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.

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.

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.

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.

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.

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.

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-domain 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 support 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.

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.

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.

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.

A convolutional neural network based approach to sea clutter suppression for small boat detection

Current methods for radar target detection usually work on the basis of high signal-to-clutter ratios.In this paper we propose a novel convolutional neural network based dual-activated clutter suppression algorithm,to solve the problem caused by low signal-to-clutter ratios in actual situations on the sea surface.Dual activation has two steps.First,we multiply the activated weights of the last dense layer with the activated feature maps from the upsample layer.Through this,we can obtain the class activation maps(CAMs),which correspond to the positive region of the sea clutter.Second,we obtain the suppression coefficients by mapping the CAM inversely to the sea clutter spectrum.Then,we obtain the activated range-Doppler maps by multiplying the coefficients with the raw range-Doppler maps.In addition,we propose a sampling-based data augmentation method and an effective multiclass coding method to improve the prediction accuracy.Measurement on real datasets verified the effectiveness of the proposed method.

Modeling and simulation methods of sea clutter based on measured data

The modeling and simulation of sea clutter are important in detecting radar targets in sea backgrounds.Because the nonstationary property of sea clutter is ignored in traditional statistical models,a new method based on measured sea clutter is proposed in this paper.First,we convert the measured sea clutter data under different sea conditions[xI,xQ]into real amplitude SM.Instantaneous phaseθis then extracted from the coherent radar’s baseband data.Second,we select a candidate statistic model and estimate its parameters based on SM by utilizing maximum likelihood estimation.Finally,we generate random series A using corresponding random data generator and then add instantaneous phaseθinto A,i.e.,y=Ae^(jθ),to obtain simulated sea clutter series.Through a comparison of simulated sea clutter and measured sea clutter data via histogram,the validity of the proposed method is proved.

RCS analysis in the detection of a generic missile target with sea clutter background

The detection of a missile target in heavy sea clutter is a significantly challenging problem due to the clutter effects. In this paper, the radar cross sections(RCS) of a pre-assumed generic missile model is computed with multilevel fast multi-pole algorithm(MLFMA), while the RCS of ocean surface is computed by a more reduced form of the fractional Weierstrass scattering model proposed here. At last, the computed RCS of missile model is compared with that of sea surface, and then the comparisons of missile-to-ocean RCS ratios of different incident angles, incident frequencies, and polarization patterns are also presented. The discussion and comparisons of RCS of the missile and ocean surface can help us to plan and design a radar system in the application of detection of a missile target or other analogous weaker targets in the strong sea clutter background.

Radar Sea Clutter Suppression and Target Indication with a Spatial Tracking Filter

It is an important issue to study sea clutter suppression because it could interfere with the detection of targets above the sea surface severely. Spatial spectrum analyses show that the majority of sea clutter has low-frequency characteristics, compared to the high-frequency characteristics of the targets. This paper proposes a frequency-based spatial tracking filter to suppress sea clutter to facilitate targets identification. Experimental results show that the signal-to-clutter ratio can increase by more than 10 dB after filtering and the algorithm is feasible for practical use. In addition, the filtering equation can be optimized to maximize the signal-to-clutter ratio improvement. The equation parameters can also be adjusted to give a proper cut-off frequency for different targets and clutter.

Overview of radar detection methods for low altitude targets in marine environments

In this paper,a comprehensive overview of radar detection methods for low-altitude targets in maritime environments is presented,focusing on the challenges posed by sea clutter and multipath scattering.The performance of the radar detection methods under sea clutter,multipath,and combined conditions is categorized and summarized,and future research directions are outlined to enhance radar detection performance for low-altitude targets in maritime environments.

Short-time maritime target detection based on polarization scattering characteristics

In this paper,a detection method combining Cameron decomposition based on polarization scattering characteristics in sea clutter background is proposed.Firstly,the Cameron decomposition is exploited to fuse the radar echoes of full polarization channels at the data level.Due to the artificial material structure on the surface of the target,it can be shown that the non-reciprocity of the target cell is stronger than that of the clutter cell.Then,based on the analysis of the decomposition results,a new feature with scattering geometry characteristics in polarization domain,denoted as Cameron polarization decomposition scattering weight(CPD-SW),is extracted as the test statistic,which can achieve more detailed descriptions of the clutter scattering characteristics utilizing the difference between their scattering types.Finally,the superiority of the proposed CPD-SW detector over traditional detectors in improving detection performance is verified by the IPIX measured dataset,which has strong stability under short-time observation in threshold detection and can also improve the separability of feature space zin anomaly detection.

大掠射角对海雷达导引头实测回波特性分析

大掠射角下,对海雷达导引头观测到的海杂波强度激增,舰船目标检测困难。本文结合全极化雷达导引头挂飞实测数据,分析了回波幅度和相位特性。首先,采用典型分布对回波幅度分布进行拟合,并利用拟合优度对拟合效果作出评估;然后,分析了平均相位变化量。结果表明:在大掠射角条件下,雷达导引头各极化通道海杂波幅度服从K分布;海杂波与舰船回波幅度在同极化通道服从K分布,在交叉极化通道服从对数正态分布;交叉极化通道回波信杂比高于同极化通道;海杂波与舰船回波相位平均变化量小于海杂波。