FOPEN SAR imaging using UWB step-frequency and random noisewaveforms

The detection and identification of targets obscured by foliage have been topics of great interest. Several synthetic aperture radar (SAR) experiments have demonstrated promising images of terrain and man-made objects obscured by dense foliage, by using either linear frequency modulation (LFM) or step-frequency waveforms. We present here the methodology and results of a comparative study on foliage penetration (FOPEN) SAR imaging using ultrawideband (UWB) step-frequency and random noise waveforms. A statistical-physical foliage transmission model is developed for simulation applications. The foliage obscuring pattern is analyzed by means of the technique of paired echoes. The results of the comparative study demonstrates the ability of a UHF band UWB random noise radar to be used as a FOPEN SAR. Advantages of the random noise radar system include covert detection and immunity to radio frequency interference (RFI)     

Geometric accuracy in airborne SAR images

Uncorrected across-track motions of a synthetic aperture radar (SAR) platform can cause both a severe loss of azimuthal positioning accuracy in, and defocusing of, the resultant SAR image. It is shown how the results of an autofocus procedure can be incorporated in the azimuth processing to produce a fully focused image that is geometrically accurate in azimuth. Range positioning accuracy is also discussed, leading to a comprehensive treatment of all aspects of geometric accuracy. The system considered is an X-band SAR     

Foliage attenuation and backscatter analysis of SAR imagery

The ability of a synthetic aperture radar (SAR) to detect targets under foliage is in part determined by the attenuation suffered by radiation propagating through the foliage and the backscatter from the foliage. MIT Lincoln Laboratory made measurements of foliage attenuation and backscatter using the NASA/JPL-UHF, L-, C-band fully-polarimetric SAR in July 1990. In this experiment, a 48 km² forested area near Portage, Maine was imaged. Twenty-seven 8 ft trihedral corner reflectors were arrayed throughout the imaged area in order to measure foliage attenuation. Ground truth was recorded at the time of the experiment in order to correlate the attenuation and backscatter results with foliage biophysical properties. The probability densities for foliage attenuation and for backscatter are determined as functions of frequency, polarization, and depression angle     

Multichannel whitening of SAR imagery

The presence of speckle in synthetic aperture radar (SAR) imagery makes image interpretation more difficult and worsens the performance of algorithms designed to detect objects in the imagery. Image processing techniques to reduce speckle usually do so at the expense of spatial resolution. Multichannel whitening is one image processing technique that reduces image speckle while maintaining spatial resolution. Multichannel whitening is applied to imagery recorded during a foliage penetration experiment undertaken by MIT Lincoln Laboratory using the NASA/JPL UHF, L-, C-band fully polarimetric SAR in July 1990. In this experiment, a 50 km² forested area near Portage, Maine was imaged. Twenty-seven 8 ft trihedral corner reflectors were arrayed throughout the imaged area beneath the foliage in order to measure foliage attenuation. The detection performance for corner reflectors under foliage is compared for the raw data and whitened data, and the predictions of a product model for the degree of speckle reduction are compared with the data     

3-D E-CSAR imaging of a T-72 tank and synthesis of its SAR reconstructions

The results of three-dimensional (3-D) imaging of a T-72 tank using its angular azimuthal (turntable) and linear elevation synthetic aperture data at X band are presented. This is achieved using an accurate and computationally efficient wavefront (Fourier-based) reconstruction algorithm for elevation and circular (E-CSAR) data. The E-CSAR 3-D images are then used to synthesize 2-D spotlight and stripmap slant plane synthetic aperture radar (SAR) images of the target at a desired range and squint angle. For this purpose, a procedure is introduced that incorporates the spatially varying azimuthal and elevation Doppler signatures of individual reflectors on the target as well as the mean range, azimuth, and elevation of the flight path. Results using the E-CSAR images of the T-72 tank are provided.     

A Model for Generating Synthetic VHF SAR Forest Clutter Images

We propose a model for generating low-frequency synthetic aperture radar (SAR) clutter that relates model parameters to physical characteristics of the scene. The model includes both distributed scattering and large-amplitude discrete clutter responses. The model also incorporates the SAR imaging process, which introduces correlation among image pixels. The model may be used to generate synthetic clutter for a range of environmental operating conditions for use in target detection performance evaluation of the radar and automatic target detection/recognition algorithms. We derive a statistical representation of the proposed clutter model's pixel amplitudes and compare with measured data from the CARABAS-II SAR. Simulated clutter images capture the structure and amplitude responses seen in the measured data. A statistical analysis shows an order of magnitude improvement in model fit error compared with standard maximum-likelihood (ML) density fitting methods.     

机动目标的逆合成孔径雷达成像

 逆合成孔径雷达(ISAR)和合成孔径雷达 (SAR)都是利用目标 (场景)与雷达的相对运动,提高横向分辨率,实现对目标 (场景 )的成像。SAR的运动方是雷达平台,可控制作平稳飞行,且用仪器测校其偏离误差;ISAR的运动方通常是非合作目标,运动不受控制,且难以精确测量。当目标作机动飞行时,以目标作固定基准,雷达等效地在空间形成流形复杂的逆合成孔径 (阵列 ),对这种情况下成像的问题进行了系统的研究。     

SAR image formation via semiparametric spectral estimation

A new algorithm, referred to as the SPAR (Semiparametric) algorithm, is presented herein for target feature extraction and complex image formation via synthetic aperture radar (SAR). The algorithm is based on a flexible data model that models each target scatterer as a two-dimensional (2-D) complex sinusoid with arbitrary unknown amplitude and constant phase in cross-range and with constant amplitude and phase in range. By attempting to deal with one corner reflector, such as one dihedral or trihedral, at a time, the algorithm can be used to effectively mitigate the artifacts in the SAR images due to the flexible data model. Another advantage of SPAR is that it can be used to obtain initial conditions needed by other parametric target feature extraction methods to reduce the total amount of computations needed. Both numerical and experimental examples are provided to demonstrate the performance of the proposed algorithm     

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     

On the resolvability of sinusoidal parameter estimates [andapplication to SAR target features]

The resolvability of 2-D (two-dimensional) sinusoidal parameter estimates is studied. These sinusoids describe the target features in SAR (synthetic aperture radar) applications. We analyze the resolvability by considering the frequency estimates of the sinusoids. Our results may be used by target classification algorithms to better classify radar targets in SAR applications     

Moving Targets Processing in SAR Spatial Domain

This paper presents a novel technique to estimate the initial coordinates and velocity vector of moving targets, including those with velocities above the Nyquist limit, using a single synthetic aperture radar (SAR) sensor without increasing the pulse repetition frequency (PRF). The basic reasoning is that, although the returned echoes may be undersampled in the azimuth direction, their phase and amplitude are informative with respect to the moving target trajectory parameters. Therefore, the so-called blind angle ambiguity, inherent to systems using a single SAR sensor, is overcome. The proposed method samples the data in the spatial domain, along the signature curve which depends on the moving target trajectory parameters. The resulting algorithm is a highly efficient (from the computational point of view) ID matched filter. The effectiveness of the proposed scheme is illustrated using simulated SAR data and real data from the MSTAR public release data set, corresponding to a static SAR scene and a static BTR-60 with simulated motion.     

Detecting moving targets in SAR imagery by focusing

A new method for detecting moving targets in a synthetic aperture radar (SAR) image is presented. It involves segmenting a complex-valued SAR image into patches, focusing each patch separately, and measuring the sharpness increase in the focused patch. The algorithm is sensitive to azimuth velocities and is exquisitely sensitive to radial accelerations of the target, allowing it to detect motion in any direction. It is complementary to conventional Doppler-sensing moving target indicators, which can sense only the radial velocity of rapidly moving targets.     

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。     

Foliage penetration experiment

This series papers describes analyses of a foliage penetration experiment undertaken by MIT Lincoln Laboratory to assess the ability of synthetic aperture radar (SAR) to detect targets under trees. Data were taken using the NASA/JPL UHF, L-, C-band fully polarimetric SAR over a forested area in Maine in July 1990. Future experiments are planned to measure the polarimetric properties of clutter and targets using the latest ultrawideband sensors with submeter resolutions and fully polarimetric data collection capabilities     

Coherent spatial filtering for SAR detection of stationary targets

Analysis of UHF synthetic aperture radar (SAR) images has revealed a spatially correlated phase structure over a resolved target such as a long wire or a large truck. This phase variation, approximated by a simple, range-dependent factor 4πr/λ, results in a line-shaped image spatial spectrum. Such image phase and spectral features can be exploited by coherent spatial filtering to improve target-to-clutter ratios of large targets and stationary target detectability in a strong clutter environment     

一种FMCW SAR地面运动目标谱图域参数估计方法

对调频连续波(FMCW)合成孔径雷达(SAR)地面运动目标的参数估计方法进行了研究,采用相位中心偏置天线(DPCA)技术对地杂波进行抑制,分析了载机及地面运动目标连续运动对回波信号的影响,推导了采用DPCA技术引入的回波慢时间包络(STE)项与地面运动目标参数之间的关系。在此基础上,提出了一种地面运动目标谱图域参数估计方法,该方法首先利用Radon变换在谱图域估计导致回波信号距离走动的目标等效径向速度,并对距离走动进行校正;其次,在谱图域中提取运动目标回波幅度,根据STE项引起的回波幅度变化与目标方位向速度之间的关系,估计目标的方位向速度,并进一步求解相应的目标径向速度。所提方法能够在谱图域完成地面运动目标二维速度估计,最后的仿真实验验证了所提方法的有效性和可行性。     

运动补偿用惯性器件误差对SAR成像分辨率的影响研究

 为提高合成孔径雷达（SAR）系统的性价比，必须根据SAR成像分辨率的要求和整体系统参数，设计相应精度的运动补偿用捷联惯导系统。在确定SAR运动补偿系统方案和安装方式的基础上，分析不同方向的加速度计和陀螺仪误差对天线相位中心位置测量误差的影响，并利用位置测量误差与SAR成像分辨率之间的关系，进一步明确了不同方向的加速度计和陀螺仪对SAR成像分辨率的影响。研究表明：基于SAR的工作原理和安装方式，x方向加速度计和y方向陀螺仪对SAR成像分辨率的影响明显比其他惯性器件严重；相同误差水平的惯性器件对SAR成像分辨率的影响随着合成孔径时间和工作波长的不同而不同，时间越长，波长越短，影响则越严重。SAR成像仿真证明了结论的正确性。研究结果对于研制高性价比SAR成像运动补偿系统有一定的理论指导意义。     

基于Gibbs-Markov随机场与连通聚类的SAR图像恢复

在传统的马尔可夫随机场(MRF)的图像建模方法基础上利用合成孔径雷达(SAR)图像的固有特性对Gibbs-MRF模型进行改进复原SAR图像,并进一步提出用数字形态学中连通性理论进行图像分割。在SAR图像像素空间的邻域内,估计最大后验概率(MAP)时引用Gamma分布代替传统的瑞利分布恢复数据,同时利用像素强度值相关性的连通模型将目标较好地提取出来。充分利用了SAR图像的数字形态信息和像素强度之间的相关性,得到了更好的分割效果。仿真实验说明本文方法是有效的。     

一种提高距离分辨率的FMCW SAR RD成像算法

调频连续波合成孔径雷达（FMCW SAR）是一种新近提出来的成像雷达体制,它结合调频连续波与合成孔径成像技术,具有体积小、重量轻、成本低、分辨率高等一系列优点。从频谱的角度进行分析,FMCW SAR的距离分辨率取决于频率测量分辨率。文章研究了一种FMCW SAR高距离分辨率成像算法——利用FFT得到差频信号谱峰的粗略范围,再对这一范围进行ChirpZ变换,从而实现距离高精度估计,并且避免了大的计算量。仿真结果表明该方法的有效性。     

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。