中国科学院研究生院学报
中國科學院研究生院學報
중국과학원연구생원학보
JOURNAL OF THE GRADUATE SCHOOL OF THE CHINESE ACADEMY OF SCIENCES
2010年
1期
36-42
,共7页
舰船检测%K-分布%局部窗口%背景杂波提取
艦船檢測%K-分佈%跼部窗口%揹景雜波提取
함선검측%K-분포%국부창구%배경잡파제취
ship detection%K-distribution%local window%clutter extraction in the background window
提出了一种基于局部K-分布的新的SAR图像舰船检测算法.取目标窗口和背景窗口,通过把泄露到背景窗口中的舰船部分去除,对背景窗口中的剩余部分统计均值和方差,最终得到杂波分布概率模型进行恒虚警检测.相对于K-分布CFAR检测算法和基于局部窗口的K-分布CFAR检测算法,该算法能够适应杂波的局部变化,对距离很近的舰船不会产生漏检.仿真结果表明了方法的有效性.
提齣瞭一種基于跼部K-分佈的新的SAR圖像艦船檢測算法.取目標窗口和揹景窗口,通過把洩露到揹景窗口中的艦船部分去除,對揹景窗口中的剩餘部分統計均值和方差,最終得到雜波分佈概率模型進行恆虛警檢測.相對于K-分佈CFAR檢測算法和基于跼部窗口的K-分佈CFAR檢測算法,該算法能夠適應雜波的跼部變化,對距離很近的艦船不會產生漏檢.倣真結果錶明瞭方法的有效性.
제출료일충기우국부K-분포적신적SAR도상함선검측산법.취목표창구화배경창구,통과파설로도배경창구중적함선부분거제,대배경창구중적잉여부분통계균치화방차,최종득도잡파분포개솔모형진행항허경검측.상대우K-분포CFAR검측산법화기우국부창구적K-분포CFAR검측산법,해산법능구괄응잡파적국부변화,대거리흔근적함선불회산생루검.방진결과표명료방법적유효성.
The new ship detection algorithm based on local K-distribution proposed in this paper uses a target window and a background window, removes the leaked ship pixels in the background window by using special methods, and estimates the remaining pixels in the background window to get the local clutter' s gray mean and variance. Then the local clutter' s gray probability distribution can be modeled to realize CFAR detection. Compared with K-distribution CFAR detector and local K-distribution CFAR detector, the new algorithm can fit the local change of the sea clutter and detect the targets which are too near. The simulation results show the effectiveness of the new algorithm.
