The Effect of Staggered PRF's on MTI Signal Detection

Long-range surveillance radars use MTI techniques to detect moving targets in a clutter background. The transmitter PRF is usually staggered to eliminate the blind speeds due to aliasing of the target and clutter spectra. A spectral analysis of the target and clutter signals is performed for the case of nonuniform sampling, and it is shown that the clutter spectral density continues to fold over at the basic PRF, but the signal spectrum becomes dispersed in frequency, which means that an MTI rader will never be completely blind to moving targets.     

Stap using knowledge-aided covariance estimation and the fracta algorithm

In the airborne space-time adaptive processing (STAP) setting, a priori information via knowledge-aided covariance estimation (KACE) is employed in order to reduce the required sample support for application to heterogeneous clutter scenarios. The enhanced FRACTA (FRACTA.E) algorithm with KACE as well as Doppler-sensitive adaptive coherence estimation (DS-ACE) is applied to the KASSPER I & II data sets where it is shown via simulation that near-clairvoyant detection performance is maintained with as little as 1/3 of the normally required number of training data samples. The KASSPER I & II data sets are simulated high-fidelity heterogeneous clutter scenarios which possess several groups of dense targets. KACE provides a priori information about the clutter covariance matrix by exploiting approximately known operating parameters about the radar platform such as pulse repetition frequency (PRF), crab angle, and platform velocity. In addition, the DS-ACE detector is presented which provides greater robustness for low sample support by mitigating false alarms from undernulled clutter near the clutter ridge while maintaining sufficient sensitivity away from the clutter ridge to enable effective target detection performance     

HF multipath passive single site radio location

This paper considers the problem of passive geolocation for the case of HF multipath propagation. A new technique is developed for the estimation of interpath time delay applying the multiple signal classification (MUSIC) superresolution spectral estimation method. The technique samples the signals received by two spatially separated antennas to compute the normalized MUSIC cepstrum. The method is applied to experimental data in a preliminary proof-of-concept analysis     

Track formation with bearing and frequency measurements in clutter

Target motion analysis from a narrowband passive sonar that yields bearing and frequency measurements in the presence of false detections (clutter) in a low-SNR (low signal-to-noise ratio) environment is discussed. The likelihood function used to compute the maximum likelihood estimation of the track parameters (localization and frequency) incorporates the false alarms via the probabilistic data association technique. The Cramer-Rao lower bound is calculated and results obtained from simulations are shown to be compatible with it. A test of track acceptance is also presented     

Resolution of Closely Spaced Optical Targets Using MLE and MEM

The capabilities of the maximum likelihood estimator (MLE) and the maximum entropy method (MEM) in resolving closely spaced optical point targets are compared using Monte Carlo simulation results for two different examples. It is found that the MEM is very sensitive to the noise and that the MLE performs better than the MEM in both examples.     

基于先验知识及其定量评估的自适应杂波抑制研究

 为了改善训练样本数受限的非均匀杂波环境中的系统检测性能,研究了基于先验知识及其定量评估的自适应杂波抑制算法。提出了使用经真实杂波信息白化后的先验杂波协方差矩阵与单位矩阵之差的谱范数,来定量评估杂波先验知识的准确程度,并给出了真实杂波协方差矩阵未知时的矩阵谱范数估计方法。结合先验知识定量评估结果,获得了具有先验知识约束时的杂波协方差矩阵最大似然估计方法。分别基于多脉冲相参雷达以及空时自适应雷达进行了杂波建模,在此基础之上分析了算法性能。仿真结果证实了该算法优于使用样本协方差矩阵及先验杂波信息形成杂波抑制权值的性能。     

The Shape of Doppler Spectra from Precipitation

From October 1982 through May 1983 an extensive weather clutter registration program was executed near the Dutch coast. Coherent echo series of 2 s were obtained from a cluster of adjacent antenna pencil beams every 10 or 15 min., mainly between 16:00 and 08:30 h and on the weekends. The beam cluster was pointed toward the intensity maximum of the clutter volume. The radar operated at 5650 MHz. Spectra with 10 Hz Doppler resolution have been computed by averaging over 19 discrete Fourier transforms of overlapping and tapered subseries of 200 echo vectors. To quantify the deviation from a Gaussian shape a spectral variability is defined which is computed for every estimated spectrum. It is found that the deviation from Gaussian is considerable in about one-fourth of the spectra. A selection of "typical worst case" spectra is presented.     

分数傅立叶变换用于抑制SAR杂波背景检测慢速动目标

慢速运动目标在时、空、频域上都落入主杂波区。利用单通道SAR图像中静止背景的信息抑制静止杂波,可改善检测动目标的性能。分数傅立叶变换是线性变换,不存在交叉项,采用分数傅立叶变换搜索匹配动目标信号,使其能量汇聚。对称计算旋转角正负对称的分数傅立叶变换,在两个对称的分数傅立叶域中得到两个复信号,这两个复信号中静止背景的模处处相同,而包含动目标的区域,模的幅度有很大差别,计算对称的分数傅立叶域信号对应位置模的差,取绝对值,可对消静止背景,敏锐地检测动目标。实测数据表明本算法有效。     

一种机动多目标雷达视频信号模拟器的设计

给出了一种机动多目标雷达视频信号模拟器的软硬件设计方案,它可实时输出所需的多个动目标雷达视频信号,雷达信号的类型、目标的数量、目标的回波特性、目标的运动特性、杂波的类型及参数等均可方便地进行设置。该模拟器可满足各种雷达信号处理算法(如杂波抑制、恒虚警检测、动目标跟踪、多基地数据融合等)的测试与效果分析,以及对雷达信号处理机等进行性能调试与测试的需要。     

On Clutter Modeling and the Spectra of Two-Dimensional Gauss-Markov Random Signals

The spectral properties of two-dimensional isotropic clutter signals are examined for the cases in which 1) the clutter has an exponential spatial autocorrelation function, and 2) the clutter is a two-dimensional Gauss-Markov random signal. The one- and twodimensional power spectral densities before and after antenna filtering are obtained, and some of the differences and similarities between these two models are discussed in the context of spectral analysis.     

利用神经网络的海杂波幅度分布参数估计方法

海杂波是制约对海雷达探测性能的主要因素之一,掌握其特性,具有十分重要的意义。经典海杂波统计模型在参数估计方法上以传统统计学理论为基础,在样本数较少的情况下,估计结果往往较差,导致建模准确度下降。此外,在复杂非均匀探测背景下,难以实现海杂波模型参数的准确实时估计。针对该问题,文章将深度神经网络模型引入海杂波参数估计领域,通过构建合理的模型,使其具备海杂波幅度分布模型的高精度参数估计能力。该方法采用直方图统计的方法进行数据预处理,合理划分输入数据标签的分组区间,构建数据集训练神经网络,并利用测试数据得到神经网络估计结果。仿真数据和X波段IPIX雷达实测数据验证结果表明,与传统数理统计估计方法相比,该算法明显提升了海杂波统计模型参数估计精度。     

扫描模式航管监视雷达风电场杂波检测与抑制

近年来,全球风力发电装机容量呈指数增长。研究表明,风轮机对其附近的航管(ATC)监视雷达会产生严重影响。风轮机杂波的有效检测及抑制,对于保证空中交通安全具有重要意义。首先提出了基于回波谱宽特征的航管监视雷达的风轮机杂波检测方法。针对扫描模式下航管监视雷达频谱分辨率较低的问题,将基于自回归(AR)模型的超分辨率方法和质量中心的概念应用于雷达回波的快速谱宽和谱中心估计算法中,提高谱宽估计的精度。其次针对扫描模式下的风轮机回波数据不是一个完整周期数据的问题,基于缺省数据幅度和相位估计(GAPES)算法实现了扫描模式下风轮机雷达回波缺省数据的估计,而后利用风轮机杂波的周期性抑制风轮机杂波。该算法实现了风轮机杂波的有效检测和抑制,并且其不受限于风轮机与飞机目标在同一个距离单元的情况。仿真结果验证了所提方法的有效性。     

小样本下分位数函数的Bootstrap置信区间估计

航空产品试验一般为小样本试验,为了分析小样本情况下的试验数据,结合以概率加权矩为约束条件的最大熵法和求解置信区间及置信带的Bootstrap方法,提出了一种估计小样本试验件母体分位数函数置信区间的方法。最大熵法在矩约束下能够估计样本的密度函数,而以概率加权矩为约束条件的最大熵法能够针对小样本直接给出分位数的无偏估计,无需由密度函数积分得到累积分布函数,再进行转化得到分位数函数。Bootstrap方法求解置信区间具有不依赖于数据分布的优点,具有广泛的应用范围。     

一种FMCW SAR地面运动目标谱图域参数估计方法

对调频连续波(FMCW)合成孔径雷达(SAR)地面运动目标的参数估计方法进行了研究,采用相位中心偏置天线(DPCA)技术对地杂波进行抑制,分析了载机及地面运动目标连续运动对回波信号的影响,推导了采用DPCA技术引入的回波慢时间包络(STE)项与地面运动目标参数之间的关系。在此基础上,提出了一种地面运动目标谱图域参数估计方法,该方法首先利用Radon变换在谱图域估计导致回波信号距离走动的目标等效径向速度,并对距离走动进行校正;其次,在谱图域中提取运动目标回波幅度,根据STE项引起的回波幅度变化与目标方位向速度之间的关系,估计目标的方位向速度,并进一步求解相应的目标径向速度。所提方法能够在谱图域完成地面运动目标二维速度估计,最后的仿真实验验证了所提方法的有效性和可行性。     

基于嵌入式仿真的雷达训练系统设计

介绍了嵌入式仿真技术及其发展,将嵌入式仿真与雷达模拟训练相结合,构成了能够嵌入到机械扫描雷达实装的模拟训练系统。描述了对嵌入式仿真训练系统的结构组成以及部分模块的功能,研究了模拟雷达视频回波数据的方法和模型,包括目标回波、地物杂波、海杂波、气象杂波、有源干扰和接收机内部噪声,利用数学模型计算回波的强度、方位、距离等特性,调制实际录取的回波数据,生成与态势设置参数相应的模拟回波数据,能够对信号处理操作和抗干扰操作做出响应。通过对视频回波进行仿真,由终端显示画面可知模拟的回波数据具有较高的逼真度,经测试模拟视频回波能够被雷达显控终端识别。     

Spectral-domain covariance estimation with a priori knowledge

A knowledge-aided spectral-domain approach to estimating the interference covariance matrix used in space-time adaptive processing (STAP) is proposed. Prior knowledge of the range-Doppler clutter scene is used to identify geographic regions with homogeneous scattering statistics. Then, minimum-variance spectral estimation is used to arrive at a spectral-domain clutter estimate. Finally, space-time steering vectors are used to transform the spectral-domain estimate into a data-domain estimate of the clutter covariance matrix. The proposed technique is compared with ideal performance and to the fast maximum likelihood technique using simulated results. An investigation of the performance degradation that can occur due to various inaccurate knowledge assumptions is also presented     

A Model for the Radar Echo from a Random Collection of Rotating Dipole Scatterers

A theoretical model for the radar echo from a random collection of dipole scatterers is presented. The analysis of the model takes into account the effects of scatterer rotation which have been neglected in previous related work. It is shown that rotational motion of the scaterers can have significant effects upon the echo waveform. The fluctuating characteristics of clutter echoes are also investigated. The theory and some experimental results in the literature are shown to be in relatively good agreement.     

Scatter factor confidence interval estimate of least square maximum entropy quantile function for small samples

Classic maximum entropy quantile function method (CMEQFM) based on the probabil-ity weighted moments (PWMs) can accurately estimate the quantile function of random variable on small samples, but inaccurately on the very small samples. To overcome this weakness, least square maximum entropy quantile function method (LSMEQFM) and that with constraint condition (LSMEQFMCC) are proposed. To improve the confidence level of quantile function estimation, scatter factor method is combined with maximum entropy method to estimate the confidence inter-val of quantile function. From the comparisons of these methods about two common probability distributions and one engineering application, it is showed that CMEQFM can estimate the quan-tile function accurately on the small samples but inaccurately on the very small samples (10 sam-ples); LSMEQFM and LSMEQFMCC can be successfully applied to the very small samples;with consideration of the constraint condition on quantile function, LSMEQFMCC is more stable and computationally accurate than LSMEQFM; scatter factor confidence interval estimation method based on LSMEQFM or LSMEQFMCC has good estimation accuracy on the confidence interval of quantile function, and that based on LSMEQFMCC is the most stable and accurate method on the very small samples (10 samples).     

Statistical analysis of real clutter at different range resolutions

A statistical analysis is presented of real radar clutter data collected using the McMaster I FIX radar in 1998 and stored in the Grimsby database. We first show the deviations of the amplitude statistics from the Rayleigh model and the suitability of the K- and Weibull-distribution for the first-order amplitude statistical characterization. Thus we focus on the I and Q components of the available data and study their statistical compatibility with the compound Gaussian model. Towards this goal it has been necessary devising appropriate testing procedures; in particular, with reference to the higher order statistics agreement, we have designed a validation procedure involving the clutter representation into generalized spherical coordinates. Remarkably the results have confirmed the suitability of the spherically invariant random processes (SIRPs) for the correct modeling of the radar clutter. Finally we have performed a spectral analysis highlighting the close matching between the estimated clutter spectral density and the exponential model.     

Reliability analysis based on a novel density estimation method for structures with correlations

Estimating the Probability Density Function (PDF) of the performance function is a direct way for structural reliability analysis,and the failure probability can be easily obtained by integration in the failure domain.However,efficiently estimating the PDF is still an urgent problem to be solved.The existing fractional moment based maximum entropy has provided a very advanced method for the PDF estimation,whereas the main shortcoming is that it limits the application of the reliability analysis method only to structures with independent inputs.While in fact,structures with correlated inputs always exist in engineering,thus this paper improves the maximum entropy method,and applies the Unscented Transformation (UT) technique to compute the frac tional moments of the performance function for structures with correlations,which is a very efficient moment estimation method for models with any inputs.The proposed method can precisely estimate the probability distributions of performance functions for structures with correlations.Besides,the number of function evaluations of the proposed method in reliability analysis,which is determined by UT,is really small.Several examples are employed to illustrate the accuracy and advantages of the proposed method.