Space-time adaptive processing and adaptive arrays: specialcollection of papers

Space-time adaptive processing (STAP) and related adaptive array techniques hold tremendous potential for improving sensor performance by exploiting signal diversity. Such methods have important application in radar, sonar, and communication systems. Recent advances in digital signal processing technology now provide the computational means to field STAP-based systems. The objective of this special collection of papers is to examine the current state-of-the art in STAP technology and explore the remaining obstacles, practical issues and novel techniques required to implement STAP-based radar, sonar or communication systems     

Adaptive Clutter Filtering Using Autogressive Spectral Estimation

A new adaptive filter to reject clutter is derived using autoregressive spectral analysis techniques. The adaptive filter performs open. Ioop processing, resulting in a shorter transient response, and is therefore suitable for radar waveforms containing only a small number of samples. A number of examples including application to ballistic missile defense are presented to demonstrate the performance capabilities of the new adaptive filter.     

风沙两相流动光学测量及图像处理技术研究进展

介绍了自风沙动力学诞生以来所使用的各类光学测量方法,阐述了各种方法的优缺点和适用范围,针对最新光学测量技术在近代风沙两相流研究中的重要作用,着重介绍了PIV、高速数字图像测量及其图像处理技术在风沙两相流中的应用,指出光学测量在时间和空间的解析能力上的持续增长将为沙粒微观力学解析和风沙流宏观统计规律获取提供充足的支持。     

一种基于单部雷达的飞行器脱靶量测试方法

对单部雷达测量飞行器脱靶量所涉及到的雷达分辨力和多目标信息获取及处理进行了分析;结合实际靶场应用介绍了脱靶量数据处理方法;分析了脱靶量的测量误差,并给出了分析结果;本方法可最大限度地补偿掉系统误差,脱靶量测量误差主要来源于雷达本身测量精度。     

Design and analysis of a knowledge-aided radar detector for doppler processing

In this paper we discuss the combined use of a priori information and adaptive signal processing techniques for the design and the analysis of a knowledge-aided (KA) radar receiver for Doppler processing. To this end, resorting to the generalized likelihood function (GLF) criterion (both one-step and two-step), we design and assess data-adaptive procedures for the selection of training data. Then we introduce a KA radar detector composed of three elements: a geographic-map-based data selector, which exploits some a priori information concerning the topography of the observed scene, a data-adaptive training selector which removes dynamic outliers from the training data, and an adaptive radar detector which performs the final decision about the target presence. The performance of the KA algorithm is analyzed both on simulated as well as on real radar data collected by the McMaster University IPIX radar. The results show that the new KA system achieves a satisfactory performance level and can outperform some previously proposed adaptive detection schemes     

Performance Compparison of Optimum and Conventional MTI and Doppler Processors

The performance of an optimum radar signal processor and more conventional techniques (such as MTI, adaptive MTI, and cqherent integration) are compared. A mathematical method is suggested and applied to several cases of practical interest. A number of operative conditions are discovered in which the conventional processing techniques give very poor performance and the optimum radar processor becomes necessary.     

Bayesian and Dempster-Shafer target identification for radarsurveillance

This paper considers the problem of target track identification in a radar surveillance system. To build a target identifier alongside a tracker, four features which are available for real-time processing in an air surveillance system are used here: target identity (TID) from a friend-and-foe identification (IFF) system, elevation measurement from the radar, target speed, and acceleration estimated by a tracker. These four features are combined to classify air targets into five different air target categories: friendly commercial, friendly military, hostile commercial (or unknown airline), hostile military, and false targets (clutter). Two popular statistic-based techniques, namely, the Bayesian and Dempster-Shafer methods, are applied to develop radar target identification algorithms for our application. Real-life as well as simulated air surveillance radar data are used to evaluate the practicality and effectiveness of this track identification approach in a radar surveillance system     

基于复近似消息传递的前视雷达成像分辨率增强算法

当机载/弹载雷达工作在前视状态时,由于成像场景内不同角度处目标的多普勒差异很小,很难得到 高的角度分辨率。针对海面舰船目标的前视成像应用,利用成像区域具有明显稀疏性的特点,提出一种基于复 近似消息传递压缩感知处理的前视成像角度分辨率增强算法,建立前视成像的线性观测信号模型,给出复近似 消息传递的迭代计算过程,以及多通道雷达前视成像的处理流程。通过仿真数据和 X 波段雷达实测数据的处 理结果验证了该方法的有效性。     

Detecting the Presence of Target Multiplicity

A method is discussed for detecting the presence of multiple targets in the radar antenna beam. It is assumed that the targets are unresolvable in range, Doppler, and angle using conventional monopulse resolution techniques. The basic approach taken is a generalization of the "quadrature" method, with significantly enhanced performance in the case when multiple pulses are integrated into a single solution. Detection and false alarm probabilities are derived analytically and the receiver operating characteristics are graphed. This study was performed for application to angle processing in a frequency agile automatic tracking radar, but the underlying concept is general and has applications outside this area.     

The Series 320 Radar: Three-Dimensional Air Surveillance for the 1980s

Air surveillance radars for this decade will be required to provide reliable target location and trajectory information in height as well as the conventional geographical coordinates. These threedimensional radars will perform this task in spite of adverse environmental conditions such as ground, airborne clutter, and electromagnetic interference. The use of powerful false-alarm control processing allows automatic target detection and remoting of target information without overloading central processing capabilities. The technological evolution of the past decade has allowed sophisticated analysis, antenna/receiver/transmitter design, and signal/data processing techniques to be applied to the next generation of practical production radar systems. These radars will meet more severe performance requirements and will be significantly improved in terms of reliability, maintainability, and life cycle cost considerations. A candidate radar to fulfill the air surveillance role of this decade is the Series 320 radar manufactured by ITT Gilfillan.     

Aperture Sampling Techniques for Precision Direction Finding

The resolution and tracking of radar targets which are close to. gether is a classical problem which is receiving increased attention. Improving the angular resolution by sampling the received wave front along the aperture and then applying modern "high resolution" spectrum estimation techniques (e. g., maximum likelihood and maximum entropy processing) to the spatial sample data is discussed. Experimental results are presented for the application ion of these techniques to field data from a L- band line array.     

Reduced-rank STAP performance analysis

The space-time radar problem is well suited to the application of techniques that take advantage of the low-rank property of the space-time covariance matrix. It is shown that reduced-rank (RR) methods outperform full-rank space-time adaptive processing (STAP) when the space-time covariance matrix is estimated from a data set with limited support. The utility of RR methods is demonstrated by theoretical analysis, simulations and analysis of real data. It is shown that RR processing has two opposite effects on the performance: increased statistical stability which tends to improve performance, and introduction of a bias which lowers the signal-to-noise ratio (SNR). A method for evaluating the theoretical conditioned SNR for fixed RR transforms is also presented. It Is shown that while best performance is obtained using data-dependent transforms, the loss incurred by the application of fixed transforms (such as the discrete cosine transform) may be relatively small. The main advantage of fixed transforms is the availability of efficient computational procedures for their implementation. These findings suggest that RR methods could facilitate the development of practical, real-time STAP technology     

Inspection of Internal Structure of Walls by Subsurface Radar

This paper deals with the application of ultra-wide band time-domain subsurface radars, equipped with special signal processing techniques, to realize non-invasive image testing of the building walls' internal structure that are made with brick, stone, concrete, reinforced concrete, and other construction materials. There are two normally associated problems: qualitative and quantitative, considered. Limitations and shortcomings of radar imaging, due to inherent physical features as well as signal processing improving the quality of radar images, are discussed. Actual field data are used to illustrate applications of subsurface radar for non-destructive testing of walls' internal regions     

Digital synthetic aperture radar processing via optical computers

A method for performing digital phase history processing of synthetic aperture radar (SAR) data using optical computers is proposed. The method has nothing in common with the old analog optical SAR processing methods (which used lenses), but is rather a totally digital (numerical) technique for computing the individual complex pixel values based on matrix-vector multiplications. The method can be expected to greatly increase the potential processing speed and coverage possibilities of high-resolution digital SAR systems     

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.     

Application of a Highly Parallel Processor to Radar Data Processing

The application of a highly parallel computer known as PEPE (Parallel Element Processing Ensemble) to radar data processing is described. The PEPE computer consists of a large number of identical processing elements which operate in parallel and are controlled by a common control unit. Each of the processing elements is assigned to a particular radar target such that many targets can be tracked in parallel. PEPE is designed to augment a conventional computer rather than to stand alone. The total data processing load associated with a radar tracking system is distributed between PEPE and the sequential machine in a manner than maximizes the overall system efficiency and desensitizes the system performance to fluctuations in traffic levels. The use of PEPE provides very high data processing throughput potential to a radar data processing system.     

Multiband coherent radar detection against compound-Gaussianclutter

A Multiband GLRT-LQ (Generalized Likelihood Ratio Test-Linear Quadratic), MBGLRT-LQ, detector is derived for the coherent radar target detection against a compound-Gaussian clutter background. This scheme is an extension to the multiband case of the Asymptotically Optimum Detector (AOD), also derived under the name of GLRT-LQ in. The proposed multiband version of the algorithm shows two main advantages with respect to the original single-band algorithm. 1) For the adaptive implementation, it requires a much smaller area of homogeneous clutter echoes to estimate the covariance matrix of the interference; 2) it provides an optimum processing of the radar echoes when the radar operates in frequency agility, as electronic counter-countermeasure (ECCM) strategy. A closed form performance analysis is provided for the MBGLRT-LQ detector, which is used to compare it with the single-band version. An application to live recorded data is also presented to validate the obtained results     

基于小波变换的单脉冲雷达目标RCS测量方法研究

随着现代信号处理技术的发展,对非平稳信号分析和处理的小波分析技术已成功应用于雷达目标特性分析领域,大功率单脉冲雷达作为我国航天测控网的主干设备,具有一定的目标特性识别能力。本文主要针对脉冲雷达RCS测量原理,讨论了基于小波变换的单脉冲雷达空间目标RCS测量方法,提出应发挥窄带低分辨率雷达在未来空间目标识别中的作用。     

飞行仿真中雷达地形数据库构建关键技术

雷达图像仿真是飞行仿真的重要组成部分,而雷达地形数据库为雷达图像仿真提供基本的数据支持。为构建满足仿真精度与实时性要求的雷达地形数据库,对相关关键技术进行了研究。在分析雷达图像仿真原理的基础上,研究了雷达地形数据库在分布式飞行仿真系统中的应用方式和组成形式。根据所用数据源的不同,对雷达地形建模技术进行了分类,并分析了不同建模方法的优缺点。比较了网格式与多边形式2种数据存储与调度技术的特点和适用性,指出多分辨率表示技术雷达地形建模中的重要性,给出了一种材质数据多分辨率映射的基于材质最大出现概率的子取样方法。对机载雷达实波束地形测绘成像进行了仿真。     

机载雷达从地杂波中检测运动目标

提出了将变抽样率处理技术应用于机载雷达下视探测,以从地杂波中检测运动目标的方法。首先分析了信号模型,针对这一模型,讨论了变抽样率处理技术应用问题,最后进行了仿真,仿真结果,表明该方法可行