共查询到19条相似文献,搜索用时 344 毫秒
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基于模型相似度拟合的海杂波统计方法 总被引:1,自引:0,他引:1
本文提出一种基于模型相似度拟合的海杂波统计方法。首先根据合成孔径雷达(SAR)图像计算瑞利分布、对数正态分布、韦布尔分布、K分布、G0分布5种经典的海杂波分布的概率密度函数,然后根据模型间的相似度准则拟合得到新的海杂波分布模型。文章利用四景不同类型的真实SAR数据对算法的拟合性能进行了评价,结果显示利用该算法得到的拟合模型与真实SAR数据的平均Kullback-Leibler距离仅为0.015 84,远优于其他分布模型。基于该拟合模型的恒虚警率舰船检测算法对四景SAR数据的平均检测精度达到95.75%,在控制虚警和漏检方面均优于采用其他模型的同类方法。 相似文献
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从侧扫声纳各类数据的特点出发,通过构建声纳图像的地理编码模型,提出侧扫声纳图像地理编码方法,将声纳回波数据与定位数据一一对应。实验数据结果表明:该方法是合理可行的,不仅较好地处理了定位数据,消除了拖鱼轨迹线上的折点和扇形裂缝,而且可实现海底回波点的地理定位。 相似文献
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高分辨率测深侧扫声纳 总被引:3,自引:0,他引:3
文中介绍了由中国科学院声学研究所和美国亚迪技术开发(上海)有限公司联合设计和制造的高分辨率测深侧扫声纳,它能够同时获得高分辨率的海底地形和地貌。该声纳由电子分机和分别安装在载体左右两侧的两条声纳阵组成,最大工作水深6000m。声纳阵由一条发射线阵和10条间距为λ/2的接收线阵组成,λ为声波波长,其中8条线阵接收声信号,两边的两条为哑元。声纳的多子阵海底自动检测-子空间拟合信号处理方法能克服水声信道多途和复杂海底的影响,正确检测到海底的直达回波。2003年11月和2004年7月,声纳在中国浙江千岛湖进行两次长时间的湖试,获得了高分辨率湖底等深线图和地貌图,正确检测出湖底边长为0.5m立方体目标的高度。 相似文献
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侧扫声呐回波信号是形成侧扫声呐图像的基础,是侧扫声呐系统对水下目标的最直接观测量, 将一维小波变换与非线性增强方法相结合,提出了一种基于小波变换的侧扫声呐回波信号非线性增强算法, 用以改善侧扫声呐图像对比度低、噪声强度大的问题。首先利用改进的 Bayes 阈值对侧扫声呐 ping 信号进行一维小波分解,提取信号特征信息;然后利用 2 种不同的非线性函数对高、低频小波系数进行处理;最后利用小波反变换重构信号,形成增强后的侧扫声呐图像。实测数据验证结果表明:利用该算法对侧扫声呐 ping 信号进行处理,实现了侧扫声呐图像对比度的增强和对噪声的抑制,可以获取较好的图像视觉效果。 相似文献
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介绍了多波束测深系统和侧扫声纳系统的工作原理,通过实例说明了多波束测深系统和侧扫声纳系统在海底目标探测的工作流程,总结出两种探测系统在探测海底目标上的优缺点,说明了多种探测手段的综合应用是海底目标探测技术的发展方向。 相似文献
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小波函数对侧扫声纳图像滤波效果的影响分析 总被引:1,自引:0,他引:1
侧扫声纳技术应用日益广泛,已成为海洋测量的重要工具,而去除噪声处理是对侧扫声纳图像进行正确判读的前提。利用小波函数滤波处理的方法,分别采用Haar、Daubechies、Coiflets、Symlets、Discrete Meyer、Biorthogonal、Reverse Biorthogonal等小波函数与中值滤波函数对侧扫声纳图像进行处理,并以平滑指数和边缘保持指数为评价指标,对滤波效果进行定量比较。试验表明,小波函数可以有效地平滑声纳图像,并能保持其较好的边缘效果。 相似文献
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Dura E. Yan Zhang Xuejun Liao Dobeck G.J. Carin L. 《Oceanic Engineering, IEEE Journal of》2005,30(2):360-371
A data-adaptive algorithm is presented for the selection of the basis functions and training data used in classifier design with application to sensing mine-like targets with a side-scan sonar. Automatic detection of mine-like targets using side-scan sonar imagery is complicated by the variability of the target, clutter, and background signatures. Specifically, the strong dependence of the data on environmental conditions vitiates the assumption that one may perform a priori algorithm training using separate side-scan sonar data collected previously. In this paper, a novel active-learning algorithm is developed based on kernel classifiers with the goal of enhancing detection/classification of mines without requiring an a priori training set. It is assumed that divers and/or unmanned underwater vehicles (UUVs) may be used to determine the binary labels (target/clutter) of a small number of signatures from a given side-scan collection. These sets of signatures and associated labels are then used to train a kernel-based algorithm with which the remaining side-scan signatures are classified. Information-theoretic concepts are used to adaptively construct the form of the kernel classifier and to determine which signatures and associated labels would be most informative in the context of algorithm training. Using measured side-looking sonar data, the authors demonstrate that the number of signatures for which labels are required (via diver/UUV) is often small relative to the total number of potential targets in a given image. This procedure designs the detection/classification algorithm on the observed data itself without requiring a priori training data and also allows adaptation as environmental conditions change. 相似文献
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This document describes the effects of nonideal hydrophone array motion on sonar image quality and derives the allowable motion errors for vehicles carrying side-scan sonar systems. Estimates of the quantity of motion that causes just noticeable sensor performance degradation as well as those that render the sensors useless are derived using two different methods. Using a special resolution target, examples of simulated image distortion resulting from several types of motion are presented. A method for quantitatively measuring the actual image distortion in situ is described 相似文献
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Active sonar detection in shallow water using the Page test 总被引:1,自引:0,他引:1
The use of active sonar in shallow water results in received echoes that may be considerably spread in time compared to the resolution of the transmitted waveform. The duration and structure of the spreading and the time of occurrence of the received echo are unknown without accurate knowledge of the environment and a priori information on the location and reflection properties of the target. A sequential detector based on the Page test is proposed for the detection of time-spread active sonar echoes. The detector also provides estimates of the starting and stopping times of the received echo. This signal segmentation is crucial to allow further processing such as more accurate range and bearing localization, depth localization, or classification. The detector is designed to exploit the time spreading of the received echo and is tuned as a function of range to the expected signal-to-noise ratio (SNR) as determined by the transmitted signal power, transmission loss, approximate target strength, and the estimated noise background level. The theoretical false alarm and detection performance of the proposed detector, the standard Page test, and the conventional thresholded matched filter detector are compared as a function of range, echo duration, SNR, and the mismatch between the actual and assumed SNR. The proposed detector and the standard Page test are seen to perform better than the conventional thresholded matched filter detector as soon as the received echo is minimally spread in time. The use of the proposed detector and the standard Page test in active sonar is illustrated with reverberation data containing target-like echoes from geological features, where it was seen that the proposed detector was able to suppress reverberation generated false alarms that were detected by the standard Page test 相似文献