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.     

基于杂波对消-自聚焦的多通道SAR-GMTI

对超高频(UHF)波段多通道合成孔径雷达(SAR)动目标检测技术进行研究,解决了长相干积累时间导致动目标在方位向散焦严重的问题。采用分块自聚焦技术对多通道SAR地面移动目标指示(GMTI)系统自适应杂波抑制后的SAR图像进行处理,改善杂波抑制后的SAR图像中动目标的聚焦情况,增强动目标与周围剩余杂波的对比度,进而提高恒虚警率(CFAR)检测的性能。与传统杂波抑制后直接进行CFAR检测方法相比较,该方法降低了检测虚警概率。实测数据处理结果显示动目标的信杂比明显提高,动目标方位向聚焦成功,证明了该方法的有效性。     

Localization of step changes in multitemporal SAR images

Deals with multitemporal sequences of synthetic aperture radar (SAR) images with regions possibly affected by step reflectivity patterns of change. Specifically, it addresses the problems of detecting a temporal step pattern with small reflectivity change against a constant pattern and of estimating the transition instant for the step. The statistically optimized signal processing techniques proposed in this work are most appropriate for the new generation of SAR systems with high revisit time that are currently under development. We propose two different techniques, based on the maximum likelihood (ML) approach, that make different use of prior knowledge on the radar cross section (RCS) levels of the searched pattern. They process the whole sequence to achieve optimal discrimination capability between regions affected and not affected by a step change and optimal estimation accuracy for the step transition instant. The first technique (known step pattern (KSP)-detector) assumes complete knowledge of the RCS levels of the searched pattern of change, while the second one (USP-detector) is based on the assumption of totally unknown step pattern.     

High resolution 3D “snapshot” ISAR imaging and featureextraction

We have developed a new formulation for three dimensional (3D) radar imaging of inverse synthetic aperture radar (ISAR) data based on recent developments in high resolution spectral estimation theory. Typically for non real-time applications, image formation is a two step process consisting of motion determination and image generation. The technique presented focuses on this latter process, and assumes the motion of the target is known. The new technique offers several advantages over conventional techniques which are based on the correlation imaging function. In particular, the technique provides for a direct 3D estimate (versus back projection to a 3D target grid matrix) of the locations of the dominant scattering centers using only a minimum set of independent 2D range-Doppler ISAR “snapshots” of the target. Because of the snapshot nature of the technique, it is particularly applicable to 3D imaging of sectors of sparse-angle data, for which the sidelobes of the correlation imaging integral become high. Furthermore, the technique provides for an estimate of amplitude and phase of each scattering center as a function of aspect angle to the target, for those aspect angles which encompass the set of 2D range-Doppler snapshots. Results illustrating the technique developed are presented for both simulated and static range data     

On the Design of a Large Aperture Radar for Target Imaging

This paper describes the design, construction, and performance of an experimental radar, in which an electronically scanned X-band array is employed as the receiving antenna. Backscatter from targets uniformly illuminated from a separate transmitting antenna is intercepted by 128 horn antennas, unequally spaced over a nine-foot circular aperture. The received signals are processed electronically to provide a complete scan of a 30X30 degree field every ten milliseconds. Resulting target images were displayed on a cathode ray tube and recorded on 16-mm motion picture film, for varying conditions of target motion using monochromatic and frequency-modulated X-band illumination. Sequences of motion picture frames obtained from a rotating copper cone are presented, which demonstrate significant changes in the image and side-lobe interference patterns for small changes in target aspect angle. Side-lobe interference effects were reduced by integrating many antenna scans as the target rotated; a clear image of a foil letter R is presented that demonstrated this result. The main objective of this work was to test this radar technique as an approach to target recognition.     

基于时频分析的双通道SAR自旋目标检测

强地杂波背景给微动目标检测带来很大困难,为此在详细分析距离向压缩数据域自旋目标回波特性基础上,提出了基于双通道合成孔径雷达相位中心偏置天线(SAR/DPCA)和沿航迹干涉(ATI)杂波抑制的两类自旋目标检测方法,并作比较分析.在DPCA模式下,微多普勒频率沿频率(m-D)轴有一整体平移量,其与目标自旋中心的方位向坐标成...     

利用分数阶Fourier域滤波的机载SAR多运动目标检测

 强度相差较大的多运动目标检测是机载合成孔径雷达 ( SAR)技术的一个重点和难点,传统的频域滤波和现代的时频分布方法都无法解决这个问题。首先分析了机载 SAR运动目标回波本质上为线性调频信号,据此提出一种基于分数阶 Fourier域滤波的运动目标检测新方法,并且应用逐次消去的思想有效地解决了强度相差较大的多目标检测问题。仿真的结果验证了算法的有效性。     

Time-frequency method for detecting an accelerating target in sea clutter

The authors design a time-frequency (TF) method for use in high-frequency surface-wave radar (HFSWR) for detecting a small accelerating target in sea clutter. The clutter is modelled by pseudo targets moving with Bragg velocity towards and away from the radar. The design is based on the Wigner distribution (WD) defined by Chan (type-III WD, in our terminology) rather than the WD defined by Claasen and Mecklenbrauker (1980) (2times type-I WD, in our terminology). Like the type-I WD, the type-III WD also concentrates a chirp signal onto a straight line in the TF plane. The type-III WD has the following advantages: 1) Its range of unambiguously measurable frequencies (RUMF) is [-pi,pi] rad/s, whereas for the type-I WD the RUMF is [-pi/2,pi/2] rad/s. 2) It allows a target separated from the clutter by pi rad/s to be detected, whereas the type-I WD coalesces such a target with the clutter and thereby mask it. An ambiguity function (AF) was defined corresponding to the type-III WD and use it to derive a smoothed type-III WD that mitigates the clutter. The smoothed type-III WD method is applied to real radar data and shown to be superior to the conventional Fourier transform method. The advantages of the type-III WD over the type-I WD are also demonstrated. The design principles laid out in the paper can also be used to develop a TF method for use in air traffic control radar (ATCR) for detecting an accelerating target in land clutter     

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.     

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     

表面粗糙的复杂目标全极化ISAR图像快速仿真

为了获取基于模板图像的车辆、飞机等复杂目标识别所需的海量高质量逆合成孔径雷达(ISAR)图像,提出了表面粗糙的复杂目标全极化ISAR图像快速仿真方法。该方法预先对车辆和飞机等复杂目标表面粗糙程度进行分级定量描述,并以改进的射线弹跳法和等效边缘流法快速预估来自目标粗糙表面的镜面反射和多次反射贡献以及细分边缘的绕射贡献,经相干叠加获得目标的精确电磁散射数据,最后进行成像处理得到高质量全极化ISAR图像。标准体、飞机和车辆目标的仿真实验结果验证了该方法的准确性和有效性。     

Quantitative SNR analysis for ISAR imaging using jointtime-frequency analysis-Short time Fourier transform

V.C. Chen recently presented an inverse synthetic aperture radar (ISAR) imaging technique using the joint time-frequency analysis (JTFA), which has been shown having a better performance for maneuvering targets over the conventional Fourier transform method. The main reason is because the frequencies of the radar returns of the maneuvering targets are time varying and a JTFA is a technique that is suitable for such signals, in particular a JTFA may concentrate a wideband signal, such as a chirp, while it spreads noise. We quantitatively study the signal-to-noise ratio (SNR) in the ISAR imaging using one of the typical JTFA techniques, namely the short time Fourier transform (STFT). We show that the SNR increases in the joint time-frequency (TF) domain over the one in the time or the frequency domain alone both theoretically and numerically. This quantitatively shows the advantage of the JTFA technique for the ISAR imaging     

双基角时变下的空间目标BISAR自聚焦算法

以空间目标为研究对象,针对双基地逆合成孔径雷达(BISAR)成像中双基角变化及同步误差导致的二维ISAR像散焦问题,提出了基于粒子群优化(PSO)的非参数自聚焦算法。算法首先将回波中平动和转动及同步误差等因素导致的相位变化项统一建模,其次将二维图像对比度最大作为优化目标,利用PSO算法对所有高次项相位进行整体优化估计,然后对高阶相位项进行补偿,最后基于补偿后剩余的一阶线性相位项进行方位压缩得到目标的二维ISAR像。算法可解决参数相位误差估计法中因模型误差导致的聚焦精度下降问题,同时也降低了BISAR自聚焦算法的复杂度。通过与参数法自聚焦算法的性能进行对比仿真实验,验证了算法的有效性。     

In This Issue - Technically

For a successful enemy maneuver, their most important action is the ability to identify, locate, and track their correct target. High-resolution imaging sensors such as the inverse synthetic aperture radar perform this action in the most effective way and are especially useful against low radar cross-section targets. Once the correct target is acquired and identified, the decision to engage is made and the weapons are selected. Counter-targeting is the attempt to prevent (or degrade) the engage-and-launch-weapons decision by the enemy. This paper describes an all-digital image synthesizer technique capable of generating realistic false-target images for counter-targeting using modern digital radio frequency memory technology. Uses in counter-lock on for coherent seekers in the terminal mode are also discussed. Examples of the output false target image capability are presented.     

Angle/Doppler estimation in heavy-tailed clutter backgrounds

This work describes new methods on the modeling of the amplitude statistics of airborne radar clutter by means of alpha-stable distributions. We develop joint target angle and Doppler, maximum likelihood-based estimation techniques from radar measurements retrieved in the presence of impulsive uncorrelated noise modeled as an alpha-stable random process. We derive the Cramer-Rao bounds (CRBs) for the additive Cauchy interference scenario to assess the best case estimation accuracy which can be achieved. In addition, we introduce a new joint spatial- and Doppler-frequency high-resolution estimation technique based on the fractional lower order statistics of the measurements of a radar array. Simulation results demonstrate that the proposed methods can be of interest in the study of space-time adaptive processing (STAP) for airborne pulse Doppler radar arrays operating in impulsive interference environments     

MTI data clustering and formation recognition

Image exploitation technology approaches have generally focused on the detection and spatial analysis of stationary groups of objects on the ground using various sensors. While spatial arrangement is clearly necessary in analyzing military formations, it is usually not sufficient. Typically the arrangement must be examined within some context in order to interpret a pattern of deployment. For moving objects the spatial arrangement of the group relative to the direction of motion is key to recognizing the formation. By examining ground moving target indicator (MTI) radar data over time, motion can be inferred and used to establish a context for interpreting the spatial arrangement of the data. New techniques that exploit the multitemporal nature of MTI data are described. The first is a space-time clustering technique that locates compact groups of objects that persist in time. The technique Is an application of Marr and Hildreth's edge detection methodology to the dual problem of region segmentation, or more accurately, volumetric segmentation of space-time. The second technique is based on the use of the Hough transform for recognizing moving formations such as columns, wedges, and lines abreast by analyzing the shape of clustered MTI detections (specifically the orientation of linear arrangements within the group) with respect to their direction of motion. Preliminary results from simulated MTI data sets are presented     

Modified Difference Change Detector for Small Targets in SAR Imagery

One of the most straightforward techniques for detecting changes in an image involves forming the difference between a test image and a reference image. Unfortunately, such a technique can give rise to a large number of false alarms due to the statistical variability of the underlying pixel values, as has been well established within the radar community over the years. One method for dealing with this large number of false alarms involves forming the ratio, rather than the difference, of two synthetic aperture radar (SAR) images. We introduce a modified version of the standard differencing technique to overcome problems associated with pixel value variability. The new (modified) differencing approach utilizes assumptions about the statistics of the image background and the object being sought (target) to reduce the number of false alarms due to highly variable background (clutter) regions, and it includes the standard ratio test as a special case. In fact, we find that the modified difference approach can also be viewed as a modified version of the ratio test with a threshold that varies as a function of the background clutter radar cross section (RCS). We also present an abridged, albeit suboptimal, version of this approach that eliminates assumptions regarding the target's probability distribution, and we analyze both of the approaches. We then compare these results with those obtained with a standard ratio test, and illustrate how the modified difference test reduces to the ratio test under certain operating conditions. The abridged version of the modified approach is applied to high resolution synthetic aperture radar imagery and compared with results obtained with the classical differencing technique, and following this, the modified difference technique is compared with the standard ratio test. Results suggest that under appropriate conditions the abridged, modified technique can successfully detect changes without the need for any image segmentation.     

Development of airborne moving target radar for long range surveillance

The following topics are discussed in the context of the development of an airborne moving target radar for long range surveillance: US Navy long range shipborne radar; Cadillac I airborne early warning (AEW) radar; Cadillac II airborne early warning (AEW) radar; airborne moving target indicating (AMTI) radar; related post-war radar activities; and the invention of the displaced center antenna. Among the topics studied is the use of a monopulse antenna in an MTI radar to remove the degradation of the MTI caused by rapid scanning of the antenna. A method of using a monopulse antenna for motion compensation in airborne MTI is discussed.<>     

Synthetic Aperture Imaging Radar and Moving Targets

This paper considers the effects of slowly moving targets as they appear in the output of an airborne coherent side-looking synthetic aperture imaging radar. The image of a moving reflector is described, and two approaches to airborne moving target indication (AMTI) are summarized. It is shown that the effects of target movement are decreased as the radar scan rate is increased, and are increased as the (Doppler processed) compression ratio is increased.     

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