameters.Finally,the target detection is accomplished by detecting the test cells(TC)using the specified probability of false alarm(PFA).This is the first time that CFAR detectors have been applied to detect offshore wind farms.The effectiveness of this method is vali-dated using the Sentinel-1 dataset.Experimental results demonstrate that the proposed algorithm achieves higher detection rate(DR)and lower false alarm rate(FAR)at the same specified PFA compared to other CFAR detectors.关键词
SAR图像/海上风电站检测/恒虚警率检测/复杂环境/双边截断杂波统计特性Key words
SAR images/offshore wind farms detection/constant false alarm rate(CFAR)detection/complex environ-ment/dual-truncated clutter statistics分类
信息技术与安全科学引用本文复制引用
余佳恒,艾加秋,史骏,张勇..基于双边截断的双参数海上风电站SAR图像CFAR检测[J].海军航空大学学报,2024,39(2):215-223,9.基金项目
国家自然科学基金面上项目(62071164) （62071164）
合肥市自然科学基金(2022001) （2022001）
信息材料与智能感知安徽省实验室开放课题(IMIS202102,IMIS202214) （IMIS202102,IMIS202214）
智能互联系统安徽省实验室开放课题(PA2023IISL0098) （PA2023IISL0098）
