共查询到19条相似文献，搜索用时 406 毫秒
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针对海杂波严重制约雷达目标探测性能的问题,本文提出了一种基于复相关相位斜率特征的海面弱小目标检测方法。本文通过研究海杂波复数域下的时间自相关特性,发现复相关系数相位信息呈线性分布,由此提出了一种新颖的统计特征:复相关相位斜率。研究表明,复相关相位斜率特征可显著提高雷达数据的信杂比。经过不同极化方式下的海杂波数据验证表明,本文提出的目标检测方法性能优于传统基于分形特征的Hurst指数检测器,使用本文的方法可以有效识别海面弱小目标。 相似文献
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基于相关矩阵特征向量的目标分解将地物回波复杂的散射过程分解成相互独立的三种单一散射分量:单向散射、双向散射和交叉散射,分别对应各自的目标相关矩阵。目标分解技术降低了散射回波之间的相关性,有利于分析地物散射机理,有助于提高分类精度。对荷兰F levoland地区全极化数据进行分解,经过试验和相关性分析,选用7种数据形成多参数数据组合,对其进行最大似然监督分类,同时进行常规三种极化加相位差的分类和基于复W ishart分布的最大似然分类,逐像元计算混淆矩阵,分析对比三种分类结果的精度,试验表明:相对于常规数据组合分类,基于复W ishart分布的监督分类可以小幅度提高分类精度,而利用目标分解得到多参数组合数据进行分类则有大幅度的提高。 相似文献
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海底峡谷是陆源沉积物向深海运移的主要通道,也是陆架/陆坡区重要的地貌单元。随着多波束测深技术的发展,如何快速而准确地从海量数据中识别并提取海底峡谷的特征要素,是一个亟待解决的重要热点问题。文中根据海底峡谷谷底下切、谷壁高而陡等地形特征,基于水文分析法和坡度分析等原理,通过ArcGIS中的数据建模工具建立了一种从数字高程模型(DEM)数据快速识别和提取海底峡谷特征要素的方法。以南海北部陆坡神狐峡谷区为例进行算例分析,结果表明,该方法在快速了解海底峡谷的发育位置和特征要素等方面是可行的,并可以获得峡谷头尾部水深、轴线长度、峡谷范围等特征信息。为获得该方法适用于研究区的最优参数组,文中讨论分析了峡谷形态、重分类阈值及数据分辨率等影响峡谷识别的因素。结果分析表明,峡谷形态会在一定程度上影响识别结果的准确性,但不影响对峡谷的总体了解;零值汇流累积量重分类阈值和DEM数据的空间分辨率是影响峡谷识别结果准确度的两个重要因素,在神狐峡谷群区,空间分辨率200 m且重分类阈值0.4时,海底峡谷识别和特征要素提取效果最佳。 相似文献
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针对水声数据的特征中含有大量冗余、不相关和噪声特征，导致水声目标识别正确率降低的问题，提出了一种新的水下目标特征选择方法——基于弹性网回归的无监督特征选择算法(Unsupervised fea- ture selection algorithm based on elastic-net regression，UFSER)。 该算法利用谱回归得到高维水声数据和其低维表示之间的回归系数矩阵，并且在回归框架中加入弹性网惩罚项优化求解回归系数矩阵；最后，对回归系数矩阵进行稀疏化从而对特征的分类性能进行评价。 使用实测水声数据集和 UCI 声呐数据集进行特征选择和 SVM 分类实验。 实验结果表明：在特征数目分别减少 60.6%和 60%的情况下，分类识别正确率较特征选择前提升了 1.05%和 6.6%。 相似文献
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雷达回波谱中的噪声和目标回波会对二阶谱的提取造成困难。基于地波雷达海面回波谱特性,提出了一种采用距离-多普勒谱(RD谱)轮廓线结合一阶和二阶谱特点的二阶谱提取方法。此方法可以通过计算机自动实现对二阶谱的提取,有利于大批数据的分析和工程化系统的实时处理。利用该方法对典型实测雷达回波数据进行了处理和分析。结果表明,RD谱轮廓线能够反映一阶谱和二阶谱的特征,并且不易受噪声和目标的影响;从RD谱轮廓线获得的二阶谱分界点,可以为一维多普勒回波谱中的二阶谱提取提供参考,能够较好地避免由于目标和噪声的影响而导致的二阶谱边界误判问题,准确地分离二阶谱。 相似文献
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蓝绿激光探测水下目标的脉冲传输统计模拟及回波特性初步研究 总被引：1，自引：0，他引：1
文中给出了用蓝绿激光脉冲探测水下目标时的回波特性初步研究结果,所用的方法是对激光脉冲在海水中的传输作蒙特卡洛统计模拟.研究表明,位于目标上方空中的接收机收到的回波脉冲功率随着目标物水深的增加而呈指数下降,但随目标物反射的增加而增加.水体对激光的多次散射增强了回波脉冲功率,但也使脉冲明显变宽. 相似文献
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Pinto M.A. Bellettini A. Hollett R. Tesei A. 《Oceanic Engineering, IEEE Journal of》2002,27(3):484-494
Results from two field experiments aimed at investigating the detection and classification of buried targets are presented. In both experiments a 2-16-kHz parametric source was used. In the first experiment, the source was used in combination with a 12-m horizontal line array and in the second with a 1.4-m vertical line array which was displaced horizontally along an underwater rail to form a 10 m /spl times/ 1.4 m two-dimensional synthetic aperture sonar (SAS). To increase the SAS integration time, the parametric source was electronically scanned in azimuth during the displacement along the rail, as in spotlight mode. It is shown that both arrays allow important signal-to-reverberation gains, enhancing the detection of sub-bottom echoes. A new, environmentally adaptive, matched filter which further improves the signal to reverberation ratio while allowing discrimination between proud and buried targets is presented and validated experimentally. The use of resonant scattering for target classification of buried objects is discussed, in the particular case of spherical shells. 相似文献
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Canonical correlation analysis is employed as a multiaspect feature extraction method for underwater target classification. The method exploits linear dependence or coherence between two consecutive sonar returns, at different aspect angles. This is accomplished by extracting the dominant canonical correlations between the two sonar returns and using them as features for classifying mine-like objects from nonmine-like objects. The experimental results on a wideband acoustic backscattered data set, which contains sonar returns from several mine-like and nonmine-like objects in two different environmental conditions, show the promise of canonical correlation features for mine-like versus nonmine-like discrimination. The results also reveal that in a fixed bottom condition, canonical correlation features are relatively invariant to changes in aspect angle. 相似文献
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De Yao Azimi-Sadjadi M.R. Jamshidi A.A. Dobeck G.J. 《Oceanic Engineering, IEEE Journal of》2002,27(3):619-627
The problem of classifying underwater targets is addressed in this paper. The proposed classification system consists of several subsystems including preprocessing, subband decomposition using wavelet packets, linear predictive coding, feature selection and neural network classifier. A multi-aspect fusion system is introduced to further improve the classification accuracy. The classification performance of the overall system is demonstrated and benchmarked on two different acoustic backscattered data sets with 40- and 80-kHz bandwidth. A comprehensive study is then carried out to compare the classification performance using these data sets in terms of the receiver operating curves, error locations, and generalization and robustness on a large set of noisy data. Additionally, the importance of different frequency bands for the wideband 80-kHz data is also investigated. For the wideband data, a subband fusion mechanism is introduced which offers very promising results. 相似文献
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In this paper, we experimentally perform the measurement of the backscattered light intensity from the underwater targets with different size. We develop a simple system, which can easily measure the intensity of the backscattered light, after the laser is scattered at the target underwater. We find that, the signal period is related to the particle size, and the stability of the intensity (standard deviation) varies linearly with changing the particle size. After the calibration, our system can be used to precisely determine the particle size of arbitrary targets. Our method could open a new opportunity for the future underwater detection using femtosecond pulse laser. 相似文献
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Shape classification of the 40-Hz waveforms obtained by the recently launched AltiKa satellite has been attempted in the paper. Since retracking algorithms suitable for altimeter return echoes based on Brown model are not applicable for the echoes from coastal ocean, specific algorithms are to be devised for such echoes. In the coastal ocean, waveforms display a wide variety of shapes due to varying coastline geometry, and topography. Hence, a proper classification strategy is required for classifying the waveforms into various categories so that suitable retracker could be applied to each category for retrieving the oceanic parameters. The algorithm consists of three steps: feature selection, linear discriminant analysis, and Bayesian classifier. The classification algorithm has been applied to the waveforms in the close proximity of Gujarat coast. Independent validation has been done near the eastern coast of India. Confusion matrices obtained for both the coasts are quite encouraging. Individual examples of classification have been provided for the purpose of illustration. 相似文献
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It has long been known that the statistical properties of acoustic echoes from individual fish can have non-Rayleigh characteristics. The statistical properties of echoes from zooplankton are generally less understood. In this study, echoes from individual fish and zooplankton from a series of laboratory measurements from the past decade are investigated. In the experiments, acoustic echoes from various individual organisms were measured over a wide range of frequencies and orientations, typically in 1/spl deg/-3/spl deg/ increments. In the analysis in this paper, the echoes from most of those measurements are grouped according to ranges of orientation, which correspond to typical orientation distributions of these organisms in the natural ocean environment. This grouping provides a distribution of echo values for each range of orientation. This approach, in essence, emulates a field experiment whereby distributions of echoes would be recorded for different distributions of orientations of the organisms. For both the fish and zooplankton data, there are conditions under which the echoes are strongly non-Rayleigh distributed. In some cases, the distribution is quantitatively connected to the physics of the scattering process while, in other cases, the connection is described qualitatively. Exploitation of the animal-specific statistics for classification purposes is suggested. 相似文献
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随着对水下目标特性研究的深入和声学探测技术的发展,基于单模态的阵列式信息融合或基于空间信息的分布式信息融合的水下目标识别方法研究已有一定成果,但针对复杂海况导致单一物理场或单一融合层次的系统识别性能提高有限等方面影响的水下目标识别方法研究还有所不足,因此,开展基于多模态深度融合模型的水下目标识别方法研究可利用模态互补,共享信息而提升识别率。文中在国内外研究基础上,深入研究了基于到达时差法和多模态方法组合的检测方法,初步形成了基于水声环境空间中多模态深度融合模型的识别框架,开展了海洋中典型自然与人为事件的信号分析与特征提取,并在此基础上,设计新型基于海底基站的被动识别系统。该系统同步记录和由位置等组成的时间序列标记声、磁和压数据,可实现高精度、高分辨率的识别。本研究可满足未来海洋观测对高性能水下目标探测、定位和跟踪系统的迫切需要,为海洋安全监管、海洋突发事件应急响应等领域提供新的技术手段和科学参考。 相似文献
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In this paper, a hierarchical system, in which each level is composed by a neural-based classifier, is proposed to recognize objects in underwater images. The system has been designed to help an autonomous underwater vehicle in sea-bottom survey operations, like pipeline inspections. The input image is divided into square regions (macro-pixels) and a neural tree is used to classify each region into different object classes (pipeline, sea-bottom, or anodes). Each macro-pixel is then analyzed according to some geometric and environment constraints: macro-pixels with doubt classification are divided into four parts and re-classified. The process is iterated until the desired accuracy is reached. Experimental results, which have been performed on a large set of real underwater images acquired in different sea environments, demonstrate the robustness and the accuracy of the proposed system 相似文献