空间目标RCS特性的分形分析

讨论了空间目标RCS特性分形分析的2种方法:布朗运动模型方法和小波变换方法,并针对RCS数据进行了处理。结果表明,小波变换方法计算的分形维数更稳定,而且能够区分雷达测量数据的正常与异常,明显优于布朗运动模型方法。最后指出了RCS实测数据不是严格意义上的自相似过程。     

飞行器RCS近场测试技术研究进展与工程应用

雷达散射截面(RCS)测试是隐身技术和目标特性研究的基础。无论是研究物体的电磁散射特性还是研制具有突防能力的隐身武器系统,RCS测试都具有非常重要的意义。通过RCS测试可以验证电磁散射计算的理论和方法,更重要的是,对部分飞行器目标进行电磁散射理论计算非常困难,而通过测试可以直观地获得目标的电磁散射特性数据,从而避开复杂的电磁仿真计算。与外场、紧缩场RCS测试方法相比,近年来得到广泛应用与发展的RCS近场测试方法在飞行器目标的散射特性测试方面具有效率高、成本低的优势。介绍了飞行器RCS测试评估方法,综述了国内外RCS近场测试技术研究的最新进展与工程应用实例,分析展望了飞行器RCS近场测试技术面临的机遇与挑战。     

飞机RCS动态数据的统计模型研究

动态测量是获取飞机电磁散射特性的一个必要手段,由于飞机飞行时姿态变化及背景等因素的影响,RCS动态测量数据呈现出剧烈的起伏。本文首先分析了离散数据统计建模与参数获取的方法,然后就某型号目标的RCS数据,应用理论模型对其进行拟合,得到其典型视向RCS的近似分布规律。     

非合作目标动态RCS仿真方法

针对非合作目标难以开展动态测量的问题,根据空气动力学原理提出了一种非合作目标动态雷达散射截面（RCS）仿真方法。该方法首先建立测量背景下典型飞行航路模型,然后计算雷达视线在机体坐标系上的时变姿态角。根据姿态角开展电磁计算,获得F-117A隐身攻击机在侧站平飞、背站拉起、对站俯冲、侧站盘旋4种航路下的动态RCS数据。着重分析了动、静态RCS特性在起伏目标检测性能评估上的差异。结果表明：静态RCS特性难以反映目标运动时真实的雷达特性,利用静态数据描述目标特性可能导致错误结论,而文中方法获取的动态RCS数据可以提高结论的完整性和可信度。     

空间目标RCS动态测量及特性分析

本文探讨了适用于某型窄带雷达的RCS相对测量法，对部分空间目标进行了RCS测量。利用随机游程检验法对实测的空间目标RCS时间序列进行了随机性检验，得到了与实际情况相符的结果。     

雷达散射截面计算方法综述

对目标雷达散射截面（RCS）计算方法进行了总结，指出了各种方法的适用范围。以具有复杂外形特征的军用战斗机为例，用物理光学法进行了全机的RCS计算，验证了该方法在飞机设计中的实用性。     

直升机的RCS计算

RCS（Radar Cross Section）是反映目标雷达散射特性的一个重要参数。一般把雷达目标除质心平动之外的转动,小幅振动和其它高阶运动统称为微动。主要研究旋翼转动情况下的直升机RCS计算。通过对直升机模型进行可视化计算即一种将目标建模与散射特性计算合为一体的交互式计算,使用图形算法（GRECO）和三维造型软件UG相结合的方法,这种方法与传统的RCS计算方法相比具有实时性好,效率高的优点,计算出直升机主体的RCS,再通过其加入调制的方法,计算得到直升机在旋翼转动条件下的RCS。最后给出了微动直升机的在具体入射情况下的单站RCS值。     

利用RCS信息的空间目标雷达识别

本文应用模糊数学和天体力学原理,提出了一种利用空间目标的雷达散射截面(RCS)时间序列进行特征提取和模糊分类的目标识别方法,给出了利用该方法对三种尺寸的三轴稳定式目标RCS序列进行特征提取和模糊识别的仿真结果。     

目标雷达截面积模型

获取目标雷达截面积（RCS）的数据的有效方法是全尺寸测量和理论计算。然而，对于局部尺寸模型在某些方面还存在疑义。本文通过全尺雨测量与理论计算数据的比较，说明这种技术在目标中起到的重要作用，及系统评估与理论算法改进的正确性。     

低散射室外隐身测试场研究

测试技术是雷达隐身技术研究和发展中的一项重要内容。影响RCS数据精度的原因除定标体的制作、标定、目标的定位和测试系统的精度外，一个重要的因素就是测试场引起的误差。本文探讨测试场误差引起的主要原因，分析如何降低测试场对测试误差的影响，提高RCS测试精度。     

A Real-Time Statistical Radar Target Model

Radar glint arises from the spatial phase perturbations of the radar signal echoed from a complex target. The glint phenomenon is closely related to the target radar cross section (RCS). This relationship plays a significant part in modern missile seeker signal processing. We present a statistical glint/RCS target model for realtime simulation of target signatures. Particular emphasis is placed upon the modeling and simulation of the appropriate glint/RCS statistical dependency. The fundamental approximation of locating uniformly distributed scatterers around the instantaneous radar centroid employed in the Delano-Gubonin [1, 2, 3] model is removed. A key result which follows from this representation is that the mean glint estimator is unbiased. This enables the estimation of model parameters from the first-order glint and RCS statistics which can easily be computed from measured data. A method of estimating model parameters is presented, and the results are applied to data from a typical combat aircraft target. It is shown that the Delano-Gubonin results are a special case of the results presented here. The 14.6 percent probability of glint falling beyond the target extent as derived by Delano [1] is not true in general. It is further shown that glint and RCS are uncorrelated but are statistically dependent. A Monte-Carlo simulation is performed to verify the assumptions made and to demonstrate the feasibility of the working models.     

Comparison of Two Target Classification Techniques

It has been shown that radar returns in the resonance region carry information regarding the overall dimensions and shape of targets. Two radar target classification techniques developed to utilize such returns are discussed. Both of these techniques utilize resonance region backscatter measurements of the radar cross section (RCS) and the intrinsic target backscattered phase. A target catalog used for testing the techniques was generated from measurements of the RCS of scale models of modern aircraft and naval ships using a radar range at The Ohio State University. To test the classification technique, targets had their RCS and phase taken from the data base and corrupted by errors to simulate full-scale propagation path and processing distortion. Several classification methods were then used to determine how well the corrupted measurements fit the measurement target signatures in the catalog. The first technique uses nearest neighbor (NN) algorithms on the RCS magnitude and (range corrected) phase at a number (e.g., 2, 4, or 8) of operating frequencies. The second technique uses an inverse Fourier transformation of the complex multifrequency radar returns to the time domain followed by cross correlation. Comparisons are made of the performance of the two techniques as a function of signal-to-error noise power ratio for various processing options.     

无人机动态RCS测量及数据统计分析

以某无人机的动态RCS特性作为研究对象,设计了无人机的测试飞行航路,应用非线性最小二乘估计方法,对采集到的无人机动态RCS试验数据进行X^2分布和对数正态分布模型的参数估计,降低了测量噪声对统计模型参数估计的影响,较为理想地解决了数学统计模型参数估计中试验数据测量噪声的影响,并对某无人机的动态RCS统计分布特点做了分析。     

Influence of stealth aircraft dynamic RCS peak on radar detection probability

For modern stealth aircraft, it is important to analyze the influence of Radar Cross Section (RCS) peak exposure on penetration for guiding stealth design and penetration trajectory planning, which needs to reflect the RCS statistical uncertainty and the RCS difference with the change of incident angle. Based on the RCS characteristics of typical stealth aircraft, this paper established a simplified RCS dynamic fluctuation statistical model with the parameters log mean and log standard deviation. According to the detection probability algorithm in radar signal processing field, this paper built the algorithm of radar detection probability based on the RCS dynamic fluctuation statistical model. The analysis of examples concluded that the key to successful penetration is to shorten the RCS peak exposure time, which can be reduced by decreasing the RCS peak width or increasing velocity. Based on the conclusion, this paper proposed the method of turning maneuvering to reduce RCS peak exposure time dramatically.     

A Statistical Glint/Radar Cross Section Target Model

We review the details of the glint (angular scintillation) problem in electromagnetic scattering. These results are employed to develop a statistical glint and radar cross section (RCS) target model featuring the correct glint probability density function, the correct time correlations of RCS and glint, and the correct cross correlation between RCS and glint. This model is suitable for simulation applications, and an implementation scheme for a glint/RCS signal generator is included.     

Radar Cross Section of Ships

A laboratory method to determine the magnitude and position of radar reflection sources on complex targets is described. In addition the method provides a way to measure the modification of the radar cross section (RCS) due to multipath. The method has application in modeling RCS for radar and electronic countermeasure (ECM) system performance analysis and in the study of the extent to which the signature of the target could be altered. The equipment described, termed MACROSCOPE, was developed for RCS studies by the U.S. Army and is described in limited distribution bution literature. The application to marine targets is new with this paper, as is the technique of measuring the RCS of parts of the target and analytically combining them to represent the whole. An illustration of the need for this type of laboratory equipment was illustrated by the extensive search for full scale data which could be compared to scale model data to validate the technique.     

Multiple moving target detection and trajectory estimation using a single SAR sensor

A novel methodology is presented for determining the velocity and location of multiple moving targets using a single strip-map synthetic aperture radar (SAR) sensor. The so-called azimuth position uncertainty problem is therefore solved. The method exploits the structure of the amplitude and phase modulations of the returned echo from a moving target in the Fourier domain. A crucial step in the whole processing scheme is a matched filtering, depending on the moving target parameters, that simultaneously accounts for range migration and compresses two-dimensional signatures into one-dimensional ones without losing moving target information. A generalized likelihood ratio test approach is adopted to detect moving targets and derive their trajectory parameters. The effectiveness of the method is illustrated with synthetic and real data covering a wide range of targets velocities and signal-to-clutter ratios (SCRs). Even in the case of parallel to platform moving target motion, the most unfavorable scenario, the proposed method yields good results for, roughly, SCR > 10 dB.     

Improved target classification using optimum polarimetric SARsignatures

We present a new method for automatic target/object classification by using the optimum polarimetric radar signatures of the targets/objects of interest. The state-of-the-art in radar target recognition is based mostly either on the use of single polarimetric pairs or on the four preset pairs of orthogonal polarimetric signatures. Due to these limitations, polarimetric radar processing has been fruitful only in the area of noise suppression and target detection. The use of target separability criteria for the optimal selection of radar signal state of polarizations is addressed here. The polarization scattering matrix is used for the derivation of target signatures at arbitrary transmit and receive polarization states (arbitrary polarization inclination angles and ellipticity angles). Then, an optimization criterion that minimizes the within-class distance and maximizes the between-class metrics is used for the derivation of optimum sets of polarimetric states. The results of the application of this approach on real synthetic aperture radar (SAR) data of military vehicles are obtained. The results show that noticeable improvements in target separability and consequently target classification can be achieved by the use of the optimum over nonoptimum signatures