本文選題：合成孔徑雷達(SAR) + Sentienl-��； 參考：《科技導報》2017年20期

【摘要】：艦船目標幾何特性提取是合成孔徑雷達(SAR)圖像海上目標檢測識別的重要基礎(chǔ)。在具有幾何真值樣本的基礎(chǔ)上,通過參數(shù)尋優(yōu)和擬合回歸,能夠提高幾何特性提取的精度,這在Terra SAR-X數(shù)據(jù)上已有研究。本文考慮Sentinel-1大部分情況下均能提供雙極化數(shù)據(jù)這一特點,探索雙極化信息能否進一步提升幾何特性提取的精度�；贠pen SARShip測試庫,首先使用二維度濾波進行圖像處理,該圖像處理過程中的關(guān)鍵參數(shù)使用交叉熵方法進行尋優(yōu),在大樣本基礎(chǔ)上,得到最優(yōu)參數(shù);之后,在目標幾何特性的圖像處理提取結(jié)果上,綜合傳感器、環(huán)境、目標3方面信息,特別是融合雙極化信息,使用多元線性回歸模型進行擬合,得到比僅用單極化信息更高的幾何特性提取精度,證實了雙極化信息的可用性。
[Abstract]:Geometric feature extraction of ship targets is an important basis for marine target detection and recognition in synthetic Aperture Radar (SAR) images. On the basis of geometric true value samples, the precision of geometric feature extraction can be improved by parameter optimization and fitting regression, which has been studied on Terra SAR-X data. In this paper, we consider that Sentinel-1 can provide bipolarization data in most cases, and explore whether bipolarization information can further improve the precision of geometric feature extraction. Based on Open SARShip test library, 2-D filtering is first used to process the image. The key parameters in the image processing process are optimized by cross-entropy method, and the optimal parameters are obtained on the basis of large samples. In the image processing of the geometric characteristics of the target, the information of sensor, environment, target 3, especially the information of double polarization, is synthesized and fitted by multivariate linear regression model. The accuracy of geometric characteristic extraction is higher than that of single polarization information, and the availability of double polarization information is verified.
【作者單位】： 上海交通大學智能探測與識別上海市重點實驗室;
【基金】：國家自然科學基金重點項目(61331015)
【分類號】：TN957.52

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本文編號：2019970