基于AIS距离-多普勒投影的地波雷达CFAR检测验证方法

恒虚警(CFAR)检测是地波雷达船只目标探测的主要方法。目前基于船舶自动识别系统(AIS)信息的CFAR检测验证方法是一种间接验证方式,容易受地波雷达系统测向误差的影响,且不具备对错检与漏检目标的分析能力。本文提出了一种基于AIS信息的评价地波雷达CFAR检测结果的直接验证方法。该方法将有效的AIS信息转换到地波雷达的距离-多普勒谱中,通过在该谱中AIS信息与CFAR检测结果的关联分析,实现CFAR检测结果的直接评价。论文首先给出了方法的原理和处理流程,然后利用实测数据给出了该方法在CFAR检测结果评价中的实际应用,验证了方法有效性,而且该方法也为低可观测目标的CFAR检测提供了参数优化调整的依据。     

A synthetic aperture radar sea surface distribution estimation by n-order Bézier curve and its application in ship detection

To dates,most ship detection approaches for single-pol synthetic aperture radar(SAR) imagery try to ensure a constant false-alarm rate(CFAR).A high performance ship detector relies on two key components:an accurate estimation to a sea surface distribution and a fine designed CFAR algorithm.First,a novel nonparametric sea surface distribution estimation method is developed based on n-order Bézier curve.To estimate the sea surface distribution using n-order Bézier curve,an explicit analytical solution is derived based on a least square optimization,and the optimal selection also is presented to two essential parameters,the order n of Bézier curve and the number m of sample points.Next,to validate the ship detection performance of the estimated sea surface distribution,the estimated sea surface distribution by n-order Bézier curve is combined with a cell averaging CFAR(CA-CFAR).To eliminate the possible interfering ship targets in background window,an improved automatic censoring method is applied.Comprehensive experiments prove that in terms of sea surface estimation performance,the proposed method is as good as a traditional nonparametric Parzen window kernel method,and in most cases,outperforms two widely used parametric methods,K and G0 models.In terms of computation speed,a major advantage of the proposed estimation method is the time consuming only depended on the number m of sample points while independent of imagery size,which makes it can achieve a significant speed improvement to the Parzen window kernel method,and in some cases,it is even faster than two parametric methods.In terms of ship detection performance,the experiments show that the ship detector which constructed by the proposed sea surface distribution model and the given CA-CFAR algorithm has wide adaptability to different SAR sensors,resolutions and sea surface homogeneities and obtains a leading performance on the test dataset.     

一种新的用于极化SAR图像船只检测的散射相似性测度

本文提出了一种新的用于极化合成孔径雷达（SAR）海上船只目标检测的测度。首先利用散射相似性参数研究船只与海杂波散射机制的差异。基于这些差异,提出了一种新的船只检测测度,该测度能够有效区分船只目标和海杂波。然后提出了利用核密度估计（KDE）方法对该测度进行建模的方法。基于统计模型,实现了自适应恒虚警率（CFAR）的检测方案。本文利用多景C波段RADARSAT-2极化SAR（Pol-SAR）数据上进行实验,系统分析了所提出测度的海杂波拟合性能与船只检测性能,并与两个经典的极化测度进行了比较,实验和比较结果证明了所提的测度的可行性。     

基于虚警函数的侧扫声纳水下目标实时检测方法

研究了侧扫声纳系统进行水下目标探测过程中目标信号的检测问题。通过分析海底回波信号的统计模型及其参数的估计,讨论了目标信号对统计模型拟合的影响规律,提出了侧扫声纳回波信号虚警函数和虚警率的概念,及其对Ping信号中目标信号的检测方法。算例结果表明,回波信号的三种分布模型中K分布拟合程度最优,在相同虚警率的条件下,基于K分布的虚警函数目标检测率最高。该法可为侧扫声纳回波信号中目标的实时报警提供技术支撑。     

Harbor surveillance radar detection performance

System requirements for harbor surveillance radars are reviewed. Experimental sea clutter data are presented and shown to be closely matched by a log-normal clutter model. Characteristics and parameters of the log-normal clutter model are described. Detection performance against a steady target in a log-normal clutter background, using logarithmic receivers, is provided. A log-normal target model is described. Detection curves for log-normal fluctuating targets in log-normal clutter are developed. A Constant False Alarm Rate (CFAR) processor that adaptively functions in log-normal clutter is described. CFAR detection performance is derived and presented in the form of CFAR loss curves.     

高频地波雷达海杂波背景下的船只目标检测研究进展

针对海杂波对高频地波雷达目标检测的干扰问题,分目标处于海杂波谱区之内和之外两种情况综述了海杂波背景下的目标检测方法。对于海杂波内目标检测的难题,介绍了一种基于现场海态同步观测信息的检测新思路以及初步验证结果。对国内外相关研究进展的归纳总结和新思路的提出,为提出更加有效的海杂波干扰下的目标检测方法提供了重要的参考。     

高频地波雷达海杂波背景下的船只目标检测研究进展

针对高频地波雷达目标检测的海杂波干扰问题,分为目标处于海杂波谱区之内和之外两种情况综述了海杂波背景下的目标检测方法。对于海杂波谱区内目标检测的难题,介绍了一种基于现场海态同步观测信息的检测新思路以及初步验证结果。对国内外相关研究进展的归纳总结和新思路的提出,为深入研究相关方法,解决海杂波干扰下的目标检测问题提供了重要的参考。     

Mitigation techniques for non-Gaussian sea clutter

This paper deals with the problem of coherent radar detection of targets embedded in clutter modeled as a compound-Gaussian process. We first provide a survey on clutter mitigation techniques with a particular emphasis on adaptive detection schemes ensuring the constant false-alarm rate (CFAR) property with respect to all of the clutter parameters. Thus, we propose a novel decision rule based on a recursive covariance estimator, which exploits the persymmetry property of the clutter covariance matrix. Remarkably, the devised receiver is fully CFAR in that its threshold can be set independently of the clutter distribution as well as of its covariance, even if the environment is highly heterogeneous; namely, the disturbance distributional parameters vary from cell to cell. At the analysis stage, we compare the performance of the novel detector with some classical radar receivers such as that of Kelly and the adaptive matched filter both in the presence of simulated as well as on real radar data, which statistical analysis has shown to be compatible with the compound-Gaussian model. The results show that the new receiving structure generally provides higher detection performance than the others and, for a fluctuating target, it uniformly outperforms the counterparts. We also provide a discussion on the CFAR behavior of the analyzed receivers as well as on their computational complexity.     

基于模型相似度拟合的海杂波统计方法

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。     

基于视觉显著性的高分辨率遥感影像舰船检测

通过研究、分析现有基于遥感影像的舰船检测算法,提出了基于Itti视觉显著度模型改进的高分辨率遥感影像海面舰船检测方法,该方法利用海面舰船相对于海面背景信息视觉关注高的特点,参考视觉显著度模型计算原理,对高分辨率遥感影像中的颜色、亮度、方向、纹理等特征进行有效提取,然后利用归一化方法将不同特征融合,形成有利于舰船目标提取得视觉显著度图,最后对生成的视觉显著度图进行阈值分割和精细化处理获得最终的舰船检测结果。与传统舰船检测算法相比,本文算法能够有效检测复杂海面背景下的舰船目标,减少了单一特征变化对检测精度的影响,提高了检测准确率,具有较好的抗噪性和较强的鲁棒性。     

Fast Double Selectivity Index-CFAR Detection Method for the Multi-Beam Echo Sounder

Abstract

Seafloor terrain and water column target detection is of great significance in marine surveys. However, the complex clutter environment can dramatically affect the detection performance of a multi-beam echo sounder. To simultaneously and robustly detect the seafloor terrains and water column targets, this paper proposes a fast two-dimensional double selectivity index-constant false alarm rate (DSI-CFAR) detection method. A two-dimensional cross sliding window, which includes reference cells and guard cells, is used in this paper. The proposed method improves the detection performance by using the appropriate clutter power level estimation strategies in different directions. An exponential model is accurately built by fitting various distributions, so the DSI-CFAR detection performance is greatly ameliorated. To reduce the computational load of the method, this paper uses a fast algorithm based on the global threshold. The region of interest (ROI) is selected by the preset global threshold, and the DSI-CFAR detector is only performed in the region of interest, which significantly reduces the number of pixels that must be calculated. In this paper, the measured results of different sliding windows and CFAR detection methods validate the basic performance of the proposed method.     

基于水声环境空间中多模态深度融合模型的目标识别方法研究

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。     

卫星视频舰船目标检测方法

舰船目标检测是进行海上目标监管,保障海上权益的重要手段.本文在SSD(single shot multibox detector)算法的基础上,利用残差网络(ResNet,residual network)作为骨干网络构建SSD模型,将改进后的SSD算法应用于卫星视频舰船目标检测,该算法采用残差连接替换原本的级联方式,...     

A Simple Empirical Formula for Predicting the Ultimate Strength of Ship Plates with Elastically Restrained Edges in Axial Compression

An investigation is conducted on the static ultimate limit state assessment of ship hull plates with elastically restrained edges subjected to axial compression. Both material and geometric non-linearities were considered in finite element(FE) analysis. The initial geometric imperfection of the plate was considered, while the residual stress introduced by welding was not considered. The ultimate strength of simply supported ship hull plates compared well with the existing empirical formula to validate the correctness of the applied boundary conditions, initial imperfection and mesh size. The extensive FE calculations on the ultimate strength of ship hull plates with elastically restrained edges are presented. Then a new simple empirical formula for plate ultimate strength is developed, which includes the effect of the rotational restraint stiffness, rotational restraint stiffness, and aspect ratios. By applying the new formula and FE method to ship hull plates in real ships, a good coincidence of the results between these two methods is obtained, which indicates that the new formula can accurately predict the ultimate strength of ship hull plates with elastically restrained edges.     

New automated maritime telephone system

As one of the most valuable services in telecommunication service, NTT has developed a new automated maritime telephone system for public use. Calls between ship and land subscribers, or between one ship and another can be connected automatically by subscribers' dialing in the nationwide system. The new system adopts a lot of technical features such as automatic location registration, new signaling methods, etc. An outline of system performance and function is described herein.     

基于弧段检测的高频地波雷达特定目标航迹跟踪方法研究

本文对现有的高频地波雷达目标跟踪方法进行了概述,提出了一种地波雷达目标长时连续跟踪的方法,基本思想是:充分挖掘航迹弧段特征,基于特征对船只运动建模,并结合杂波背景进行融合决策。进一步,为了达到长时间连续跟踪的需求,借鉴深度学习的思想,利用新获取的弧段数据对算法估计结果不断递归校正,使得随着获取数据的增加跟踪越准确。该方法适用于杂波环境且在航道附近存在众多干扰船只的情况下对机动目标航迹的实时稳定跟踪,为高频地波雷达在复杂干扰环境下特定目标持续跟踪提供理论基础和方法指导,为充分发挥地波雷达在海上监视监测中的作用提供技术支撑。     

尺度自适应分层多阈值热红外遥感舰船检测

针对热红外遥感图像由于低对比度、条带噪声、低空间分辨率等特点而导致的检测效果不佳问题,提出了一种近岸舰船目标尺度自适应选择分层多阈值检测方法。采用舰船模板图像尺度归一化高斯拉普拉斯函数取极大值准则进行尺度自适应选择,利用所选的高斯多尺度空间差分多阈值筛选进行近岸舰船检测,并根据不同类型舰船模板图像尺度和分块数选择对热红外图像舰船目标检测的影响进行验证实验。实验结果表明:所提方法能根据模板尺度特征滤除相似区域,通过设置合理尺度和阈值参数能实现有效检测,且具有一定的抗噪能力。     

一种增强型YOLOv3的合成孔径雷达(SAR)舰船检测方法

近年来,海战场成为现代战争的主要作战区域之一,舰船目标逐渐成为海上重点监测对象,能否快速准确地识别海战场舰船目标的战术意图,给指挥员的决策提供必要的支持,这关系到一场海上战役的成败.随着合成孔径雷达(synthetic aperture radar,SAR)成像技术的不断发展,大量SAR图像可用于舰船目标检测与识别.利用SAR图像进行舰船目标检测与识别,已经成为重要的海洋应用之一.针对传统SAR图像舰船检测方法准确率较低的问题,本文在YOLOv3的基础上,结合感受野(receptive field block,RFB)模块,提出一种增强型的SAR舰船检测方法.该方法在最近公开的SAR图像舰船检测数据集上平均准确率值达到了91.50％,与原YOLOv3相比提高了0.92％.实验结果充分表明本文提出的算法在SAR舰船的检测中具有较好的检测效果.     

Signal detection for communications in the underwater acousticenvironment

Signal detection is a critical stage in the implementation of any effective communications system. The underwater acoustic environment, particularly in the presence of underwater vehicles, presents significant challenges to reliable detection without excessive false alarms. While there is often sufficient signal-to-noise ratio with respect to stationary broad-band background noise to permit reliable operation, the presence of strong event-like interference signals such as narrow-band signals and impulsive broad-band signals complicates the detection problem significantly. Frequency-hopped signals interleaved with quiescent bands are proposed as the basis of a robust detection system. These signals also make robust detection possible in a multi-access communications system. Two new detection algorithms that exploit the particular structure of these frequency-hopped signals are developed and their performance is analyzed. This analysis uses a modification of the doubly noncentral F-distribution that has not been used previously for such analysis. This distribution makes possible the direct calculation of probabilities of detection and false-alarm under interference and signal scenarios that cannot be analyzed using the better known noncentral F-distribution. With this analysis, the two developed detectors are shown to offer superior performance to that of either the CFAR detector or the binary data sequence detector. Experimental data confirms the theoretically derived results     

The new simple design equations for the ultimate compressive strength of imperfect stiffened plates

The new simple design equations for predicting the ultimate compressive strength of stiffened plates with initial imperfections in the form of welding-induced residual stresses and geometric deflections were developed in this study. A non-linear finite element method was used to investigate on 60 ANSYS elastic–plastic buckling analyses of a wide range of typical ship panel geometries. Reduction factors of the ultimate strength are produced from the results of 60 ANSYS inelastic finite element analyses. The proposed design equations have been developed based on these reduction factors. For the real ship structural stiffened plates, the most general loading case is a combination of longitudinal stress, transverse stress, shear stress and lateral pressure. The new simplified analytical method was generalized to deal with such combined load cases. The accuracy of the proposed equations was validated by the experimental results. Comparisons show that the adopted method has sufficient accuracy for practical applications in ship design.