无需辅助数据的分布式目标自适应检测器

在非高斯背景和没有辅助数据的条件下,研究了高分辨率雷达分布式目标的自适应检测问题.首先采用有序检测理论和协方差矩阵的迭代估计方法粗略估计散射点集合,进一步利用迭代估计方法获得协方差矩阵的近似最大似然估计,提出了无需辅助数据的自适应检测器(ADWSD).ADWSD在非高斯背景下具有近似恒虚警率特性,且检测性能远好于修正的...     

VSAR: a high resolution radar system for ocean imaging

The velocity synthetic aperture radar (VSAR) is a conceptual synthetic aperture radar (SAR)-based sensor system for high resolution ocean imaging. The VSAR utilizes data collected by a multielement SAR system, to extract information not only about the radar reflectivity of the observed area, but also about the radial velocity of the scatterers in each pixel. This is accomplished by making use of the phase information contained in multiple SAR images, and not just the magnitude information as in conventional SAR. Using this velocity information, the VSAR attempts to compensate for the velocity distortion inherent in conventional SAR and to reconstruct the ocean reflectivity. We present the basic theory of the VSAR system and its performance. We also provide an analysis of the VSAR imaging mechanism for a statistical model of the radar returns, designed to capture the effects of speckle and of resolution degradation due to the decorrelation of the radar returns     

Multiple moving target detection and trajectory estimation using a single SAR sensor

A novel methodology is presented for determining the velocity and location of multiple moving targets using a single strip-map synthetic aperture radar (SAR) sensor. The so-called azimuth position uncertainty problem is therefore solved. The method exploits the structure of the amplitude and phase modulations of the returned echo from a moving target in the Fourier domain. A crucial step in the whole processing scheme is a matched filtering, depending on the moving target parameters, that simultaneously accounts for range migration and compresses two-dimensional signatures into one-dimensional ones without losing moving target information. A generalized likelihood ratio test approach is adopted to detect moving targets and derive their trajectory parameters. The effectiveness of the method is illustrated with synthetic and real data covering a wide range of targets velocities and signal-to-clutter ratios (SCRs). Even in the case of parallel to platform moving target motion, the most unfavorable scenario, the proposed method yields good results for, roughly, SCR > 10 dB.     

A Velocity Estimation Algorithm of Moving Targets using Single Antenna SAR

A new algorithm is proposed for velocity estimation of moving targets in single antenna synthetic aperture radar (SAR). Based on the fact that different velocity vectors cause different geometrical figures of the two-dimensional (2-D) signature in the range-Doppler (RD) domain, this algorithm estimates the azimuth and range velocities by a 2-D search such that the range cell migration correction (RCMC) and the second range compression (SRC) are correctly performed. It is shown that, using the proposed algorithm, the Doppler ambiguity problem can be avoided and satisfactory accurate velocity estimation can be obtained in high signal-to-clutter ratio (SCR) scenarios.     

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     

Synthetic aperture radar image formation from compressed data usinga new computation technique

A convolution technique is proposed that allows direct reconstruction of the processed synthetic-aperture radar (SAR) image from the digitally-sampled, block-encoded raw data. This computational compression technique reduces the number of arithmetic operations from that required by fast Fourier transform (FFT) convolution for SAR processing. SAR phase histories are block encoded and directly processed into an image where only arithmetic additions are required for the processing. For SAR data previously block encoded, the processing time is reduced by a factor of 100 or more. A speed-up of three times over SAR processing by FET convolution has been demonstrated when both computation of the block encoding and subsequent direct processing are included in the time. SAR image quality measurements for a method of block encoding called vector quantization at compression ration ranging from 5:1 to 50:1 show image degradation proportional to the compression ratio. For a 5:1 compression radio, image quality measurements show minimal degradation     

High Range Resolution Profiles as Motion-Invariant Features for Moving Ground Targets Identification in SAR-Based Automatic Target Recognition

A quantitative model analysis is presented to justify the extraction of high range resolution (HRR) profiles from synthetic aperture radar (SAR) images as motion-invariant features for identifying moving ground targets. A comparative study is conducted to assess the effectiveness in the identification process between using HRR profiles and SAR images as target signatures. The results indicate that HRR profiles are just as viable as SAR image for identification. Furthermore, a score-level multi-look fusion identification method has been investigated. It is found that a correct accurate identification rate of greater than 99 percent, a low false alarm rate, and a high level of identification confidence can be achieved, providing very robust performance.     

Tradeoff between Picture Element Dimensions and Noncoherent Averaging in Side-Looking Airborne Radar

An experiment was performed to determine the effect on radar image interpretation of: 1) rectangular instead of square pixels, and 2) spatial resolution in the presence of noncoherent averaging. The result is a proof of the hypothesis that interpretability of images is determined by a "spatial-gray-level (SGL) resolution volume" that is the product of the range resolution, the azimuth resolution, and a gray-level resolution. The last is defined as the ratio of the value exceeded 10 percent of the time to that exceeded 90 percent of the time for a chi-square distribution having twice as many degrees of freedom as the number of independent samples averaged. Since the area of the pixel enters, rather than explicit dependence on range or azimuth resolution, rectangular pixels are as interpretable as square pixels having the same area. The SGL accounts for the effect of reduction in fading on interpretability. The numerical interpretability assigned by experienced image interpreters asked to look for specific classes of targets was found to fall exponentially with increasing SGL volume, with a scale determined by the class of target. The experiment showed that, for most of the tasks assigned to the interpreters, the interpretability is reduced to 37 percent for a fully focussed synthetic-aperture radar (SAR) (1-look) for a 10-m (33-ft) square pixel. With an infinite number of samples averaged, the comparable square-pixel dimension is 48 m (157 ft). This is consistent with results obtained using LANDSAT images of about 60-m resolution.     

Target prescreening based on a quadratic gamma discriminator

This work presents the development, analysis and validation of a new target discrimination module for synthetic aperture radar (SAR) imagery based on an extension of gamma functions to 2-D. Using the two parameter constant false-alarm rate (CFAR) stencil as a prototype, a new stencil based on 2-D gamma functions is used to estimate the intensity of the pixel under test and its surroundings. A quadratic discriminant function is created from these estimates, which is optimally adapted with least squares in a training set of representative clutter and target chips. This discriminator is called the quadratic gamma discriminator (QGD). The combination of the CFAR and the QGD was tested in realistic SAR environments and the results show a large improvement of the false alarm rate with respect to the two-parameter CFAR, both with high resolution (1 ft) fully polarimetric SAR and with one polarization, 1 m SAR data     

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     

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。     

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     

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     

A multiresolution approach to discrimination in SAR imagery

We develop and test a new algorithm for discriminating man-made objects from natural clutter in synthetic-aperture radar (SAR) imagery. This algorithm exploits characteristic variations in speckle pattern as image resolution is varied from course to fine. We model these variations as an autoregression in scale, and then use the autoregressive model to define a multiresolution log-likelihood ratio discriminant. We incorporate this discriminant into the existing Lincoln Laboratory SAR system for automatic target recognition (ATR), and test the augmented system by applying it to millimeter-wave SAR imagery having 0.3 m resolution and representing 56 square kilometers of terrain. At a probability of detection of 0.95, the addition of the multiresolution discriminant reduces the number of natural-clutter false alarms by a factor of six.     

MMW system trade-offs

A brief review is given of the current state of knowledge of millimeter-wave atmospheric propagation and clutter characteristics and the detection performance of two air-to-ground fire-control systems evaluated in terms of their ability to detect a 40-m² target in the presence of atmospheric attenuation and three types of clutter. Generally, the 35-GHz system considered performed better in terms of signal-to-noise ratio performance and in signal-to-clutter ratio performance for light clutter. In heavy clutter, the 95-GHz system performed significantly better than the 35-GHz system. For 300-m altitude with refrozen snow clutter background, neither system developed a large enough signal-to-clutter radio to detect the target reliably     

基于迁移学习的SAR目标超分辨重建

针对合成孔径雷达(SAR)目标超分辨重建问题,提出了一种基于迁移学习的超分辨方法。在光学图像梯度域中联合训练超完备字典与稀疏编码映射,利用半耦合字典联系SAR图像与光学图像,寻找SAR图像在半耦合字典下的稀疏编码,并在高分辨率字典下完成重建。结合SAR图像的先验信息,使用正则化方法对SAR目标进行特征增强。所提方法在TerraSAR-X数据和MSTAR数据上进行了仿真实验,重建结果表明,相比目前的插值方法和稀疏表示方法,所提方法空间分辨率可提高0.5~1.5个像素。正则化增强结果表明,引入稀疏先验的正则化增强能够进一步提高空间分辨率并抑制杂波比,最后分析了正则化参数的选取对图像质量的影响。     

MTI Improvement Factors for Weighted DFTs

The use of the discrete Fourier transform (DFT) to enhance the detection of moving targets in ground clutter is examined. The improvement factor, defined as the signal-to-clutter ratio at the DFT processor output compared with that of the input, is given as a function of normalized clutter spectral width for various weighting functions on the DFT input. The effect of quantization of the weights on the improvement factor is also examined.     

Optimum Processing of Unequally Spaced Radar Pulse Trains for Clutter Rejection

A train of radar pulses from one resolution cell can be processed coherently to reject echoes from external clutter and detect targets moving radially with respect to the clutter. Optimum methods of signal processing are defined for systems in which the interpulse spacings are multiply staggered to avoid target blind speeds. Likelihood ratio tests are developed for systems in which the target Doppler frequency is known a priori and for systems employing a bank of filters to cover the target Doppler band. To implement such tests, the N pulses in the train are added with complex weights and the amplitude of the sum compared with a detection threshold. The set of weights which maximizes the average signal-to-clutter ratio is also computed for a single-filter system with unknown target Doppler frequency. When the clutter autocorrelation function is exponential, the clutter covariance matrix can be inverted analytically. This latter result is useful for comparing different interpulse-spacing codes for a particular system application.     

用于SAR运动补偿的DGPS/SINS组合系统研究

使用考虑位置误差相关项的伪距率观测模型 ,研究了用于合成孔径雷达运动补偿的差分 GPS/ SINS伪距率组合系统。结果表明 ,组合系统的长期位置精度能达到 1 m左右。 GPS数据更新率低于 INS,在 GPS测量时间间隔内 ,组合系统的性能仅由 INS决定。虽然 INS误差随时间积累 ,在 GPS数据更新率为 1 s的情况下 ,即使采用中等精度的惯性仪表 ,其相对位置精度为厘米级 (这里相对位置精度指组合系统在 GPS测量时间间隔内位置误差的变化范围)。     

聚束SAR扩展Chirp Scaling成像算法.

在合成孔径雷达（SAR Synthetic Aperture Radar)的成像算法中，Chrip Scaling成像算法具有计算效率高的优点，因此得到了较为广泛的应用。详细研究了子孔径扩展Chirp Scaling算法在高分辩率聚束模式SAR中的应用，包括子孔径划分和方位向处理问题，针对A.Moreira等1996年所提算法在处理聚束SAR数据时所产生的问题，给出了经过改进的适合于大斜视角处理的整个计算过程的完整表达式。在给出点目标仿真的同时，利用E-SAR实际数据对述方法进行了验证，结果对具体的兼容条带和聚束两种工作模式的SAR处理机设计具有一定的参考价值。