Predicting an upper bound on SAR ATR performance

We present a method for predicting a tight upper bound on performance of a vote-based approach for automatic target recognition (ATR) in synthetic aperture radar (SAR) images. In such an approach, each model target is represented by a set of SAR views, and both model and data views are represented by locations of scattering centers. The proposed method considers data distortion factors such as uncertainty, occlusion, and clutter, as well as model factors such as structural similarity. Firstly, we calculate a measure of the similarity between a given model view and each view in the model set, as a function of the relative transformation between them. Secondly we select a subset of possible erroneous hypotheses that correspond to peaks in similarity functions obtained in the first step. Thirdly, we determine an upper bound on the probability of correct recognition by computing the probability that every selected hypothesis gets less votes than those for the model view under consideration. The proposed method is validated using MSTAR public SAR data, which are obtained under different depression angles, configurations, and articulations     

一种提高SAR目标识别率的有效方法

在合成孔径雷达自动目标识别SAR ATR中，SAR像的预处理是提高识别率的关键技术之一。给出了一种简单有效的SAR图像预处理方法，该方法首先对SAR目标像进行对数变换后，再做傅立叶变换。经预处理后的SAR像用支持矢量机SVM分类器进行目标识别。实验结果表明：本方法不但有效地提高了目标识别率，而且保证了目标的平移不变性并具有良好的推广能力。     

Improving slant-range resolution with multiple SAR surveys

Across-track resolution of a spaceborne synthetic aperture radar (SAR) system is limited by power and data rate constraints. The authors derive and discuss a new technique for increasing the across-track resolution of objects that do not change with time, using multiple surveys of the same area from different off-nadir angles. Precise information on the spaceborne trajectories are not requested since they can be derived from SAR interferometry. Simulated data show that theoretical derivations are in good agreement with practice     

Super resolution SAR imaging via parametric spectral estimationmethods

Super resolution synthetic aperture radar (SAR) image formation via sophisticated parametric spectral estimation algorithms is considered. Parametric spectral estimation methods are devised based on parametric data models and are used to estimate the model parameters. Since SAR images rather than model parameters are often used in SAR applications, we use the parameter estimates obtained with the parametric methods to simulate data matrices of large dimensions and then use the fast Fourier transform (FFT) methods on them to generate SAR images with super resolution. Experimental examples using the MSTAR and Environmental Research Institute of Michigan (ERIM) data illustrate that robust spectral estimation algorithms can generate SAR images of higher resolution than the conventional FFT methods and enhance the dominant target features     

Automatic target recognition using enhanced resolution SAR data

Using advanced technology, a new automatic target recognition (ATR) system has been developed that provides significantly improved target recognition performance compared with ATR systems that use conventional synthetic aperture radar (SAR) image-processing techniques. This significant improvement in target recognition performance is achieved by using a new superresolution image-processing technique that enhances SAR image resolution (and image quality) prior to performing target recognition. A computationally efficient two-level implementation of a template-based classifier is used to perform target recognition. The improvement in target recognition performance achieved using superresolution image processing in this new ATR system is quantified     

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     

Effects of Navigation Errors in Maneuvering SAR

A maneuvering synthetic aperture radar in squint mode, during a loosely piloted maneuver, is simulated with presence of various navigation system errors. The error sources investigated place emphasis on short-term effects, involving platform servo transients, noise and quantization in accelerometers, interaction of angle pickoff uncertainty with the displacement from platform to radar antenna, and uncertainty in this displacement itself. Simulation results are accompained by interpretive discussion, and followed by suggested areas for further study.     

Effects of finite weight resolution and calibration errors on theperformance of adaptive array antennas

Adaptive antennas are now used to increase the spectral efficiency in mobile telecommunication systems. A model of the received carrier-to-interference plus noise ratio (CINR) in the adaptive antenna beamformer output is derived, assuming that the weighting units are implemented in hardware, The finite resolution of weights and calibration is shown to reduce the CINR. When hardware weights are used, the phase or amplitude step size in the weights can be so large that it affects the maximum achievable CINR. It is shown how these errors makes the interfering signals “leak” through the beamformer and we show how the output CINR is dependent on power of the input signals. The derived model is extended to include the limited dynamic range of the receivers, by using a simulation model. The theoretical and simulated results are compared with measurements on an adaptive array antenna testbed receiver, designed for the GSM-1800 system. The theoretical model was used to find the performance limiting part in the testbed as the 1 dB resolution in the weight magnitude. Furthermore, the derived models are used in illustrative examples and can be used for system designers to balance the phase and magnitude resolution and the calibration requirements of future adaptive array antennas     

Theory and experiments on hard-limited SAR imaging

Known results in the area of hard-limited array theory are extended and generalized for synthetic aperture radar (SAR) applications in order to obtain a significant reduction of the required transmission channel bandwidth. The results provide a theoretical basis for subsequent numerical experiments related to the SIR-B mission. The SAR signal is hard-limited (at the offset frequency, after the heterodyne process) and filtered, and the restored signal is processed in the conventional way to obtain the image of the pertinent scene. Results of this experiment may be useful in assessing image degradation due to 1-b coding     

局部进气ATR涡轮性能影响因素数值模拟研究

为研究局部进气条件下ATR涡轮内的流动特性,对局部进气涡轮进行定常和非定常数值模拟.定常计算采用冻结转子方法,改变动叶与静叶的周向相对位置研究涡轮内流场特征;改变进气扇区布局、进口参数和局部进气度,研究其对涡轮性能的影响.研究结果表明,对于给定局部进气度,进气扇区整体布局时,涡轮性能的优越性最大;在局部进气ATR涡轮的设计中,需要综合考虑流量、效率和功率3个因素来决定局部进气度.不同位置定常流动结果的平均值与非定常流动的时均值存在差异,非定常计算更好地展示了静叶尾迹和流动积累效应的影响,因而更加可靠.     

SAR干扰效果研究

研究了对干扰前不同图像质量的合成孔径雷达(SAR)的干扰效果问题。从干扰前SAR图像质量指标积分旁瓣比(ISLR)入手,提出等效信干比的概念,建立积分旁瓣比与等效信干比的关系,分析等效信干比与发现概率、错误概率的关系,最后确定不同图像质量所对应的所需信干比。     

基于北斗卫星导航的搜救系统原理与构型

为使基于北斗卫星的导航搜救系统比现有全球卫星搜救系统（COSPAS-SARSAT）更具先进性、优越性、更适应我国国情,在全球卫星搜救系统基础上构建基于北斗卫星搜救系统的原理和构型,使其具备提供全天候、全天时、高精度、高可靠的定位、导航和授时服务,并充分利用短消息服务有效缩短救生搜索和定位时间,提高了搜救效率,同时加强卫星定位保密程度,为未来军事用途打下基础。     

鲁棒成形极化敏感阵列波束的方法及极化估计

基于极化敏感阵列,提出了一种鲁棒成形阵列波束的方法。该方法首先将阵列的数据模型进行了重新描述,从而获得了信号波达角(DOA)和极化解耦的模型。借助于该模型并对信号的两个极化方向分别进行鲁棒约束,设计出了一个新的鲁棒空域波束空间成形矩阵,利用该矩阵可以获得信号两个极化分量的鲁棒估计。基于特征值分解的方法,最后给出了估计信号极化参数的方法。分析和数值仿真实验均表明:提出的方法,在对DOA估计误差以及阵列位置误差等造成的阵列失配具有较强鲁棒性的同时,也能有效抑制干扰和噪声,进而提升了极化参数估计的性能。     

为发展中国支线航空支招——访ATR全球商务副总裁John Moore

对于支线航空的定位和作用,支线飞机制造商和支线航空公司使用了不同的表达方式.     

无人机载SAR图像压缩传输中的关键技术研究

本文在深入研究EBCOT算法的基础上.对算法进行了部分改进.设计了基于JPEG2000标准的SAR图像压缩算法,并完成了该算法的软件设计工作,并对其压缩性能和容错性能进行了分析.     

基于低成本INS的机载SAR运动补偿研究

为了提高雷达成像的质量．得到高分辨率的SAR图像就必须保证有精确的运动补偿方法来校正运动误差对成像的影响。提出了一种基于惯导数据INS的视线方向位移误差的补偿方法,采用了低精度低成本的INS．对此部分的原理及实现进行了深入的建模分析和推导,并给出仿真结果。结果表明,基于惯导进行运动补偿时低精度也可满足要求。     

A SAR processor based on two-dimensional FFT codes

A synthetic aperture radar (SAR) processor approach based on two-dimensional fast Fourier transform (FFT) codes coupled with an asymptotic evaluation of the unit response function is presented. For the latter, no approximation is made to the distance function, so that the full range of geometric aberrations is analytically considered, enabling an effective reference filter to be designed. The two-dimensional FFTs were designed as to run on computers of very limited memory: the required FFT is computed by means of FFTs of lower order. Two FFT codes were considered: one is faster and allows full or reduced (quick look or multilook) resolution performance to be obtained easily; the second is slower but allows the use of a space-varying filter and/or investigations on limited portions (zoom) of the image. Both codes are suited to parallel processing, e.g. by a transputer net. A full discussion on computer memory and time requirements is presented as well as first examples of image processing results     

New SAR Processor Based on Matched Subspace Detectors

This paper deals with a new synthetic aperture radar (SAR) Processor based on a subspace detector designed for man-made target (MMT) detection. As MMTs are more accurately decribed by a set of canonical elements than with isotropic points, we develop a new algorithm which aims at using new models, instead of the isotropic point model commonly used in SAR processors. A subspace detector matched to canonical elements is included in the SAR processing. The implementation and the optimization of subspace detector SAR (SDSAR) algorithm is described. Simple examples of MMT detection in simulations and real data with a target hidden in a forest show the power of our approach. The SDSAR algorithm is shown to be the first robust and tractable algorithm relying on realistic scattering assumptions about the target.     

MMWR/FLIR/ATR sensor fusion: proof of concept

To improve the relocatable target capabilities of strategic aircraft, a sensor fusion concept using a millimeter-wave radar (MMWR) and a forward-looking infrared (FLIR) system providing inputs to an auto target recognizer (ATR) has been developed. To prove this concept, a cooperative research effort is being conducted by a group of industry leaders in bomber avionics, MMWR, and ATR technologies. The author discusses the concept and the plan developed to test, evaluate, and demonstrate the expected performance     

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