基于导航雷达海面回波图像去噪研究

根据海面X波段雷达回波图像数据的时空特点,提出了一种新的去噪方法。该方法利用线检测对雷达图像中的射线状噪声进行分离,然后针对这种特殊的噪声形式提出一种阈值分割的方法,最后在极坐标下针对噪声点进行插值修复。实验表明,与传统的均值滤波和中值滤波等方法相比,新方法无论在主观视觉还是信噪比方面,都有了一定改进,图像保留了更多的细节信息,具有较好的去噪效果。     

一种基于平稳小波变换的海底管线边缘检测方法

海底影像存在着对比度低、噪声污染严重、图像质量差等问题，采用传统算子的海底管线边缘图像中含有大量的无用和断裂边缘信息。文中将多尺度边缘检测和匹配跟踪相结合，提出利用平稳小波变换的海底管线边缘检测方法；在提取边缘的同时利用匹配跟踪手段对噪声干扰进行抑制，提高图像目标边缘检测质量。通过对海底管线和测试图像边缘检测实验表明，文中所提出的方法在抑制图像噪声的干扰、提高水下目标边缘完整性方面明显优于传统的边缘提取算子，证明该算法的有效性。     

两步SVD在极低频电场透地通信中的应用

在极低频电场透地通信中,通常同步采集 2 个互相垂直的电场水平分量。当收发距较大时,采集获得的电场数据往往具有较小的信噪比,接收信号严重受到噪声的干扰,所传递的信息不清晰甚至错误。因此,当在极低频电场透地通信数据信噪比较低时,需要对其进行滤波处理,压制噪声成分,提高数据的质量。提出了一种两步奇异值分解滤波方法,该方法第 1 步压制极低频电场透地通信数据中较强的噪声,第 2 步在第 1 步的基础上继续压制数据中残留的噪声。将该方法应用到某湖上极低频电场透地通信数据中,处理结果表明,该方法可以有效改善各接收点电场数据的质量,极大地提高了数据的信噪比。     

基于MRF与引导滤波的声纳图像去噪方法

声纳具有对大范围水下场景探测的能力,一直以来都是水下设备感知外界环境的重要手段,但由于声纳图像分辨率低,海洋环境噪声干扰较为复杂,所以在诸多方面的应用都受到了限制。文中提出了一种基于马尔可夫随机场和引导滤波的声纳图像去噪与增强方法,使用马尔可夫随机场对声纳图像进行预分割,然后采用中值滤波方法对原始图像进行简单滤波处理,最后将该图像作为引导图像对马尔可夫随机场(Markov Random Field,MRF)分割后的图像进行引导滤波实现了对声纳图像的去噪与增强。该方法有效地去除了背景和影子内的噪声,对目标区域内部噪声起到了很好的抑制作用,消除了MRF分割产生的伪轮廓效应,具有较好的边界保持和增强效果。     

基于LOG算子的侧扫声呐图像水下小目标检测算法研究

针对侧扫声呐图像噪声干扰严重、分辨率低、目标轮廓模糊等特点,提出了一种基于LOG算子的侧扫声呐图像水下小目标检测算法。首先,根据侧扫声呐图像中水下小目标成像特点,对声呐图像进行滤波及聚类分割,大幅降低图像中噪声;然后,采用斑点检测思想,提取侧扫声呐图像中疑似目标区域;最后,基于自动阈值分割算法对声呐图像进行分割,获取目标区域二值图像,使用二阶矩估计目标尺度,剔除虚假目标,最终实现水下小目标准确检测。实验结果表明：该方法计算速度快、检测成功率高,对侧扫声呐图像中的水下小目标具有良好的检测效果。     

基于非锐化掩模引导滤波的水下图像细节增强算法研究

针对水下图像对比度偏低,细节模糊的问题,本文提出基于非锐化掩模引导滤波的细节增强方法。首先由原始图像做引导图进行滤波得到细节层图像,并对细节层使用噪声检测的中值滤波去除斑点噪声;然后对原始图像进行基于均值滤波的非锐化掩模,得到锐化图像,并将锐化图像作为引导图对原始图像进行引导滤波,获取基础层图像;最后将滤波后的细节层进行增益后与引导滤波获取的基础层进行叠加,达到增强水下图像细节的目的。并通过信息熵、局部对比度和平均梯度3种客观评价指标对图像处理结果进行了对比分析,主观和客观测试结果表明,本文采用的算法能够有效提高图像对比度以及增强细节信息,有利于提高水下图像资料解释的准确性。     

一种机载SAR非周期性线状噪声去除方法

由于受雷达系统本身、飞行姿态、大气扰动等多种因素的影响,机载SAR图像中存在大量的非周期性线状噪声,限制了数据的后续应用。针对利用机载SAR图像进行海上绿潮探测的应用目的,本文在对机载SAR图像中非周期性线状噪声进行统计特征分析的基础上,提出了一种机载SAR图像非周期性线性噪声去除方法,并与均值滤波、高斯低通滤波、增强Lee滤波、增强Frost滤波、Gamma滤波、小波分析滤波、傅里叶变化滤波等多种常用滤波算法进行了对比,验证了该方法的有效性。结果表明,与常用滤波算法相比,我们算法的噪声去除率最高,且边缘特征清晰;图像经滤波后,噪声区灰度值与海水相近,与绿潮的对比显著增大,提高了绿潮和海水的区分能力。     

基于纹理特征的围填海SAR图像分水岭分割方法

本文提出了一种基于纹理特征的围填海SAR图像分水岭分割方法,首先对机载MiniSAR图像进行灰度共生矩阵纹理滤波,获得纹理特征图像,再对纹理特征图像进行分水岭算法分割,将获得的形态学重建图像进行门限阈值分割,得到最后的二值化分割结果。该方法一方面通过调整灰度共生矩阵纹理滤波的窗口大小,抑制了斑点噪声的影响;另一方面,利用分水岭算法对边缘模糊杂乱图像的优势,提高了围填海信息提取的准确性。实验结果表明,本方法对高分辨率SAR图像围填海监测图像的分割效果良好。     

基于K-means聚类与数学形态学的侧扫声呐图像目标轮廓自动提取方法

针对侧扫声呐图像斑点噪声强、背景海底散射干扰严重,海底目标轮廓自动提取困难的问题,提出了一种基于K-means聚类与数学形态学相结合的海底目标轮廓自动提取算法。为克服噪声干扰,该算法首先利用中值滤波去除侧扫声呐图像中的强斑点噪声;然后采用K-means聚类算法对侧扫声呐灰度图像进行分割,并二值化,除去大部分海底背景噪声,初步提取出目标;接着利用数学形态学运算去除提取结果中的孤立噪点,并填充目标内部孔洞,得到连续化、圆滑的目标边缘;最后对处理后的侧扫声呐图像进行边缘检测,提取出目标轮廓。实验结果表明:该算法思想简单易行,具有很强的克服背景噪声的能力,自动提取的目标轮廓连续性较好,结果准确可靠。目前,在侧扫声呐图像目标轮廓提取过程中,主要采用人工方式,自动性较差,效率较低。本文算法可以实现目标轮廓的自动提取,提高效率,具有较强的实用价值。     

基于方向分解的高频地波雷达射频干扰抑制

本文根据射频干扰的来源和特性构造出其基本的理论模型,并结合数据处理流程从理论上分析了射频干扰在方位-距离-多普勒域的特性,得出了在不同距离上,射频干扰具有强相关性;而在不同方位上,射频干扰具有同频但不同幅的特点。基于此分析,在实际工程应用中,分析常规射频干扰抑制方法的不足,为减少干扰抑制过程对目标信息的影响,提出了包括回波信号方向分解、射频干扰估计与抑制、幅值合成三个步骤。通过仿真和实测数据对算法进行了验证,并与常规抑制方法进行对比,结果显示该方法对射频干扰具有良好的抑制效果,有效提高了被射频干扰覆盖的目标点的信干比。     

Radar-based collision avoidance for unmanned surface vehicles

Unmanned surface vehicles (USVs) have become a focus of research because of their extensive applications. To ensure safety and reliability and to perform complex tasks autonomously, USVs are required to possess accurate perception of the environment and effective collision avoidance capabilities. To achieve these, investigation into realtime marine radar target detection and autonomous collision avoidance technologies is required, aiming at solving the problems of noise jamming, uneven brightness, target loss, and blind areas in marine radar images. These technologies should also satisfy the requirements of real-time and reliability related to high navigation speeds of USVs. Therefore, this study developed an embedded collision avoidance system based on the marine radar, investigated a highly real-time target detection method which contains adaptive smoothing algorithm and robust segmentation algorithm, developed a stable and reliable dynamic local environment model to ensure the safety of USV navigation, and constructed a collision avoidance algorithm based on velocity obstacle (V-obstacle) which adjusts the USV’s heading and speed in real-time. Sea trials results in multi-obstacle avoidance firstly demonstrate the effectiveness and efficiency of the proposed avoidance system, and then verify its great adaptability and relative stability when a USV sailing in a real and complex marine environment. The obtained results will improve the intelligent level of USV and guarantee the safety of USV independent sailing.     

降雨条件下的导航X波段雷达海浪参数反演算法研究

X波段的电磁波受降雨影响容易产生衰减,这导致导航X波段雷达在降雨时无法用于海浪观测。本文提出了一种新的降低降雨影响的算法来反演海浪参数。首先,对X波段雷达图像做主成分分析,获得波浪变化的主成分,利用一维傅里叶变换得到波数谱,对其滤波减小降雨对雷达图像的影响;然后,选取JONSWAP(Joint North Sea Wave Project)谱作为理论谱,建立以观测谱与理论谱的最小化差异为目标函数的模型,求解该模型估算海浪的有效波高。与浮标测量的有效波高相比,该方法反演的有效波高的均方根误差是0.23 m,证明了该方法的可行性。     

X波段导航雷达浪高实时测量研究

针对舰船对浪高实时测量的需要,提出了基于X波段导航雷达浪高实时测量的方案。介绍X波段导航雷达浪高测量原理,建立基于X波段导航雷达浪高实时测量的数学模型。通过某海域实测采集的雷达图像,经过数学模型反演得出浪高实时数据,并与采用浮标传感器实时测量的浪高数据进行对比,发现X波段导航雷达与浮标传感器测得的浪高数据有近一致的线性关系,标准差也较小。从一定程度上为舰船浪高测量提供一种可行性方法。     

Optical flow-based method to estimate internal wave parameters from X-band marine radar images

The velocity and direction of internal waves (IWs) are important parameters of the ocean, however, traditional observation methods can only obtain the average parameters of IWs for a single location or large area. Herein, a new method based on optical flow is proposed to derive the phase velocity vectors of IWs from X-band marine radar images. First, the X-band marine radar image sequence is averaged, and ramp correction is used to reduce the attenuation of gray values with increasing radial range. Second, the average propagation direction of the IWs is determined using the two-dimensional Fourier transform of the radar images; two radial profiles along this direction are selected from two adjacent radar images; and then, the average phase velocity of the IWs is estimated from these radial profiles. Third, the averaged radar images are processed via histogram equalization and binarization to reduce the influence of noise on the radar images. Fourth, a weighting factor is determined using the average phase velocity of a reference point; the phase velocities on the wave crest of the IWs are subsequently estimated via the optical flow method. Finally, the proposed method is validated using X-band marine radar image sequences observed on an oil platform in the South China Sea, and the error of the phase velocity is calculated to be 0.000 3–0.073 8 m/s. The application conditions of the proposed method are also discussed using two different types of IW packets.     

灰度共生矩阵纹理特征对SAR海冰漂移监测的增强性能研究

海冰漂移监测对气候变化分析、船只航行、海上石油平台等海上活动安全作业具有重要意义。当前主流的SAR海冰漂移监测方法多是基于SAR灰度图开展的,其受噪声、环境等因素的影响较大,导致其在海冰漂移探测时,特征失配率高,匹配正确率低。针对这一问题,本文尝试利用SAR海冰纹理特征来增强海冰漂移探测性能。首先对比分析了8种纹理特征对海冰漂移探测中特征匹配的增强性能,筛选出能够有效增强特征匹配性能的最优纹理特征;其次进一步分析了海冰类型、入射角和分辨率对基于纹理特征的海冰漂移探测性能增强的影响。实验结果表明,均值是最优的纹理特征,与SAR强度图相比,特征匹配正确率提高了约7%。     

A speckle noise suppression method based on surface waves investigation and monitoring data

The internal energy distribution of waves can be described using ocean-wave spectra. In many ways, obtaining wave spectra on a global scale is critical. Surface waves investigation and monitoring onboard the Chinese-French oceanography satellite is the first space-borne instrument for detecting wave spectra specially, which was launched on October 29, 2018. It can avoid the shortage of synthetic aperture radar detection results while still having some problems, especially with the effects of spe...     

GNSS-R观测下的海面飓风风速反演

利用全球导航卫星系统在地球表面的反射信号（GNSS-R）进行海面风速反演已经被广泛研究并作为一种重要的遥感手段。目前,该L波段微波信号的相关功率已可以在多普勒频率和时延码片空间进行多普勒时延图像的成像。由于该图像的图像特征与海面粗糙度有较高的相关性,因此能够用来进行海面风场反演。然而,对于该遥感手段而言,其双基雷达前向散射截面（BRCS）理论上与海面粗糙度有更高的相关性,如同目前合成孔径雷达使用后向雷达散射截面而非相关功率。所以,本文通过改进已有的GNSS-R的双基雷达散射截面方程,代替相关功率在多普勒时延空间进行成像,得出了与海面粗糙度相关的双基雷达散射截面图像（BRCS map）。基于该图像,本文提出了三种与其形状特征相关的观测量,通过2005年Dennis飓风GNSS-R机载数据生成的16000多幅图像进行地球物理模式函数建模并与经典的一维时延波形匹配方法得出结果进行对比分析,得出更为精确的风速反演结果。     

基于光流法的X波段雷达浪向反演研究

浪向代表着海浪传播方向,它是海上交通安全以及海岸资源管理的重要海洋环境参数之一。本文针对X波段测波雷达对海杂波的连续成像,提出了一种基于光流法的海浪传播方向反演新方法。该方法利用X波段测波雷达接收的海面回波图像序列直接进行光流运动估计,将得到的每个像素点的运动矢量进行加权平均,最后得到实际的海浪传播方向。与传统基于频域的X波段测波雷达浪向反演方法相比,本文提出的方法直接从时域来进行回波信号处理,无需提前得到调制传递函数以及精确的海流,减少了由于海流估算的不准确以及调制传递函数选取的误差而给雷达浪向反演带来的影响。同时,该方法简单高效,占用资源少,将其应用至仿真雷达回波以及现场实测数据来进行浪向反演,反演得到的浪向与仿真设定浪向值以及浮标实时观测浪向结果都有很好的吻合度,变化趋势也完全一致,进而验证了该方法的有效性以及准确性。     

Applying chaos to radar detection in an ocean environment: anexperimental study

Ship navigation through ice-infested waters is a problem of deep concern to the oil exploration industry of Northern countries. Conventional marine radars do not perform satisfactorily in detecting small targets such as small pieces of iceberg. This paper reports a new method for detection in an ocean environment. The approach is based on the recent observation that sea clutter, radar echoes from the sea surface, can be modeled as a nonlinear deterministic dynamical system which can be used as an alternative to the conventional stochastic process. Based on this model, detection in sea clutter is considered as dynamical system classification instead of statistical hypothesis testing. Two dynamical detection methods are proposed. The first one uses a dynamical invariant called the attractor dimension to distinguish a target from a pure clutter process. The second approach tries to detect the existence of a target by observing the “difference” of the motion of the target and the clutter process. To show the validity of the idea of dynamical detection in sea clutter, real sea clutter, and target data were used in this study     

A method minimizing the correlation properties of a noise field andimproving detection of signals embedded in anisotropic noise

This paper deals with the development of a processing technique that improves the signal-to-noise ratio (SNR) at the single sensor for a received signal that is embedded in a partially correlated noise field. The approach of this study is unique in that the noise is treated as being non-white and partially correlated. The concept of the proposed development is based on the time interval over which the temporal coherence or correlation properties of a noise field are defined. For narrowband signals, the associated temporal coherence period is much longer than the correlation time interval of the anisotropic noise field. Thus, a coherent integration of discontinuous segments of received signals will enhance the SNR at the single sensor by lowering the correlation properties of the associated non-white noise. Reconstruction of the narrow-band signal time series, with improved SNR at the sensor will allow the use of the existing high resolution techniques to be utilized more effectively by lowering their threshold values in order to detect very weak signals. The intention here is to integrate the characteristics of the real anisotropic noise field during the preliminary processing stages of the received signals by an array of sensors. Simulations show that the proposed method can be integrated in the signal processing functionality of sonar and radar systems