Maximum likelihood angle extractor for two closely spaced targets

In a scenario of closely spaced targets special attention has to be paid to radar signal processing. We present an advanced processing technique, which uses the maximum likelihood (ML) criterion to extract from a monopulse radar separate angle measurements for unresolved targets. This processing results in a significant improvement, in terms of measurement error standard deviations, over angle estimators using the monopulse ratio. Algorithms are developed for Swerling I as well as Swerling III models of radar cross section (RCS) fluctuations. The accuracy of the results is compared with the Cramer Rao lower bound (CRLB) and also to the monopulse ratio technique. A novel technique to detect the presence of two unresolved targets is also discussed. The performance of the ML estimator was evaluated in a benchmark scenario of closely spaced targets - closer than half power beamwidth of a monopulse radar. The interacting multiple model probabilistic data association (IMMPDA) track estimator was used in conjunction with the ML angle extractor     

Monopulse DOA estimation of two unresolved Rayleigh targets

This paper provides for new approaches to the processing of unresolved measurements as two direction-of-arrival (DOA) measurements for tracking closely spaced targets rather than the conventional single DOA measurement of the centroid. The measurements of the two-closely spaced targets are merged when the target echoes are not resolved in angle, range, or radial velocity (i.e., Doppler processing). The conditional Cramer Rao lower bound (CRLB) is developed for the DOA estimation of two unresolved Rayleigh targets using a standard monopulse radar. Then the modified CRLB is used to give insight into the boresight pointing for monopulse DOA estimation of two unresolved targets. Monopulse processing is considered for DOA estimation of two unresolved Rayleigh targets with known or estimated relative radar cross section (RCS). The performance of the DOA estimator is studied via Monte Carlo simulations and compared with the modified CRLB     

Performance analysis of a radar target discrimination technique

The performance of a radar target discrimination technique using multiple-frequency scattering amplitude without phase data is investigated. Based on the concept of natural resonance frequencies, the technique is aspect independent so that a priori information of the aspect angle is not necessary. The radar cross sections (RCSs) of spheroids are calculated numerically to simulate the received radar returns for distinguishing different spheroids and wires in the resonance frequency range by the proposed technique. By Monte Carlo simulation, the discrimination error rate is estimated as a function of the standard deviation of added noise. The numerical results show that the discrimination algorithm works well under moderately noisy situations and can be applied even in a high-resonance frequency range     

复杂目标高频区 RCS 的实时计算

提出一种在安装图形加速卡的高性能微机上实时计算复杂目标高频区雷达散射截面（RCS）的方法。该方法利用了“图形电磁计算（GRECO）”的新技术。目标用G2Catmul-om（C-R）几何样条模拟,由图形加速卡硬件完成遮挡、消隐运算,运用Phong光照模型着色渲染目标可见表面,应用物理光学（PO）、等效电流法（MEC）、物理绕射理论（PTD）及阻抗边界条件（IBC）等方法计算目标高频区雷达散射截面（RCS）.     

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.     

Impact of target RCS fluctuations on radar measurement accuracy

The impact of target radar cross section (RCS) fluctuations on the thermal noise limited accuracy of radar measurements of range, range rate, and angle is evaluated for Swerling fluctuation models. The impact is expressed as a modification of the large-signal approximation to the standard deviation σ of measurement error     

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。     

SAR imaging of moving targets

A method of forming synthetic aperture radar (SAR) images of moving targets without using any specific knowledge of the target motion is presented. The new method uses a unique processing kernel that involves a one-dimensional interpolation of the deramped phase history which we call keystone formatting. This preprocessing simultaneously eliminates the effects of linear range migration for all moving targets regardless of their unknown velocity. Step two of the moving target imaging technique involves a two-dimensional focusing of the movers to remove residual quadratic range migration errors. The third and last step removes cubic and higher order defocusing terms. This imaging technique is demonstrated using SAR data collected as part of DARPA's Moving Target Exploitation (MTE) program     

Bayesian gamma mixture model approach to radar target recognition

This paper develops a Bayesian gamma mixture model approach to automatic target recognition (ATR). The specific problem considered is the classification of radar range profiles (RRPs) of military ships. However, the approach developed is relevant to the generic discrimination problem. We model the radar returns (data measurements) from each target as a gamma mixture distribution. Several different motivations for the use of mixture models are put forward, with gamma components being chosen through a physical consideration of radar returns. Bayesian formalism is adopted and we obtain posterior distributions for the parameters of our mixture models. The distributions obtained are too complicated for direct analytical use in a classifier, so Markov chain Monte Carlo (MCMC) techniques are used to provide samples from the distributions. The classification results on the ship data compare favorably with those obtained from two previously published techniques, namely a self-organizing map and a maximum likelihood gamma mixture model classifier.     

Modeling the Augmentation System of a Radar Target

The objective of the high-altitude supersonic target (HAST) radar augmentation system is to simulate the radar cross section (RCS) of a real target. The system is, therefore, of the active transponder type with various radiating antennas simulating the dominant scattering centers on the real target. We develop a system model, which when combined with the measured RCS of the HAST vehicle, simulates the RCS of the real target. Comparisons with measurements illustrating the success of the simulation program are given.     

Superresolution HRR ATR with high definition vector imaging

A new 1-D template-based automatic target recognition (ATR) algorithm is developed and tested on high range resolution (HRR) profiles formed from synthetic aperture radar (SAR) images of targets taken from the Moving and Stationary Target Acquisition and Recognition (MSTAR) data set. In this work, a superresolution technique known as High Definition Vector Imaging (HDVI) is applied to the HRR profiles before the profiles are passed through ATR classification. The new I-D ATR system using HDVI demonstrates significantly improved target recognition compared with previous I-D ATR systems that use conventional image processing techniques. This improvement in target recognition is quantified by improvement in probability of correct classification (PCC). More importantly, the application of HDVI to HRR profiles helps to maintain the same ATR performance with reduced radar resource requirements     

飞行器目标频率响应散射特性

为研究飞行器目标散射频率响应特性和隐身、反隐身原理,对两种飞行器平板缩比模型进行了系列测试和计算研究,推导和验证了简单目标（金属球）的频率响应特性在飞行器目标上的适用性,并推广到如飞行器复杂散射体的分析。提出了划分瑞利区、谐振区、高频区的新方法,指出飞行器具有隐身能力极限的概念;研究了目标多频散射的极化特性,发现频率降低时,水平极化下全向雷达散射截面（RCS)均值逐渐增大,垂直极化时减小。得到了两种飞行器目标处于瑞利区、谐振区时依靠外形隐身所能达到的RCS极限值。结果分析表明,在瑞利区和谐振区,目前的外形隐身措施存在不能超越的极限,在这两个区域的雷达隐身需结合外形和材料隐身技术。     

A technique for enhanced slant range resolution for SAR systems inknowledge-based environment

Synthetic Aperture Radar (SAR) is an airborne (or spaceborne) radar mapping technique for generating high resolution maps of surface target areas including terrain. High resolution is achieved by coherently combining the returns from a number of radar transmissions. The resolution of the images is determined by the parameters of the emissions, with more data giving greater resolution. A requirement of the Microwave Radar Division's SAR radar is to provide classification of targets. This paper presents a technique for enhancing slant range resolution in SAR images by dithering the carrier centre frequency of the transmitted signal. The procedure controls the radar waveforms so they will optimally perform the classification function, rather than provide an image of best quality. It is shown that a Knowledge-Based engineering approach to determining the waveform of the radar gives considerably improved performance as a classifier of targets (of large radar cross-section), even though the corresponding image is degraded     

基于鸟类目标散射特性分析的雷达探鸟实验

 鸟类目标散射特性研究是雷达探鸟系统探测性能分析的理论基础。基于此,首先进行了鸟类目标散射特性分析,采用实验数据构造的理论统计模型,估计出单只鸟和鸟群的雷达散射截面（RCS）量级范围。然后,详细介绍了雷达探鸟实验系统的系统结构、探测性能和飞鸟目标识别算法。最后,基于外场实验获取的雷达探鸟图像序列提取出飞鸟目标轨迹与相关信息,验证了雷达探鸟的可行性,并通过对不同实验结果的分析提出了抑制虚警和漏警的算法改进方向。     

航迹规划中雷达探测空间的生成

从飞机突防习行任务规划出发，综合考虑地球曲率、陆地（或海洋）的反射和杂波干扰、大气折射和吸收损耗等因素的影响，采用临界散射截面法生成了对空警戒雷达在不同地貌、发现概率下，对不同雷达散射截面的目标的探测空间。计算并分析了飞行高度、目标雷达散射截面、发现概率和地貌等因素对雷达探测空间的影响，以便选择低探测概率的飞行走廓，这对制定和实施安全突防飞行策略有实际意义。     

Reduced-rank STAP for high PRF radar

Due to the range ambiguity of high pulse-repetition frequency (HPRF) radars, echoes from far-range fold over near-range returns. This effect may cause low Doppler targets to compete with near-range strong clutter. Another consequence of the range ambiguity is that the sample support for estimating the array covariance matrix is reduced, leading to degraded performance. It is shown that space-time adaptive processing (STAP) techniques are required to reject the clutter in HPRF radar. Four STAP methods are studied in the context of the HPRF radar problem: low rank approximation sample matrix inversion (SMI), diagonally loaded SMI, eigencanceler, and element-space post-Doppler. These three methods are evaluated in typical HPRF radar scenarios and for various training conditions, including when the target is present in the training data     

Application of frequency correlation function to radar target detection

Analysis of high-resolution 35 GHz synthetic aperture radar (SAR) imagery of terrain reveals that when point targets, such as vehicles, are viewed at angles close to grazing incidence, they are often difficult to distinguish from tree trunks because the radar cross section (RCS) intensities of the vehicles are comparable to the upper end of the RCS exhibited by tree trunks. To resolve the point target/tree trunk ambiguity problem, a detailed study was conducted to evaluate the use of new detection features based on the complex frequency correlation function (FCF). This paper presents an analytical examination of FCF and its physical meaning, the results of a numerical simulation study conducted to evaluate the performance of a detection algorithm that uses FCF, and the corroboration of theory with experimental observations conducted at 35 and 95 GHz. The FCF-based detection algorithm was found to correctly identify tree trunks as such in over 90% of the cases, while exhibiting a false alarm rate of only 3%.     

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.     

An MTI Technique for Processing Radar Measurements of a Waking Reentry Body

A processing technique based on pulse-cancellation techniques familiar in moving target indicator (MTI) radar is proposed for separating (in Doppler) echoes of a reentry body traveling at hypersonic velocities from those of its lower velocity turbulent wake appearing in the same range cell. The cancellation technique is implemented by forming the sum of the products of binomial weighting coefficients of alternating sign with the complex echoes of a small number of closely spaced transmitted coherent pulses; thereby, in effect, synthesizing a digital canceler. The ability of the two-and three-pulse canceler to estimate body RCS in the presence of attached wake is demonstrated by employing coherent burst data collected by the AMRAD radar for a mission flown at the White Sands Missile Range. Estimates of body RCS obtained from the two-and three-pulse canceler compare favorably to the corresponding estimates obtained from a 30-pulse Doppler periodogram for this mission. Expressions for both the achievable wake rejection ratio and the mean and standard deviation of the body power estimate of the N-pulse canceler are derived as a function of the wake parameters, assuming Gaussian wake statistics.