基于宽带相关处理的水下运动目标检测

对于水下运动目标的检测,宽带相关处理是一种有效的方法.为了实时实现的需要,选择一类多普勒宽容信号为发射信号,给出了单尺度宽带相关处理器作为运动目标检测器.仿真结果证明,该检测器性能优良,且能够实时实现.     

一种基于Mellin变换的水声宽带相关模糊函数的快速算法

提出了一种基于Ｍｅｌｌｉｎ变换的快速算法，其特点是在给定的某一时刻得到不同尺度下的变换结果，算法的运算量与待分析的时廷成正比，而在固定时刻下的运算量为两个２Ｍ点的ＦＦＴ和一次２Ｍ点复数乘法（Ｍ为待分析的尺度的个数）。该算法的优点是实时性好，且适合于水声信号领域尺度跨度小、尺度分析较细的特点，并给出了与直接法、ＣＺＴ法的比较结果。     

宽带与窄带模型下的时延——多普勒滤波比较

1引言在主动声纳探测中,估计目标的径向距离和径向速度是其重要目的之一。通常是通过发射信号与接收信号的拷贝相关来获得模糊度函数[1],实现时延--多普勒滤波的。时延对应着目标的径向距离,多普勒频移对应目标的径向速度。窄带模型是宽带模型的一种弱化,它操作简单,方便运算,但当发射信     

Multiple target detection using split spectrum processing and groupdelay moving entropy

The split spectrum processing technique obtains a frequency-diverse ensemble of narrow-band signals through a filterbank then recombines them nonlinearly to improve target visibility. Although split spectrum processing is an effective method for suppressing grain noise in ultrasonic nondestructive testing, its application was mainly limited to the detection of single targets or multiple targets having similar spectral characteristics. In this paper, the group delay moving entropy technique is introduced primarily to enhance the performance of split spectrum processing in detecting multiple targets which exhibit different spectral characteristics (i.e., variations in target signal center frequency and bandwidth). This is likely to occur in complex, dispersive, and nonhomogeneous media such as composites, layered, and clad materials, etc. The analysis shows that the group delay moving entropy method can be used effectively to select the optimal frequency region for split spectrum processing when detecting such targets. Based on an iterative procedure that combines group delay moving entropy and split spectrum processing, multiple targets can be identified one at a time, and subsequently eliminated by using time domain windows. The removal of the dominant target improves the detection of the remaining weaker targets. Simulation results are presented which demonstrate the feasibility of the multistep split spectrum processing technique for detecting multiple targets in such materials     

基于核滤波器实时运动目标的抗遮挡再跟踪

相关滤波算法是通过模板与检测目标的相似性来确定目标位置,自从将相关滤波概念用于目标跟踪起便一直受到广泛的关注,而核相关滤波算法的提出更是将这一理念推到了一个新的高度。核相关滤波算法以其高速度、高精度以及高鲁棒性的特点迅速成为研究热点,但核相关滤波算法在抗遮挡性能上有着严重的缺陷。本文针对核相关滤波在抗遮挡性能上的缺陷对此算法进行改进,提出了一种融合Sobel边缘二元模式算法的改进KCF算法,通过Sobel边缘二元模式算法加权融合目标特征,然后计算目标的峰值响应强度旁瓣值比检测目标是否丢失,最后将Kalman算法作为目标遮挡后搜索目标的策略。结果显示,本文方法不仅对抗遮挡有较好的鲁棒性,而且能够满足实时要求,准确地对目标进行再跟踪。     

机动小目标的时空联合检测技术

主动声呐信号处理中一般采用匹配滤波和背景均衡等算法检测回波信号,为提高信号的检测性能,还需利用信号与混响和环境噪声在时间、空间上的统计特征差异。文章在对信号的时、空特征算法进行简单描述的基础上,提出了频率能量统计特征和方位能量统计特征,将两种特征检测器的输出进行融合处理构成时、空联合检测器。仿真和试验数据处理结果证明,此方法可有效提高机动小目标在混响及环境噪声中的检测性能。     

对数极坐标图像匹配在目标姿态测量中的应用

本文介绍了一种基于极坐标下图像匹配的方法实现帧与帧之间旋转角度的计算,并可以得到目标轮廓保证可靠跟踪,其坐标变换部分不同于传统的对数极坐标变换,该方法并不进行对笛卡尔坐标系下图像的采样,而是完全保留目标精确的边缘信息用以进行边缘形状匹配.匹配过程分为粗匹配和精匹配两步进行,这种方法主要是利用了极坐标下目标轮廓旋转不变性来实现的.本文还提出了一种双目测量目标旋转角度系统,通过该系统可以完成对空间中的目标在任一旋转平面上的旋转角度.实验证明,该方法计算量小、简单实用、跟踪精度满足要求.     

Constrained quadratic correlation filters for target detection

A method for designing and implementing quadratic correlation filters (QCFs) for shift-invariant target detection in imagery is presented. The QCFs are quadratic classifiers that operate directly on the image data without feature extraction or segmentation. In this sense the QCFs retain the main advantages of conventional linear correlation filters while offering significant improvements in other respects. Not only is more processing required for detection of peaks in the outputs of multiple linear filters but choosing the most suitable among them is an error-prone task. All channels in a QCF work together to optimize the same performance metric and to produce a combined output that leads to considerable simplification of the postprocessing scheme. The QCFs that are developed involve hard constraints on the output of the filter. Inasmuch as this design methodology is indicative of the synthetic discriminant function (SDF) approach for linear filters, the filters that we develop here are referred to as quadratic SDFs (QSDFs). Two methods for designing QSDFs are presented, an efficient architecture for achieving them is discussed, and results from the Moving and Stationary Target Acquisition and Recognition synthetic aperture radar data set are presented.     

Distance-classifier correlation filters for multiclass target recognition

We describe a correlation-based distance-classifier scheme for the recognition and the classification of multiple classes. The underlying theory uses shift-invariant filters to compute distances between the input image and ideal references under an optimum transformation. The original distance-classifier correlation filter was developed for a two-class problem. We introduce a distance-classifier correlation filter that simultaneously considers multiple classes, and we show that the earlier two-class formulation is a special case of the classifier presented. Initial results are presented to demonstrate the discrimination- and distortion-tolerance capabilities of the proposed filter.     

Wavelet processing of images for target detection

This article has as its goal the development and test and evaluation of wavelet-based algorithms for automatically detecting unknown anomalies in two-dimensional images. The general idea behind the work is that the class of wavelet transforms induces a so-called multiresolution analysis (MRA) in image space whereby the image of interest is naturally decomposed into a sequence of images of varying resolution (from coarse to fine resolution) in a computationally efficient manner. The anomaly detection can then be performed sequentially beginning at a coarse scale (low resolution) and proceeding to finer scales as needed. The wavelet representation thus effectively allows the user to zoom in on particular areas of interest and thus detect image anomalies in a very efficient manner. The article includes results from computer simulations testing the proposed approach against a standard energy-detection algorithm for the unknown anomalies embedded in additive Gaussian white noise. © 1996 John Wiley & Sons, Inc.     

一种用于水声运动目标成像的空间散射模型

水声成像过程中为了分析所接收的运动目标回波、理解接收信号的形成机理,提出了一种用于该情况的空间散射模型,并利用此模型仿真了"T"型阵成像声呐接收的回波信号。对信号的分析说明了空间散射模型的正确性。以空间散射模型为基础,利用傅里叶变换波束形成算法对不同条件下的球体目标进行了水声成像,并分析了成像性能。性能分析说明了水声目标大小、距离等因素对成像的影响情况,还特别强调了在运动情况下目标的成像情况。以上工作完成了对"T"型阵水声成像过程的模拟,为成像过程回波信号研究和成像声呐研制提供了理论基础和仿真手段。     

Highly cited researchers: a moving target

Scientometrics - Highly cited researchers are a category of researchers defined by scientometric rules relating to counts of citations to their scholarly articles. The designation often refers to...