A general evaluation system for optimal selection performance of radar clutter model

The optimal selection of radar clutter model is the premise of target detection,tracking,recognition,and cognitive waveform design in clutter background.Clutter characterization models are usually derived by mathematical simplification or empirical data fitting.However,the lack of standard model labels is a challenge in the optimal selection process.To solve this problem,a general three-level evaluation system for the model selection performance is proposed,including model selection accuracy index based on simulation data,fit goodness indexs based on the optimally selected model,and evaluation index based on the supporting performance to its third-party.The three-level evaluation system can more comprehensively and accurately describe the selection performance of the radar clutter model in different ways,and can be popularized and applied to the evaluation of other similar characterization model selection.

Ray tracing/correlation approach to estimation of surface-based duct parameters from radar clutter

This paper describes a technique to estimate surface-based duct parameters by using a simple ray tracing/correlation method. The approach is novel in that it incorporates the Spearman rank-order correlation scheme between the observed surface clutter and the surface ray density for a given propagation path. The simulation results and the real data results both demonstrate the ability of this method to estimate surface-based duct parameters. Compared with the results obtained by a modified genetic algorithm combined with the parabolic wave equation, the results retrieved from the ray tracing/correlation scheme show a minor reduction in accuracy but a great improvement on computation time. Therefore the ray tracing/correlation method might be used as a precursor to more sophisticated and slower techniques, such as genetic algorithm and particle filters, by narrowing the parameter search space and providing a comprehensive and more efficient estimation algorithm.

Inversion for atmosphere duct parameters using real radar sea clutter

This paper addresses the problem of estimating the lower atmospheric refractivity （M profile） under nonstandard propagation conditions frequently encountered in low altitude maritime radar applications. The vertical structure of the refractive environment is modeled using five parameters and the horizontal structure is modeled using five parameters. The refractivity model is implemented with and without a priori constraint on the duct strength as might be derived from soundings or numerical weather-prediction models. An electromagnetic propagation model maps the refractivity structure into a replica field. Replica fields are compared with the observed clutter using a squared-error objective function. A global search for the 10 environmental parameters is performed using genetic algorithms. The inversion algorithm is implemented on the basis of S-band radar sea-clutter data from Wallops Island, Virginia （SPANDAR）. Reference data are from range-dependent refractivity profiles obtained with a helicopter. The inversion is assessed （i） by comparing the propagation predicted from the radar-inferred refractivity profiles with that from the helicopter profiles, （ii） by comparing the refractivity parameters from the helicopter soundings with those estimated. This technique could provide near-real-time estimation of ducting effects.

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.

Space-time clutter model for airborne bistatic radar with non-Gaussian statistics

To validate the potential space-time adaptive processing （STAP） algorithms for airborne bistatic radar clutter suppression under nonstationary and non-Gaussian clutter environments, a statistically non-Gaussian, space-time clutter model in varying bistatic geometrical scenarios is presented. The inclusive effects of the model contain the range dependency of bistatic clutter spectrum and clutter power variation in range-angle cells. To capture them, a new approach to coordinate system conversion is initiated into formulating bistatic geometrical model, and the bistatic non-Gaussian amplitude clutter representation method based on a compound model is introduced. The veracity of the geometrical model is validated by using the bistatic configuration parameters of multi-channel airborne radar measurement （MCARM） experiment. And simulation results manifest that the proposed model can accurately shape the space-time clutter spectrum tied up with specific airborne bistatic radar scenario and can characterize the heterogeneity of clutter amplitude distribution in practical clutter environments.

Clutter suppression for hypersonic vehicle-borne radar with frequency diverse array

The seriously range-ambiguous clutter is one of the main problems in clutter suppression for hypersonic vehicle-borne forward-looking radar. An approach based on the frequency diverse array (FDA) technique is proposed to mitigate the range ambiguous clutter. The frequency increment is designed to distinguish the clutter at ambiguous ranges and suppress the clutter by using a subspace projection algorithm. On the platform with high altitude or limited array antennas, the proposed method performs better for its independence of the elevation degrees-of-freedom (DOF). Finally, simulation results verify the effectiveness of the proposed method.

HF radar sea clutter rejection by nonlinear projections

In the background of signal detection for high frequency （I/F） radar, the sea clutter is quite significant and can mask some weak target signals. A new clutter rejection method named “nonlinear projection” is given to improve the SNR of the target. This approach is based on the recent observation that HF sea clutter may be modeled as a nonlinear deterministic dynamical system. After approximating the multidimensional reconstruction of the clutter by a low-dimensional attractor, projections onto this attractor can separate the clutter from other components. Real sea clutter, simulated target data and real target data are used to show that a nonlinear clutter rejection method is a promising technique to suppress sea clutter and enhances target detection.

Study on Clutter Model and Characteristics of Airborne Radar with Parabolic Conformal Phased Array

The studies on clutter modeling and suppression of airborne radar with a parabolic conformal array are uncommon due to the complexity of this type of antenna array configuration.The correct understanding of clutter characteristics for airborne radar with a parabolic conformal antenna array is the prerequisite and foundation of optimal suppression of this type of clutter.This paper establishes the model of clutter echo of airborne parabolic conformal phased array radar and analyzes the structure characteristics and the distribution features of this type of clutter.The simulation results show that this type of clutter has the following characteristics：1） The main lobe on the azimuth is seriously broadened,2） the power spectrum presents strong heterogeneity,and 3） the freedom degrees are high.Based on the existing related clutter suppression methods,we verified the correctness of the constructed clutter model.This work has an important guidance to further study on clutter suppression methods in airborne parabolic conformal array radar.

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.

ON CLUTTER DOF FOR PHASED ARRAY AIRBORNE EARLY ARNING RADARS

In recent years,considerable attention has been paid to adaptive clutter suppressionfor airborne early warning(AEW)radars.A necessary condition for efficient clutter suppressionis that the number of adaptive degrees of freedom(DOF)is no less than that of clutter DOF.This paper analyzes the DOF of clutter for phased array AEW radars.The new results obtainedhere are helpful to design an adaptive system for clutter suppression.

Signal decomposition of HF radar maneuvering targets by using S^2-method with clutter rejection

Multiple maneuvedng targets signal processing in high frequency radar is challenging due to the following difficulties： the interference between signals is severe because of significant spread of the target Doppler spectrum, the low signal to clutter ratio （SCR） environment degrades the performance of signal process- ing algorithms. This paper addresses this challenging problem by using an S2-method and an adaptive clutter rejection scheme. The proposed S2-method improves the S-method by eliminating inter- ference between signals, and thus it enables multi-target signals to be reconstructed individually. The proposed adaptive clutter rejec- tion scheme is based on an adaptive notch filter, which is designed according to the envelop of the clutter spectrum. Experiments with simulated targets added into radar sea clutter echo and real air target data illustrate the effectiveness of the proposed method.

Suppression of Log-Normal Distributed Weather Clutter Observed by an S-Band Radar

We have observed weather clutter containing targets (ships) using an S-band radar with a frequency 3.05 GHz, a beam width 1.8°, and a pulsewidth 0.5 μs. To investigate the weather clutter amplitude statistics, we introduce the Akaike Information Criterion (AIC). We have found that the weather clutter amplitudes obey the log-normal, Weibull, and log-Weibull distributions with the shape parameters of 0.308 to 0.470, 4.42 to 4.51, and 15.91 to 16.44, respectively, for small data within the beam width of an antenna. We have proposed the log-normal/CFAR circuit modified a Cell-Averaging (CA) LOG/CFAR circuit. It is found that weather clutter is suppressed with improvement of 51.58 dB by log-normal/CFAR. As a result, we have showed that weather clutter observed by S-band radar does not obey the Rayleigh distribution and our log-normal/CFAR circuit has an effect on suppression of clutter and detection of target, while conventional LOG/CFAR circuit does not. In addition, if our circuit can be realized, we will have an advantage economically.

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.

Waveform Design for Cognitive Radar with Deterministic Extended Targets in the Presence of Clutter

Adjusting radar transmitted waveform to its environment is one of the most important roles in cognitive radar;having the capability of updating transmitted waveforms in different applications is a key point. It has been shown in many studies that if the waveform is designed according to the target and clutter characteristics, the detection performance will improve significantly. The uncertainty of the target radar signatures decreases via maximizing MI and the probability of extended target detection is increases via maximizing SNR. In this paper, a waveform design approach based on maximizing both SNR and MI and with regard to target and clutter shape is presented. The detection performance for proposed waveform is compared with previous proposed waveforms. The present paper compares different scenarios of target and clutter and using the probability of detection as a cost function to investigate the advantages and disadvantages of each waveform in different scenarios which are mainly discussed in this text. The desired waveform for cognitive radar is selected based on simultaneously making compromises between SNR and MI, which plays an important role in cognitive radar systems and based on the assumption addressed in the text, the best waveform transmitted into the environment.

A NEW METHOD TO COMPENSATE CLUTTER RANGE DEPENDENCE FOR FORWARD LOOKING AIRBORNE RADARS

The clutter direction-Doppler curves are not aligned on the near range bins for forward looking airborne radar. As a result, the performance of clutter suppression by Space-Time Adaptive Processing (STAP) degrades greatly because of the clutter range dependence. To deal with this problem, a new compensated method is proposed in this paper. The method rebuilds the clutter covariance matrix based on spatial high resolution Minimum Variance Distortionless Response (MVDR) spectrum, and then finds a matrix to transform the covariance matrix of short-range gate to the referred far-range gate. The method can compensate the clutter range dependence well. The simulation results show validity of the method.

基于杂波拖尾分布的雷达无人机检测性能分析

固定翼无人机(unmanned aerial vehicle,UAV)给雷达低空监视提出了严峻挑战。分析雷达对固定翼UAV的检测性能,可为雷达UAV检测能力评估和技术升级提供重要参考。本文结合雷达探测低空固定翼UAV外场实测数据,首先分析了低空固定翼UAV雷达接收信号幅度统计分布,采用多项式对杂波拖尾导致的虚警概率进行拟合建模;然后,根据虚警概率分布得到雷达检测门限;进而根据UAV回波+杂波幅度分布理论推导得到雷达检测概率;最后,将理论分析性能与传统性能分析结果、雷达实际检测性能进行对比。结果表明,采用多项式对杂波拖尾导致的虚警概率进行单独建模,由此获得的雷达检测门限精度更高,从而使雷达UAV检测性能分析结果较传统性能分析结果更准确。

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。

一种基于谱连续的极化-多普勒气象雷达信号重构方法

谱极化滤波技术广泛应用于气象雷达杂波抑制中,但是当地杂波与降雨目标混叠时,这些方法在滤除杂波的同时会损失气象信息。针对这一问题,提出一种基于谱连续的极化-多普勒气象雷达信号重构方法。该方法利用气象回波和杂波在距离-多普勒图上的特征差异实现气象目标的保留和杂波的滤除。具体是利用气象目标的多普勒速度和谱宽的空间连续性,采用多项式拟合和高斯拟合的方法补偿降雨区域。业务气象雷达实测数据验证了所提方法的有效性。

基于稀疏恢复的双基地机载雷达杂波抑制方法

基于杂波谱稀疏恢复(sparse recovery,SR)的空时自适应处理(space-time adaptive processing,STAP)技术对训练样本个数要求低,适用于杂波非均匀环境。然而在双基地配置下,杂波脊不落在均匀网格点上,这将造成网格失配,严重影响SR-STAP方法性能。针对双基地机载雷达杂波的网格失配问题,提出了一种利用杂波脊先验信息划分非均匀网格的SR-STAP方法,所提方法首先由导航系统或参数估计方法获得待检测单元的杂波空时轨迹,然后根据杂波空时轨迹和均匀划分的空间频率确定初始归一化多普勒频率集合,接着根据可调参数更新归一化多普勒频率集合,最后构造对应的非均匀字典。所提方法可适用于任意双基地配置情况。仿真结果表明,应用非均匀字典的SR-STAP方法的杂波抑制性能较传统均匀字典有较大提升,并能在非理想条件下表现稳健。

基于模型阶数选择准则的稳健杂波边缘检测方法

在雷达目标自适应检测问题当中,辅助数据存在杂波边缘的情况将导致杂波协方差矩阵(CCM)的估计性能出现严重下降,极大地影响目标检测性能。为了解决这一问题,该文提出一种杂波边缘检测方法,能够对辅助数据中杂波边缘数量与位置进行自适应判别。首先,假定辅助数据中存在杂波边缘,采用模型阶数选择算法和最大似然估计方法完成杂波参数估计,其中杂波边缘位置由循环搜索方法得到。之后将杂波参数估计结果应用到检测算法中,通过广义似然比检验方法来判断杂波边缘是否存在。此外为了进一步提升算法在小样本条件下的稳健性,引入CCM的特殊结构作为先验知识,将算法推广至CCM为斜对称、谱对称以及中心对称3种结构的情况。仿真及实测数据均表明该文所提算法能够高效地识别雷达辅助数据中的杂波边缘数量和位置,先验知识的引入更能进一步改善算法在辅助数据量较小时的性能。