Persymmetric adaptive polarimetric detection of subspace range-spread targets in compound Gaussian sea clutter

This paper focuses on the adaptive detection of range and Doppler dual-spread targets in non-homogeneous and nonGaussian sea clutter.The sea clutter from two polarimetric channels is modeled as a compound-Gaussian model with different parameters,and the target is modeled as a subspace rangespread target model.The persymmetric structure is used to model the clutter covariance matrix,in order to reduce the reliance on secondary data of the designed detectors.Three adaptive polarimetric persymmetric detectors are designed based on the generalized likelihood ratio test(GLRT),Rao test,and Wald test.All the proposed detectors have constant falsealarm rate property with respect to the clutter texture,the speckle covariance matrix.Experimental results on simulated and measured data show that three adaptive detectors outperform the competitors in different clutter environments,and the proposed GLRT detector has the best detection performance under different parameters.

High-Resolution Simulation and Analysis of the Mature Structure of a Polar Low over the Sea of Japan on 21 January 1997

This paper presents a high-resolution simulation of a remarkable polar low observed over the Sea of Japan on 21 January 1997 by using a 5-km mesh non-hydrostatic model MRI-NHM (Meteorological Research Institute Non-Hydrostatic Model). A 24-hour simulation starting from 0000 UTC 21 January 1997 successfully reproduced the observed features of the polar low such as the wrapping of western part of an initial E-W orientation vortex, the spiral-shaped bands, the cloud-free 'eye', and the warm core structure at its mature stage. The 'eye' of the simulated polar low was relatively dry, and was associated with a strong downdraft. A thermodynamic budget analysis indicates that the 'warm core' in the 'eye' region was mainly caused by the adiabatic warming associated with the downdraft. The relationship among the condensational diabatic heating, the vertical velocity, the convergence of the moisture flux, and the circulation averaged within a 50 km×50 km square area around the polar low center shows that they form a positive feedback loop, and this loop is not inconsistent with the CISK (Conditional Instability of the Second Kind) mechanism during the developing stage of the polar low.

Case study on the three-dimensional structure of meso-scale eddy in the South China Sea based on a high-resolution model

Meso-scale eddies are important features in the South China Sea（SCS）. The eddies with diameters of 50–200 km can greatly impact the transport of heat, momentum, and tracers. A high-resolution wave-tide-circulation coupled model was developed to simulate the meso-scale eddy in the SCS in this study. The aim of this study is to examine the model ability to simulate the meso-scale eddy in the SCS without data assimilations The simulated Sea Surface Height（SSH） anomalies agree with the observed the AVISO SSH anomalies well. The simulated subsurface temperature profiles agree with the CTD observation data from the ROSE（Responses of Marine Hazards to climate change in the Western Pacific） project. The simulated upper-ocean currents also agree with the main circulation based on observations. A warm eddy is identified in winter in the northern SCS. The position and domain of the simulated eddy are confirmed by the observed sea surface height data from the AVISO. The result shows that the model has the ability to simulate the meso-scale eddy in the SCS without data assimilation.The three-dimensional structure of the meso-scale eddy in the SCS is analyzed using the model result. It is found that the eddy center is tilted vertically, which agrees with the observation. It is also found that the velocity center of the eddy does not coincide with the temperature center of the eddy. The result shows that the model has the ability to simulate the meso-scale eddy in the SCS without data assimilations. Further study on the forming mechanism and the three-dimensional structure of the meso-scale eddies will be carried out using the model result and cruise observation data in the near future.

Deep-large faults controlling on the distribution of the venting gas hydrate system in the middle of the Qiongdongnan Basin, South China Sea

Many locations with concentrated hydrates at vents have confirmed the presence of abundant thermogenic gas in the middle of the Qiongdongnan Basin(QDNB).However,the impact of deep structures on gasbearing fluids migration and gas hydrates distribution in tectonically inactive regions is still unclear.In this study,the authors apply high-resolution 3D seismic and logging while drilling(LWD)data from the middle of the QDNB to investigate the influence of deep-large faults on gas chimneys and preferred gasescape pipes.The findings reveal the following:(1)Two significant deep-large faults,F1 and F2,developed on the edge of the Songnan Low Uplift,control the dominant migration of thermogenic hydrocarbons and determine the initial locations of gas chimneys.(2)The formation of gas chimneys is likely related to fault activation and reactivation.Gas chimney 1 is primarily arises from convergent fluid migration resulting from the intersection of the two faults,while the gas chimney 2 benefits from a steeper fault plane and shorter migration distance of fault F2.(3)Most gas-escape pipes are situated near the apex of the two faults.Their reactivations facilitate free gas flow into the GHSZ and contribute to the formation of fracture‐filling hydrates.

A parameter inversion for sea bridge based on high-resolution polarimetric synthetic aperture radar

Each reflection return of a bridge over water is displayed as wide stripe in a high-resolution synthetic aperture radar （SAR） image, which lead to difficulties in a parameter inversion. Therefore, a method of bridge parameter inversion is proposed for high-resolution full polarimetric SAR （PolSAR）. First, the single, double and triple- bounce returns from each component of the bridge are distinguished by the polarization scattering features. Then the reasons which lead to the backscatter echoes oft_he bridge over water being displayed as stripes are analyzed, using a principle of microwave reflection, as well as an extraction method for each reflection return, and a parameter retrieval method is obtained. Finally, the parameters of the bridge, including the height （top and bottom surfaces of the sea bridge）, width, thickness, span, and height of the bridge tower, are retrieved using full polarimetric AIRSAR data. When a comparison of the measured data is completed, the results indicate that the proposed method can invert the parameters with a high accuracy, and that the inversion error of the bridge height （bottom surface） is only 1.3%. Moreover, the results also show that for the high-resolution SAR, the C and L-band images have the same ability in regards to parameter retrieval.

High-resolution simulation of upper-ocean submesoscale variability in the South China Sea:Spatial and seasonal dynamical regimes

Submesoscale processes in marginal seas usually have complex generating mechanisms,highly dependent on the local background flow and forcing.This numerical study investigates the spatial and seasonal differences of submesoscale activities in the upper ocean of the South China Sea(SCS)and the different dynamical regimes for sub-regions.The spatial and seasonal variations of vertical vorticity,horizontal convergence,lateral buoyancy gradient,and strain rate are analyzed to compare the submesoscale phenomenon within four sub-regions,the northern region near the Luzon Strait(R1),the middle ocean basin(R2),the western SCS(R3),and the southern SCS(R4).The results suggest that the SCS submesoscale processes are highly heterogeneous in space,with different seasonalities in each sub-region.The submesoscale activities in the northern sub-regions(R1,R2)are active in winter but weak in summer,while there appears an almost seasonal anti-phase in the western region(R3)compared to R1 and R2.Interestingly,no clear seasonality of submesoscale features is shown in the southern region(R4).Further analysis of Ertel potential vorticity reveals different generating mechanisms of submesoscale processes in different sub-regions.Correlation analyses also show the vertical extent of vertical velocity and the role of monsoon in generating submesoscale activities in the upper ocean of sub-regions.All these results suggest that the sub-regions have different regimes for submesoscale processes,e.g.,Kuroshio intrusion(R1),monsoon modulation(R2),frontal effects(R3),topography wakes(R4).

Study on Dim Target Detection and Discrimination from Sea Clutter

Dim target detection from sea clutter is one of the difficult topics in ocean remote sensing application. By aiming at the shortcoming of false alarms when using track before detect （TBD） based on dynamic programming, a new discrimination method called statistics of direction histogram （SDH） is proposed, which is based on different features of trajectories between the true target and false one. Moreover, a new series of discrimination schemes of SDH and Local Extreme Value method （LEV） are studied and applied to simulate the actually measured radar data. The results show that the given discrimination is effective to reduce false alarms during dim targets detection.

Modified GIT model for predicting wind-speed behavior of low-grazing-angle radar sea clutter

A modified GIT model for describing the variational trend of mean clutter reflectivity as a function of wind speed is proposed. It uses two slope adjustment factors and two critical wind-speed factors to define and adjust the increasing slope of reflectivity with respect to wind speed. In addition, it uses a constant factor to compensate the overall amplitude of clutter reflectivity. The performance of the modified GIT model has been verified on the basis of the L-band low-grazing-angle radar sea clutter data. The results are in good agreement with the experimental data, indicating that the model is more effective in predicting the wind-speed behavior of clutter reflectivity than the conventional GIT model, especially for lower and higher wind speeds. We believe that the proposed model can provide deeper insights into the relationship between radar sea clutter reflectivity and sea state conditions.

Estimation of sea clutter inherent Doppler spectrum from shipborne S-band radar sea echo

Measurement of shipborne radar sea echo is instrumental in collecting the sea clutter data in open sea areas.However,the ship movement would introduce an extra Doppler component into the spectrum of the sea clutter,so the sea clutter inherent spectrum must be estimated prior to investigating the sea clutter Doppler characteristics from the shipborne radar sea echo.In this paper we show some results about a shipborne sea clutter measurement experiment that was conducted in the South China Sea in a period between 2017 and 2018;abundant clutter data have been collected by using a shipborne S-band clutter measurement radar.To obtain the sea clutter inherent Doppler spectrum from these data,an estimation method,based on the mapping relationship between the shipborne clutter spectrum and the inherent clutter spectrum,is proposed.This method is validated by shipborne clutter data sets under the same measuring conditions except for the ship speed.Using this method,the characteristics of the Doppler spectrum lineshapes in the South China Sea are calculated and analyzed according to different sea states,wave directions,and radar resolutions,which can be instrumental in designing the radar target detection algorithms.

Fractal-based weak target detection within sea clutter

The target on the sea surface is complex and difficult to detect due to the interference of backscattered returns from the sea surface illuminated by the radar pulse. Detrended fluctuation analysis （DFA） has been used successfully to extract the time-domain Hurst exponent of sea-clutter series. Since the frequency of the sea clutter mainly concentrates around Doppler center so that we consider to extract frequency-do- main fractal characterization and then detect a weak target within sea clutter by using the difference of frequency-domain fractal characterization. The generalized detrended fluctuation analysis （GDFA） is more flexible than traditional DFA owing to its smoothing action for the clutters. In this paper, we apply the GDFA to evaluate the generalized Hurst exponent of sea-clutter series in the frequency domain. The difference of generalized Hurst exponents between different sea-clutter range bins would be used to determine whether the target exists. Moreover, some simulations with the real IPIX radar data have also been demonstrated in order to suooort this conclusion.

A statistical distribution of quad-pol X-band sea clutter time series acquired at a grazing angle

Although the complex Wishart distribution has been widely used to analyze the statistic properties of quad-pol SAR spatial data, the applicability of this complex distribution to the time series of sea clutter is rarely discussed.The measured data of the quad-pol X-band marine radar demonstrate that the time series of the sea echoes are also satisfied the circular Gaussian distributions if the low intensity signals, which are mainly dominated by a radar noise, in the shadow regions of the large-scale waves are removed. On the basis of this fact, the probability density functions（PDFs） of the intensity as well as the phase, the real and the imaginary parts of the sea echoes obtained by the marine radar have been derived, and the theoretical models are all expressed in closed forms. In order to validate the theoretical results, the PDFs are compared with the experimental data collected by the Mc Master IPIX radar. And the comparisons show that the PDF models are in good agreement with the experimental data.

Effective Sea Clutter Spectrum Extraction Method for HFSWR in Adverse Conditions

An effective approach in solving the sea clutter spectrum extraction problem is studied in the paper.Different from the conventional signal to noise ratio（SNR）method based on Doppler frequency or range domain information,a method is developed to characterize the differences between the sea echo and those interferences are by signal to interference plus noise ratio（SINR）which jointly utilizing the range,Doppler frequency and azimuth domain information.Furthermore,these differences can be adaptable to adverse conditions by forming the necessary boundaries and constraints in searching of the maximum SINR,which greatly promotes the extraction of sea clutter spectrum.The real high frequency surface wave radar（HFSWR）data demonstrate that the proposed method is less influenced by those interferences and can effectively extract the sea clutter spectrum even under the adverse conditions.Furthermore,it has been shown as an effective method for ship detection and sea state remote sensing of HFSWR.

Effect of Changes in Sea-Surface State on Statistical Characteristics of Sea Clutter with X-Band Radar

We have made observations of X-band radar sea clutter from the sea surface and sea-surface state in the Uraga Suido Traffic Route, which is used by ships entering and leaving Tokyo Bay, and the nearby Daini Kaiho Sea Fortress. We estimated the distributions of reflected amplitudes due to sea clutter using models that assume Weibull, Log-Weibull, Log-normal, and K-distributions. We then compared the results of estimating these distributions with sea-surface state data to investigate the effects of changes in the sea-surface state on the statistical characteristics of sea clutter. As a result, we showed that observed sub-ranges not containing a target conformed better to the Weibull distribution regardless of Significant Wave Height (SWH). Further, sub-ranges conforming to the Log-Weibull or Log-normal distribution in areas contained a target when the SWH was large, and as SWH decreases, sub-ranges conforming to a Log-normal. We also showed that for observed sub-ranges not containing a target, the shape parameter, c, of both Weibull and Log-Weibull distribution correlated with SWH. The correlation between wave period and shape parameters of Weibull and Log-Weibull distribution showed a weak correlation.

Distributed Sea Clutter Denoising Algorithm Based on Variational Mode Decomposition

In order to improve the detection accuracy of chaotic small signal prediction models under the background of sea clutter,a distributed sea clutter denoising algorithm is proposed,on the basis of variational modal decomposition(VMD).The sea clutter signal is decomposed into variational modal functions(VMF)with different center bandwidths by means of VMD.By analyzing the autocorrelation characteristics of the deco mposed signal,we perform instantaneous half-period(IHP)and wavelet threshold denoising processing on the high-frequency and low-frequency components respectively,and regain the sea clutter signals.Based on LSSVM sea clutter prediction model,this research compares and analyzes the denoising effects of VMD.Experi ment results show that,the RMSE after denoising is reduced by two orders of magnitude,approximating 0.00034,with an apparently better denoising effect,compared with the root mean square error(RMSE)of the prediction before denoising.

The multifractal spectrum of a sea clutter using a random walk model

The radar echo signal of a sea clutter is nonlinear, nonstationary and time varying. A multifractal measure analysis can describe the local singularity of a physics system. The random walk model of a sea clutter scattering is analysed to disclose the intrinsic physical characteristics and laws of the sea clutter. Stochastic differential equations are given for the physical quality of the sea clutter. A diffusion process model is established using It o formula. The singularity of the random walk model is tested by a multifractal spectroscopy, and the accuracy of this model is proven by the multifractal spectroscopy of a real-life IPIX radar data set. Thus, the random walk model is effective for describing the dynamics mechanism of the sea clutter.

First order sea clutter cross section for bistatic shipborne HFSWR

This paper studies the development on the first order sea clutter cross section for bistatic high frequency surface wave radar (HFSWR). Based on the received first order electric field expression, a closed-form of cross sections is derived to account for the case of receiving antenna array being mounted on the shipborne platform. The uniform linear motion and sway motion components are assumed to be responsible for the observed differences in comparison with the bistatic fixed antenna case. Correspondingly, simulations are conducted to study the sea clutter spectral characteristics for these two cases versus different system parameters and sea state conditions. It is shown numerically that the forward motion component will spread the Bragg lines severely and the influence triggered by the sway motion can be explained as the Bessel function modulation of the ordinary sea clutter spectra. The obtained results have important implications in the application of shipborne HFSWR technology to ocean remote sensing and target detection.

Bayesian track-before-detect algorithm for nonstationary sea clutter

Radar detection of small targets in sea clutter is a particularly demanding task because of the nonstationary characteristic of sea clutter.The track-before-detect(TBD)filter is an effective way to increase the signal-to-clutter ratio(SCR),thus improving the detection performance of small targets in sea clutter.To cope with the nonstationary characteristic of sea clutter,an easily-implemented Bayesian TBD filter with adaptive detection threshold is proposed and a new parameter estimation method is devised which is integrated into the detection process.The detection threshold is set according to the parameter estimation result under the framework of information theory.For detection of closely spaced targets,those within the same range cell as the one under test are treated as contribution to sea clutter,and a successive elimination method is adopted to detect them.Simulation results prove the effectiveness of the proposed algorithm in detecting small targets in nonstationary sea clutter,especially closely spaced ones.

Reflectivity Model of Low Grazing Angle Radar Sea Clutter

The commonly used reflectivity models of radar sea clutter are summarized. Among these models, the adjusted Barton model and the adjusted Morchin model are compared. From the analysis result, the γ-p reflectivity model is presented for low grazing angle radar sea clutter by the adjustment of the original Barton reflectivity model. The model takes into account radar frequency, grazing angle, sea condition, and polarization property. The influences of these factors on the proposed model are analyzed. The model absorbs the merits from commonly used reflectivity models for sea clutter. It introduces several researchers' opinions, and extends them. And it accounts for the reflectivity at arbitrary radar frequency from VHF to X-band, arbitrary low grazing angle, arbitrary sea condition and different polarization property. One of the main results is the proposed γ-p reflectivity model can reflect the influence of polarization on sea clutter reflectivity to some extent. The proposed γ-p reflectivity model of low-angle radar-sea clutter is validated by comparing the simulated and statistically experimental data.

基于WGAN-GP-CNN的海面小目标检测

针对传统基于统计理论的海面小目标检测方法在复杂海面环境中性能不高的问题,该文提出了一种改进的检测方法。首先通过分析海杂波和目标回波的特征,将检测问题转化为特征空间的分类任务。鉴于海面小目标样本数量有限,存在样本不平衡的问题,该文引入了一种基于梯度惩罚的沃瑟斯坦生成对抗网络(Wasserstein Generative Adversarial Network with Gradient Penalty,WGAN-GP)来增强目标数据,从而在数量上平衡目标样本与海杂波样本。同时,对原始WGAN-GP网络的损失函数进行了改进,引入相位损失以确保生成数据能够反映真实数据的相位信息。基于这些数据,进一步提取了生成目标和海杂波的高维特征,并将其送入卷积神经网络(Convolutional Neural Network,CNN)进行训练。为了应对高维特征空间中虚警概率难以控制的问题,对CNN算法进行了改进,通过设置Softmax分类器的阈值,实现了虚警概率可控。最后,借助公开的IPIX雷达数据集进行实验验证,所提的WGAN-GP-CNN检测器在积累时间为1.024 s,虚警概率为0.001时,平均检测概率达到0.8683,具有良好的检测效果。

基于无监督图互信息最大化的海面小目标异常检测

受到复杂海洋环境的影响,雷达对海面慢速小目标难以实现高性能检测。对于这类目标,传统的基于能量的统计检测方法存在着严重的性能损失。针对这一问题,该文提出了基于互信息最大化框架下的海面小目标检测方法,实现海杂波背景下的无监督目标异常检测任务。首先,考虑到高分辨雷达回波不满足传统神经网络对样本独立同分布的假设,该文从图的角度重新建模数据,利用回波的空时相关特性来构建图拓扑结构。该文提出相对最大节点度并联合7个已有特征作为节点的初始表示向量。接下来,采用图注意力网络作为互信息最大化框架中的编码器学习节点表示向量。最后,使用异常检测算法进行目标检测,并实现虚警可控。经实测数据验证,使用快速凸包学习算法时,相比三特征检测器,所提检测器性能提升了9.2%;相比时频三特征检测器,性能提升了7.9%。当网络输出更高维的表示向量时,使用孤立森林算法的检测器的性能提升了27.4%。