基于隐马尔可夫模型的多孔径SAR目标检测
HIDDEN MARKOV MODELS FOR MULTI-APERTURE SAR TARGET DETECTION
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摘要: 穿透叶簇的VHF/UHF超宽带(UWB)SAR具有相对带宽很宽,积累角大的特点,可同时获得距离、方位两个方向的高分辨能力,能用于探测叶簇隐蔽的军用车辆等人造目标而有着重要的军事应用价值。在多孔径SAR成像的基础上,本文用隐马尔可夫模型对人造目标和叶簇等杂波建模,可有效地检测目标,实现一个ATR系统的预筛选处理。Abstract: Foliage penetrating VHF/UHF Ultra-WideBand (UWB) SAR can image hidden man-made targets such as military vehicles with wide-angle and ultra-wideband to achieve high resolutions in both range and azimuth, which has great military application value. Exploiting several multi-aperture SAR images, HMMs for man-made object and foliage clutter are developed separately in the paper, which can be utilized in detecting targets effectively to realize the pre-screening process in a ATR system.
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Flake L R, et al. Progress report: Multi-aperture SAR target detection using hidden Markov models. Technical Report TR-94-02, The Ohio State University, SPANN Laboratory, November,1994.[2]Kapoor R, Nandhakumar N. Multi-aperture ultra-wideband SAR processing with polarimetric variety[J].SPIE.1995, 2487:26-37[3]Halverson S D,et al. A comparison of ultra-wideband SAR target detection algorithms[J].SPIE.1994, 2230:230-243[4]蒋咏梅.UWB叶簇覆盖SAR人造目标模型.技术报告,长沙:国防科技大学电子工程学院,1997.[5]谢锦辉.隐Markov模型(HMM)及其在语音处理中的应用.武汉:华中理工大学出版社,1995:1-46.
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