Detection of small objects in clutter using a GA-RBF neural network

Detection of small objects in a radar or satellite image is an important problem with many applications. Due to a recent discovery that sea clutter, the electromagnetic wave backscatter from a sea surface, is chaotic rather than purely random, computational intelligence techniques such as neural networks have been applied to reconstruct the chaotic dynamic of sea clutter. The reconstructed sea clutter dynamical system which usually takes the form of a nonlinear predictor does not only provide a model of the sea scattering phenomenon, but it can also be used to detect the existence of small targets such as fishing boats and small fragments of icebergs by observing abrupt changes in the prediction error. We applied a genetic algorithm (GA) to obtain an optimal reconstruction of sea clutter dynamic based on a radial basis function (RBF) neural network. This GA-RBF uses a hybrid approach that employes a GA to search for the optimum values of the following RBF parameters: centers, variance, and number of hidden nodes, and uses the least square method to determine the weights. It is shown here that if the functional form of an unknown nonlinear dynamical system can be represented exactly using an RBF net (i.e., no approximation error), this GA-RBF approach can reconstruct the exact dynamic from its time series measurements. In addition to the improved accuracy in modeling sea clutter dynamic, the GA-RBF is also shown to enhance the detectability of small objects embedded in the sea. Using real-life radar data that are collected in the east coast of Canada by two different radar systems: a ground-based radar and a satellite equipped with synthetic aperture radar (SAR), we show that the GA-RBF network is a reliable detector for small surface targets in various sea conditions and is practical for real-life search and rescue, navigation, and surveillance applications     

A Model for Generating Synthetic VHF SAR Forest Clutter Images

We propose a model for generating low-frequency synthetic aperture radar (SAR) clutter that relates model parameters to physical characteristics of the scene. The model includes both distributed scattering and large-amplitude discrete clutter responses. The model also incorporates the SAR imaging process, which introduces correlation among image pixels. The model may be used to generate synthetic clutter for a range of environmental operating conditions for use in target detection performance evaluation of the radar and automatic target detection/recognition algorithms. We derive a statistical representation of the proposed clutter model's pixel amplitudes and compare with measured data from the CARABAS-II SAR. Simulated clutter images capture the structure and amplitude responses seen in the measured data. A statistical analysis shows an order of magnitude improvement in model fit error compared with standard maximum-likelihood (ML) density fitting methods.     

海杂波谱的机理及时变特性分析

针对海杂波背景下目标检测问题的实际需求,在机理分析的基础上,利用实测数据对海杂波谱的时变特性进行了分析。首先,分析了波束照射区域内由海表面波浪运动引起的多普勒频移和展宽现象,以及随雷达工作参数之间的依赖关系;然后,对已有海杂波谱机理研究结果进行了分析和总结。在此基础上,利用加窗的周期图法估计得到海杂波的时间-多普勒谱,进而从相关时间的统计特性、谱宽与时域海杂波拖尾程度的依赖关系两个层面对海杂波谱的时变特性进行了分析。分析结果可为海杂波谱建模、海杂波抑制及目标检测方法设计提供理论指导。     

HRR Detector for Slow-Moving Targets in Sea Clutter

The radar detection of targets in the presence of sea clutter has historically relied upon the radial velocity of targets with respect to the radar platform either by exploiting the relative target Dopplers (for targets with sufficient radial velocity) or by discerning the paths targets traverse from scan to scan. For targets with little to no radial velocity component, though, it can become quite difficult to differentiate targets from the surrounding sea clutter. This paper addresses the detection of slow-moving targets in sea clutter using a high resolution radar (HRR) such that the target has perceptible extent in range. Under the assumption of completely random sea clutter spikes based on an epsiv-contaminated mixture model with the signal and clutter powers known, optimal detection performance results from using the likelihood ratio test (LRT). However, for realistic sea clutter, the clutter spikes tend to be a localized phenomenon. Based upon observations from real radar data measurements, a heuristic approach exploiting a salient aspect of the idealized LRT is developed which is shown to perform well when applied to real measured sea clutter.     

一种基于FPGA的海杂波产生器设计

海杂波是反舰导弹末制导雷达回波的主要背景噪声,在末制导雷达模拟器的设计中,海杂波产生器是一个重要组成部分。在研究海杂波噪声概率分布密度的基础上,给出了一种基于FPGA技术的海杂波产生器的设计方案,并利用Altera公司的cyclone II系列芯片和QuartusII开发软件对设计进行了仿真验证。采用FPGA技术可以方便地对设计方案、海杂波的分布形式、数据量大小进行修改。仿真结果表明,该设计能够产生符合要求的海杂波信号,并且具有结构简单、集成度高、易于修改等特点。     

基于混合 MOM-PO的复合电磁散射问题分析

海面(或地面)环境中目标电磁散射特性,对实际战场环境下军用目标的雷达探测、雷达特性形成以及雷达目标识别等技术具有基础支撑作用。因此,快速准确地分析目标和粗糙面复合电磁散射特性具有重要理论意义和应用价值。文章采用基于矩量法(MOM)和物理光学法(PO)的混合方法MOM-PO分析了目标和粗糙面复合电磁散射问题。与传统的矩量法相比,该方法在保证精确度的前提下大大加快了计算速度。     

A Quantitative Analysis of Sea Clutter Decorrelation with Frequency Agility

A brief statement of the sea clutter problem in surface-search radar operation illustrates the need for some form of signal-to-clutter enhancement. Post-detection integration used in the simpler radars is limited by the pulse-to-pulse correlation of the clutter. Analysis of the effect of changing frequency from pulse to pulse leads to an expression for the correlation between pulses in the sequence. Knowing this correlation, the reduction in the fluctuating clutter component produced by integration can be determined. This is described by an equivalent number of independent pulses, Nc. For the particular case of sinusoidal modulation of the transmitted frequency, N6 is computed. The critical dependecne of Nc upon the modulating frequency fm is illustrated by spectrum photographs. Choice of an optimum fm is discussed. The results of computations of N4 for optimum fm are presented as a family of normalized curves. These data permit the tradeoff of the radar parameters against their quantitative effect on radar performance.     

Vector subspace detection in compound-Gaussian clutter. Part II: performance analysis

For pt. I see ibid., vol. 38, no. 4, p. 1295 (2002). In this second part we deal with the problem of detecting subspace random signals against correlated non-Gaussian clutter modeled by the compound-Gaussian distribution. In the first part of the paper, we derived the optimum Neyman-Pearson (NP) detector, the generalized likelihood ratio test (GLRT), and a constant false-alarm rate (CFAR) detector; we also provided some interesting interpretations of them. In this second part, these detectors are tested against both simulated data and measured high resolution sea clutter data to investigate the dependence of their performance on the various clutter and signal parameters. Numerical examples concern a space-time adaptive processing (STAP) scenario and a ground-based surveillance radar system scenario.     

基于实测数据的海杂波时空相关性分析

海杂波的相关特性分为时间相关性和空间相关性,二者均与雷达系统参数、环境条件等多种因素有关。文章利用X波段雷达实测海杂波数据,重点研究了不同极化条件下海杂波的时间相关性、高低典型海况和不同入射余角条件下的海杂波距离向和方位向空间相关性。经大量实测数据验证表明,极化方式对海杂波强时间相关性影响较小,海杂波距离向空间相关性受海况影响较大、方位向相邻分辨单元空间相关性较弱,这些结论对于海杂波中目标检测方法优化设计具有重要意义。     

A robust exponential mixture detector applied to radar

Exponential mixture probability density functions (pdfs) are shown to be useful models of radar sea clutter. The variability of certain parameters leads to estimation error and degradation in the performance of detection algorithms derived from this model. Robust implementations are introduced by assuming that parameters are known within certain intervals and selecting values to prevent an excessive number of false alarms. An empirical study demonstrates an average 6-9 dB gain in comparison with a constant false-alarm rate (CFAR) processor     

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。     

IPIX雷达海尖峰统计特性研究

根据雷达海尖峰构成原理，以K分布为模型，提出了海尖峰的统计特性分析方法，并使用该方法对IPIX雷达实测海杂波数据进行了统计特性分析，分析结果证明了该方法的有效性。     

无线电引信抗海杂波干扰方法

无线电引信抗海杂波的能力决定了舰空导弹无线电引信低空和超低空工作性能,针对海杂波对无线电引信的影响,分析了海面回波的平均功率、海面散射系数、海杂波的多普勒频谱等海杂波特性,提出了无线电引信抗海杂波干扰方法。     

海杂波条件异方差特性分析与波动信息提取

由于低擦地角、高海况等易引起雷达海杂波序列的局部剧烈波动,传统的统计分布模型难以描述突然出现的具有冲激特性的强回波,因此,针对这一问题,将广义自回归条件异方差(Generalized Auto Regressive Conditional Heteroskedasticity,GARCH)模型引入海杂波建模中,通过 GARCH模型阶数步进搜索结合残差序列方差齐性检验,实现了海杂波数据的波动信息提取。经 X波段雷达实测数据验证,所提出的波动信息提取方法,可以很好地提取实测海杂波数据在局部区域或时间段内的波动信息,为特征检测方法设计提供有效的特征支撑。     

Adaptive Clutter Suppression in Step Scan Radars

Clutter echoes with unknown power spectra (from weather, sea, chaff disturbances) can be suppressed only adaptively. The use of the discrete Fourier transform (DFT) for clutter suppression in step scan radars is investigated by use of a clutter model that is derived in analogy to measured clutter data of a radar with a rotating antenna.     

MTI Optimization in a Multiple-Clutter Environment

A means of optimizing a moving target indicator (MTI) filter for rejecting several types of clutter, which are generated by different mechanisms such as by rain or the ground, is formulated. lt is found that the optimal performance of such a filter depends on the spectral density functions, average radar cross sections, and the relative mean Doppler frequencies of each type of clutter. lt is shown that the optimal improvement factor of such a filter is bounded by the weighted average (weighted in accordance with the radar cross sections of the clutter types) of the improvement factor for the individual clutter type. lt is also shown that the improvement factor of such a filter is a function of the relative mean Doppler frequency f0 between the clutter types. As f0 increases, the performance of the MTI system degrades. The worst improvement factor occurs when f0 is equal to half of the radar pulse-repetition frequency (PRF).     

Generalized radar clutter model

A commonly used density model for radar clutter is chi-square for power, or, equivalently, Rayleigh for amplitude. However, for many modern high resolution radar systems, this density underestimates the tails of the measured clutter density. Log normal and Weibull distributions have proved to be better suited for the clutter in these high resolution radars. Generalizing the chi-square density by replacing it with the noncentral chi-square density and allowing the mean power level (the noncentrality parameter) to vary, we can both suitably shape the clutter density to produce larger tails and model the fluctuation of the average clutter power, commonly referred to as speckle. The resulting form, although appearing cumbersome, readily allows for efficient and accurate computations of the probability of detection in clutter     

Coherent detection of radar targets in a non-gaussian background

The problem of detecting radar targets against a background of coherent, correlated, non-Gaussian clutter is studied with a two-step procedure. In the first step, the structure of the amplitude and the multivariate probability density functions (pdfs) describing the statistical properties of the clutter is derived. The starting point for this derivation is the basic scattering problem, and the statistics are obtained from an extension of the central limit theorem (CLT). This extension leads to modeling the clutter amplitude statistics by a mixture of Rayleigh distributions. The end product of the first step is a multidimensional pdf in the form of a Gaussian mixture, which is then used in step 2. The aim of step 2 is to derive both the optimal and a suboptimal detection structure for detecting radar targets in this type of clutter. Some performance results for the new detection processor are also given     

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.     

A novel target detection approach based on adaptive radar waveform design

To resolve problems of complicated clutter, fast-varying scenes, and low signal-clutterratio (SCR) in application of target detection on sea for space-based radar (SBR), a target detection approach based on adaptive waveform design is proposed in this paper. Firstly, complicated sea clutter is modeled as compound Gaussian process, and a target is modeled as some scatterers with Gaussian reflectivity. Secondly, every dwell duration of radar is divided into several sub-dwells. Regular linear frequency modulated pulses are transmitted at Sub-dwell 1, and the received signal at this sub-dwell is used to estimate clutter covariance matrices and pre-detection. Estimated matrices are updated at every following sub-dwell by multiple particle filtering to cope with fast-varying clutter scenes of SBR. Furthermore, waveform of every following sub-dwell is designed adaptively according to mean square optimization technique. Finally, principal component analysis and generalized likelihood ratio test is used for mitigation of colored interference and property of constant false alarm rate, respectively. Simulation results show that, considering configuration of SBR and condition of complicated clutter, 9 dB is reduced for SCR which reliable detection requires by this target detection approach. Therefore, the work in this paper can markedly improve radar detection performance for weak targets.