Wave height measurement in the Taiwan Strait with a portable high frequency surface wave radar

As an important equipment for sea state remote sensing, high frequency surface wave radar （HFSWR） has received more and more attention. The conventional method for wave height inversion is based on the ratio of the integration of the second-order spectral continuum to that of the first-order region, where the strong external noise and the incorrect delineation of the first- and second-order Doppler spectral regions due to spectral aliasing are two major sources of errors in the wave height. To account for these factors, two more indices are introduced to the wave height estimation, i.e., the ratio of the maximum power of the second-or- der continuum to that of the Bragg spectral region （RSCB） and the ratio of the power of the second harmonic peak to that of the Bragg peak （RSHB）. Both indices also have a strong correlation with the underlying wave height. On the basis of all these indices an empirical model is proposed to estimate the wave height. This method has been used in a three-months long experiment of the ocean state measuring and analyzing ra- dar, type S （OSMAR-S）, which is a portable HFSWR with compact cross-loop/monopole receive antennas developed by Wuhan University since 2006. During the experiment in the Taiwan Strait, the significant wave height varied from 0 to 5 m. The significant wave heights estimated by the OSMAR-S correlate well with the data provided by the Oceanweather Inc. for comparison, with a correlation coefficient of 0.74 and a root mean square error （RMSE） of 0.77 m. The proposed method has made an effective improvement to the wave height estimation and thus a further step toward operational use of the OSMAR-S in the wave height extraction.

Surface tidal currents in the open sea area to the east of the Zhoushan Islands measured with high frequency surface wave radar

Based on the quasi-harmonic analysis of 11 d vector ocean currents obtained from two high frequency sur- face wave radars located at Zhujiajian Island and Shengshan Island, the spatial distribution characteristics of surface tidal currents in the open sea area to the east of the Zhoushan Islands of Zhejiang Province, China are studied. The following conclusions are drawn from the analysis： the tidal current pattern in the open sea area to the east of Zhoushan Islands is primarily regular semidiurnal, which is significantly affected by the shallow water constituents. The directions of the major axes of tidal current ellipses of M2 lie approx- imately in the NW-SE direction. With the increasing of distance away from the coast, the directions of the tidal current ellipses gradually shift toward the E-W direction. The tidal currents are mainly reversing cur- rents. The spatial distribution of probable maximum current velocities decreases gradually from northeast to southwest which is basically in accordance with the spatial distribution of measured maximum current velocities. The residual currents near the coast are larger than those far away from the coast. The directions of the residual currents are basically north by east, and the angle to the due north increases gradually with the increasing distance away from the coast. The topography shows a certain impact on the spatial distri- bution of shallow water constituents, the rotation of tidal currents, the probable maximum currents and the residual currents.

Vessel fusion tracking with a dual-frequency high-frequency surface wave radar and calibrated by an automatic identification system

High-frequency surface wave radar（HFSWR） and automatic identification system（AIS） are the two most important sensors used for vessel tracking.The HFSWR can be applied to tracking all vessels in a detection area,while the AIS is usually used to verify the information of cooperative vessels.Because of interference from sea clutter,employing single-frequency HFSWR for vessel tracking may obscure vessels located in the blind zones of Bragg peaks.Analyzing changes in the detection frequencies constitutes an effective method for addressing this deficiency.A solution consisting of vessel fusion tracking is proposed using dual-frequency HFSWR data calibrated by the AIS.Since different systematic biases exist between HFSWR frequency measurements and AIS measurements,AIS information is used to estimate and correct the HFSWR systematic biases at each frequency.First,AIS point measurements for cooperative vessels are associated with the HFSWR measurements using a JVC assignment algorithm.From the association results of the cooperative vessels,the systematic biases in the dualfrequency HFSWR data are estimated and corrected.Then,based on the corrected dual-frequency HFSWR data,the vessels are tracked using a dual-frequency fusion joint probabilistic data association（JPDA）-unscented Kalman filter（UKF） algorithm.Experimental results using real-life detection data show that the proposed method is efficient at tracking vessels in real time and can improve the tracking capability and accuracy compared with tracking processes involving single-frequency data.

Imposing Active Sources during High-Frequency Passive Surface-Wave Measurement

Passive surface-wave utilization has been intensively studied as a means of compensating for the short-age of low-frequency information in active surface-wave measurement, In general, passive surface-wave methods cannot provide phase velocities up to several tens of hertz; thus, active surface-wave methods are often required in order to increase the frequency range, To reduce the amount of field work, we pro-pose a strategy for a high-frequency passive surface-wave survey that imposes active sources during con-tinuous passive surface-wave observation; we call our strategy ＂mixed-source surface-wave （MSW） measurement,＂ Short-duration （within 10 min） passive surface waves and mixed-source surface waves were recorded at three sites with different noise levels： namely, inside a school, along a road, and along a railway, Spectral analysis indicates that the high-frequency energy is improved by imposing active sources during continuous passive surface-wave observation, The spatial autocorrelation （SPAC） method and the multichannel analysis of passive surface waves （MAPS） method based on cross-correlations were performed on the recorded time sequences, The results demonstrate the flexibility and applicability of the proposed method for high-frequency phase velocity analysis, We suggest that it will be constructive to perform MSW measurement in a seismic investigation, rather than exclusively performing either active surface-wave measurement or passive surface-wave measurement,

Hierarchical microstructures with high spatial frequency laser induced periodic surface structures possessing different orientations created by femtosecond laser ablation of silicon in liquids

High spatial frequency laser induced periodic surface structures(HSFLs)on silicon substrates are often developed on flat surfaces at low fluences near ablation threshold of 0.1 J/cm2,seldom on microstructures or microgrooves at relatively higher fluences above 1 J/cm^2.This work aims to enrich the variety of HSFLs-containing hierarchical microstructures,by femtosecond laser(pulse duration:457 fs,wavelength:1045 nm,and repetition rate:100 kHz)in liquids(water and acetone)at laser fluence of 1.7 J/cm^2.The period of Si-HSFLs in the range of 110–200 nm is independent of the scanning speeds(0.1,0.5,1 and 2 mm/s),line intervals(5,15 and 20μm)of scanning lines and scanning directions(perpendicular or parallel to light polarization direction).It is interestingly found that besides normal HSFLs whose orientations are perpendicular to the direction of light polarization,both clockwise or anticlockwise randomly tilted HSFLs with a maximal deviation angle of 50°as compared to those of normal HSFLSs are found on the microstructures with height gradients.Raman spectra and SEM characterization jointly clarify that surface melting and nanocapillary waves play important roles in the formation of Si-HSFLs.The fact that no HSFLs are produced by laser ablation in air indicates that moderate melting facilitated with ultrafast liquid cooling is beneficial for the formation of HSFLs by LALs.On the basis of our findings and previous reports,a synergistic formation mechanism for HSFLs at high fluence was proposed and discussed,including thermal melting with the concomitance of ultrafast cooling in liquids,transformation of the molten layers into ripples and nanotips by surface plasmon polaritons(SPP)and second-harmonic generation(SHG),and modulation of Si-HSFLs direction by both nanocapillary waves and the localized electric field coming from the excited large Si particles.

Wave height estimation using the singular peaks in the sea echoes of high frequency radar

The popular methods to estimate wave height with high-frequency（HF） radar depend on the integration over the second-order spectral region and thus may come under from even not strong external interference. To improve the accuracy and increase the valid detection range of the wave height measurement, particularly by the smallaperture radar, it is turned to singular peaks which often exceed the power of other frequency components. The power of three kinds of singular peaks, i.e., those around ±1,±√2 and ±1√2 times the Bragg frequency, are retrieved from a one-month-long radar data set collected by an ocean state monitoring and analyzing radar,model S（OSMAR-S）, and in situ buoy records are used to make some comparisons. The power response to a wave height is found to be described with a new model quite well, by which obvious improvement on the wave height estimation is achieved. With the buoy measurements as reference, a correlation coefficient is increased to 0.90 and a root mean square error（RMSE） is decreased to 0.35 m at the range of 7.5 km compared with the results by the second-order method. The further analysis of the fitting performance across range suggests that the peak has the best fit and maintains a good performance as far as 40 km. The correlation coefficient is 0.78 and the RMSE is 0.62 m at 40 km. These results show the effectiveness of the new empirical method, which opens a new way for the wave height estimation with the HF radar.

Contrast validation test for retrieval method of high frequency ground wave radar

In this paper, on the basis of the working principles of high frequency ground wave radar for retrieval of ocean wave and sea wind elements were used to systematically study the data obtained from contrast validation test in Zhoushan sea area of Zhejiang Province on Oct. 2000, to validate the accuracy of OSMAR2000 for wave and wind parameters, and to analyze the possible error caused when using OSMAR2000 to retrieve ocean parameters.

Forecasting of surface current velocities using ensemble machine learning algorithms for the Guangdong−Hong Kong−Macao Greater Bay area based on the high frequency radar data

Forecasting of ocean currents is critical for both marine meteorological research and ocean engineering and construction.Timely and accurate forecasting of coastal current velocities offers a scientific foundation and decision support for multiple practices such as search and rescue,disaster avoidance and remediation,and offshore construction.This research established a framework to generate short-term surface current forecasts based on ensemble machine learning trained on high frequency radar observation.Results indicate that an ensemble algorithm that used random forests to filter forecasting features by weighting them,and then used the AdaBoost method to forecast can significantly reduce the model training time,while ensuring the model forecasting effectiveness,with great economic benefits.Model accuracy is a function of surface current variability and the forecasting horizon.In order to improve the forecasting capability and accuracy of the model,the model structure of the ensemble algorithm was optimized,and the random forest algorithm was used to dynamically select model features.The results show that the error variation of the optimized surface current forecasting model has a more regular error variation,and the importance of the features varies with the forecasting time-step.At ten-step ahead forecasting horizon the model reported root mean square error,mean absolute error,and correlation coefficient by 2.84 cm/s,2.02 cm/s,and 0.96,respectively.The model error is affected by factors such as topography,boundaries,and geometric accuracy of the observation system.This paper demonstrates the potential of ensemble-based machine learning algorithm to improve forecasting of ocean currents.

基于多帧聚类的紧凑型HFSWR虚假点迹识别方法

紧凑型高频地波雷达发射功率低,目标检测时信噪比低、虚警率高,会产生大量虚假点迹,影响后续目标跟踪性能。为了滤除虚假点迹,利用目标的运动特性,提出了一种多帧聚类与极限学习机分类两级级联的虚假点迹识别方法。首先,利用基于最优邻域尺寸的多帧聚类方法,将连续多帧中与待识别点迹属于同一潜在目标的点迹聚类成簇。然后,计算簇内待识别点迹与其相邻帧内点迹的距离-多普勒速度的差分值,以其为特征利用极限学习机辨识虚假点迹。实验结果表明,所提方法能够准确将属于同一目标的点迹聚类,虚假点迹识别率达到95%。

Surface motion of a semi-elliptical hill for incident plane SH waves

A closed-form analytical solution of surface motion of a semi-elliptical cylindrical hill for incident plane SH waves is presented. Although some previous analytical work had already dealt with hill topography of semi-circular and shallow circular, our work aims at calculating surface motion of very prolate hill for high incident frequency, and explaining the special vibrating is checked by boundary conditions, numerical results for and some conclusions are obtained. properties of very prolate hill. Accuracy of the solution surface motion of oblate and prolate hills are calculated,

基于改进DeeplabV 3+的HFSWR电离层杂波及海杂波自动识别

针对高频地波雷达(HFSWR)回波谱中背景噪声复杂、杂波占比较小且电离层杂波形态位置各异,难以自动识别的问题,以DeeplabV3+深度学习算法为基础架构并加以改进,提出一种HFSWR电离层杂波及海杂波自动识别方法。选用轻量级MobileNetV2作为主干特征网络,加入通道注意力机制模块SENet,实现对杂波标签的侧重学习,优化训练集中各类标签的损失权重;采用模型预训练迁移法对网络进行预训练,解决样本空间过小的问题。实测数据集上的实验结果表明,本方法可以实现HFSWR电离层杂波及海杂波的自动识别。相比原DeeplabV3+算法,杂波识别结果更为准确和精细,海杂波识别结果的平均交并比(mIoU)和准确率(ACC)分别提升2.9%和5.1%;电离层杂波识别结果的mIoU和ACC分别提升3.0%和4.9%。

HFSWR海洋-电离层一体化探测实验与数据分析

高频地波雷达(High-frequency Surface Wave Radar,HFSWR)凭借其全天时、全天候和超视距探测等方面的能力,在海洋遥感与电离层探测应用方面均取得了阶段性进展,然而当前在海洋-电离层回波联合方面的研究还十分有限。本文基于哈尔滨工业大学(威海)HFSWR一体化探测系统,对台风“梅花”过境渤海湾期间的海洋回波与电离层回波进行了数据分析。首先对HFSWR一体化探测系统的整体构成进行了介绍,之后基于Bragg原理对海洋回波进行了海洋径向流速分析,并采用经验模态分解以及HHT变换方法对电离层回波进行能量谱分析。实验结果表明,在台风“梅花”过境期间,海洋回波与电离层回波均出现了明显的特征变化,两者之间存在一定的联动机制。本文提出了进一步研究海洋与电离层之间动力学关系的需要,并强调了HFSWR一体化探测系统的独特体制在海洋-电离层联合研究方面的优势。

Spatial Distribution Characteristics of Surface Tidal Currents in the Southwest of Taiwan Strait

This study was conducted on the spatial distribution characteristics of surface tidal currents in the southwestern Taiwan Strait based on the quasi-harmonic analysis of current data obtained by two high frequency surface wave radar(HFSWR) systems. The analysis shows that the tidal current pattern in the southwestern Taiwan Strait is primarily semi-diurnal and influenced significantly by shallow water constituents. The spatial distribution of tidal current ellipses of M2 is probably affected by the interaction between two different systems of tide wave, one from the northern mouth of Taiwan Strait and the other from the Bashi Channel. The directions of the major axes of M2 tidal current ellipses coincide roughly with the axis of the Taiwan Strait. The spatial distribution of the magnitudes of the probable maximum current velocity(PMCS) shows gradual increase of the velocity from northeast to southwest, which is in accordance with the spatial distribution of the measured maximum current velocity(MMCS). The directions of the residual currents are in accordance with the direction of the prevailing monsoon wind at the Taiwan Strait and the direction of the Taiwan warm current during summer. The bathymetry also shows a significant effect on the spatial distribution characteristics of tidal currents.

Observation and modeling of tide- and wind-induced surface currents in Galway Bay

A high-frequency radar system has been deployed in Galway Bay, a semi-enclosed bay on the west coast of Ireland. The system provides surface currents with fine spatial resolution every hour. Prior to its use for model validation, the accuracy of the radar data was verified through comparison with measurements from acoustic Doppler current profilers （ADCPs） and a good correlation between time series of surface current speeds and directions obtained from radar data and ADCP data. Since Galway Bay is located on the coast of the Atlantic Ocean, it is subject to relatively windy conditions, and surface currents are therefore strongly wind-driven. With a view to assimilating the radar data for forecasting purposes, a three-dimensional numerical model of Galway Bay, the Environmental Fluid Dynamics Code （EFDC）, was developed based on a terrain-following vertical （sigma） coordinate system. This study shows that the performance and accuracy of the numerical model, particularly with regard to tide- and wind-induced surface currents, are sensitive to the vertical layer structure. Results of five models with different layer structures are presented and compared with radar measurements. A variable vertical structure with thin layers at the bottom and the surface and thicker layers in the middle of the water column was found to be the optimal layer structure for reproduction of tideand wind-induced surface currents. This structure ensures that wind shear can properly propagate from the surface layer to the sub-surface layers, thereby ensuring that wind forcing is not overdamped by tidal forcing. The vertical layer structure affects not only the velocities at the surface layer but also the velocities further down in the water column.

基于改进SFLA-Elman神经网络的电离层杂波抑制方法

针对高频地波雷达目标检测中电离层杂波的干扰问题,提出了一种基于改进混合蛙跳算法优化Elman神经网络预测抑制电离层杂波的策略。为解决混合蛙跳算法初始种群分布不均匀、收敛精度低、易陷于局部极值等问题,引入Cubic混沌映射、莱维飞行策略、非线性平衡因子和复制操作,增强种群多样性,提高算法搜索能力。利用改进后的算法和其他算法分别优化Elman神经网络预测抑制模型,结果表明,改进后的算法无论是在收敛精度和稳定性上,还是在临近距离单元电离层杂波的预测抑制上,都取得了显著的提升。在基本保留目标信号的基础上,平均信杂比较原始回波提升18.52 dB,较原始混合蛙跳算法提升1.08 dB,对于电离层杂波的抑制具有较高应用价值。

基于自适应KF的船载地波雷达目标跟踪方法

针对使用传统的卡尔曼滤波器进行多目标跟踪易发生状态估计不准确、航迹断裂的问题,提出了一种转换量测卡尔曼滤波增益自适应调整方法。结合船只目标的运动特性和历史船只航迹数据,采用线性最小二乘拟合提取出航迹参数的变化趋势。使用似然函数分别计算目标预测状态和量测状态与航迹的隶属度。利用预测状态和量测状态的隶属度值对滤波方式进行选择。利用仿真及实测船载地波雷达数据开展了目标跟踪实验,结果表明,使用该文方法能够得到平滑、持续的航迹输出,目标的跟踪距离远、跟踪精度高,优于现有的自适应滤波方法。

基于卷积神经网络的高频地波雷达有效波高反演

高频地波雷达海面回波多普勒谱中蕴含着非常丰富的海浪信息,针对经验模型通常存在对回波谱信息利用不充分的问题,本文提出了一种利用卷积神经网络反演波高的方法。首先基于雷达后向散射截面方程和有效波高反演的参数化经验模型,并结合实测数据分析,本文选取了二阶与一阶谱能量比值、二阶谱能量和、二阶与一阶谱峰值比、Bragg频率处无向波高谱值、二阶谱能量、二阶谱峰值、左右一阶谱峰值及其比值、■布拉格频率处峰值、一阶谱能量共11种与有效波高相关的回波谱特征参数;为进一步说明一阶和二阶信息对有效波高的作用,将11种特征参数分成4个组合,分别搭建了多层深度卷积神经网络并进行高频地波雷达有效波高反演;然后将高、低两种海况下多层深度卷积神经网络模型与经验模型反演结果进行对比分析。研究结果表明,利用11种特征参数构建的模型波高反演精度更高,在高、低海况测试集中雷达反演有效波高与浮标波高序列相关系数R分别为0.92和0.78,均方根误差(Root Mean Square Error,RMSE)分别为0.32 m和0.21 m,平均绝对误差(Mean Absolute Error,MAE)分别为0.25 m和0.16 m,平均相对误差(Mean Relative Error,MRE)分别为0.12和0.27。综合利用这11种特征参数,能够提高雷达在复杂海况下对有效波高的反演精度。

基于自适应α-β滤波的HFSWR海上目标航迹跟踪

针对基于α-β滤波的高频地波雷达海上目标航迹跟踪方法跟踪精度较低、工程适用性较差的问题,提出了一种极坐标下α-β滤波自适应系数选取方法,该方法有效利用了高频地波雷达目标量测参数的特点,能够在跟踪过程中根据实际量测对滤波系数进行自适应调整。利用仿真及实测地波雷达数据以及同步AIS航迹对提出方法的航迹跟踪性能进行了实验验证,并与现有自适应系数选取方法的跟踪性能进行了对比,结果表明,本文方法能够得到平滑、持续的航迹输出,跟踪距离远,跟踪率及跟踪精度高。

基于IAVOA-GRU网络的高频地波雷达电离层杂波预测

电离层杂波的精确预测对提升高频地波雷达的探测性能具有重要作用。提出了一种基于改进非洲秃鹫优化算法优化门控循环单元(Improved African Vultures Optimization Algorithm Optimization Gated Recurrent Unit,IAVOA-GRU)网络的电离层杂波预测方法。首先,依据电离层杂波的混沌特性,通过相空间重构方法对接收到的电离层杂波进行相空间重建,构建GRU网络的输入、输出样本集;然后,利用IAVOA对GRU网络的隐层节点数、迭代次数及初始学习速率3个超参数值执行优选;最后,重新训练优化后的GRU网络,并进行预测。实测结果表明,相较其他6种对比预测模型,所提出的IAVOA-GRU网络模型具有较高的预测精度和可靠性,为有效改善高频地波雷达的探测性能提供了一种思路和方法。

基于差值信噪比法的船载地波雷达一阶谱识别

本文提出了适用于船载地波雷达展宽一阶谱识别的差值信噪比方法。通过结合仿真分析和实测试验数据,开展了船载地波雷达展宽一阶谱的频移和展宽特性分析,确定了一阶谱的最大展宽范围与平台运动速度之间的定量关系。通过分析一维多普勒频点间的差值数量关系,确定了边界预筛选准则。利用展宽一阶谱的区域连续特性,实现展宽一阶谱边界最终识别。采用船载地波雷达仿真和实测数据对所提方法的有效性进行了验证,所提方法相对于传统方法取得了较好的识别效果。