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     

Improved target classification using optimum polarimetric SARsignatures

We present a new method for automatic target/object classification by using the optimum polarimetric radar signatures of the targets/objects of interest. The state-of-the-art in radar target recognition is based mostly either on the use of single polarimetric pairs or on the four preset pairs of orthogonal polarimetric signatures. Due to these limitations, polarimetric radar processing has been fruitful only in the area of noise suppression and target detection. The use of target separability criteria for the optimal selection of radar signal state of polarizations is addressed here. The polarization scattering matrix is used for the derivation of target signatures at arbitrary transmit and receive polarization states (arbitrary polarization inclination angles and ellipticity angles). Then, an optimization criterion that minimizes the within-class distance and maximizes the between-class metrics is used for the derivation of optimum sets of polarimetric states. The results of the application of this approach on real synthetic aperture radar (SAR) data of military vehicles are obtained. The results show that noticeable improvements in target separability and consequently target classification can be achieved by the use of the optimum over nonoptimum signatures     

Optimal speckle reduction in polarimetric SAR imagery

Speckle is a major cause of degradation in synthetic aperture radar (SAR) imagery. With the availability of fully polarimetric SAR data, it is possible to use the three complex elements (HH, HV, VV) of the polarimetric scattering matrix to reduce speckle. The optimal method for combining the elements of the scattering matrix to minimize image speckle is derived, and the solution is shown to be a polarimetric whitening filter (PWF). A simulation of spatially correlated, K-distributed, fully polarimetric clutter is then used to compare the PWF with other, suboptimal speckle-reduction methods. Target detection performance of the PWF, span, and single-channel |HH|² detectors is compared with that of the optimal polarimetric detector (OPD). A novel, constant-false-alarm-rate (CFAR) detector (the adaptive PWF) is as a simple alternative to the OPD for detecting targets in clutter. This algorithm estimates the polarization covariance of the clutter, uses the covariance to construct the minimum-speckle image, and then tests for the presence of a target. An exact theoretical analysis of the adaptive PWF is presented; the algorithm is shown to have detection performance comparable with that of the OPD     

Optimal polarimetric processing for enhanced target detection

The results of a study of several polarimetric target detection algorithms are summarized. The algorithms were tested using real target-in-clutter data collected by the Lincoln Laboratory 35 GHz synthetic aperture radar (SAR) sensor. Fully polarimetric measurements (HH, HV, VV) are processed into intensity imagery using adaptive and nonadaptive polarimetric whitening filters (PWFs). Then a two-parameter constant false alarm rate (CFAR) detector is run over the imagery to detect the targets. Nonadaptive PWF processed imagery is shown to provide better protection performance than either adaptive PWF processed imagery or single-polarimetric-channel HH imagery. In addition, nonadaptive PWF processed imagery is shown to be visually clearer than adaptive processed imagery     

RFI suppression for ultra wideband radar

An estimate-and-subtract algorithm is presented for the real-time digital suppression of radio frequency interference (RFI) in ultrawideband (UWB) synthetic aperture radar (SAR) systems used for foliage- and ground-penetrating imaging. The algorithm separately processes fixed- and variable-frequency interferers. Excision of estimated targets greatly reduces bias in RFI estimates, thereby reducing target energy loss and sidelobe levels in SAR imagery. Performance is demonstrated on data collected with the Army Research Laboratory's UWB rail SAR.     

Fitting a statistical model to SIR-C SAR images of the sea surface

A suite of statistical procedures aimed at assessing to what extent polarimetric and/or multifrequency synthetic aperture radar (SAR) images of the sea surface can be modeled in terms of spherically invariant random vectors and matrices (SIRVs and SIRMs) is presented. The proposed tests assume that images can be described by resorting to the compound-Gaussian model, but do not require any a priori knowledge about the actual first-order probability density function (pdf) of the texture. The tests have also been used to analyze three data sets from STR-C/X-SAR missions.     

UAVSAR: New NASA Airborne SAR System for Research

NASA's Jet Propulsion Laboratory is currently building a reconfigurable, polarimetric L-band synthetic aperture radar (SAR), specifically designed to acquire airborne repeat track SAR data for differential interferometric measurements. Differential interferometry can provide key deformation measurements, important for studies of earthquakes, volcanoes, and other dynamically changing phenomena. Using precision real-time GPS and a sensor controlled flight management system, the system will be able to fly pre-defined paths with great precision. The expected performance of the flight control system will constrain the flight path to be within a 10 m diameter tube about the desired flight track. The radar will be designed to be operable on a Unpiloted Arial Vehicle (UAV) but will initially be demonstrated on a NASA Gulfstream III. The radar will be fully polarimetric, with a range bandwidth of 80 MHz (2 m range resolution), and will support a 16 km range swath. The antenna will be electronically steered along track to assure that the antenna beam can be directed independently, regardless of the wind direction and speed. Other features supported by the antenna include elevation monopulse and pulse-to-pulse re-steering capabilities that will enable some novel modes of operation. The system will nominally operate at 45,000 feet (13,800 m). The program began as an Instrument Incubator Project (IIP) funded by NASA Earth Science and Technology Office (ESTO).     

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     

Effects of polarization and resolution on SAR ATR

Lincoln Laboratory is investigating the detection and classification of stationary ground targets using high resolution, fully polarimetric, synthetic aperture radar (SAR) imagery. A study is summarized in which data collected by the Lincoln Laboratory 33 GHz SAR were used to perform a comprehensive comparison of automatic target recognition (ATR) performance for several polarization/resolution combinations. The Lincoln Laboratory baseline ATR algorithm suite was used, and was optimized for each polarization/resolution case. Both the HH polarization alone and the optimal combination of HH, HV, and VV were evaluated; the resolutions evaluated were 1 ft/spl times/1 ft and 1 m/spl times/1 m. The data set used for this study contained approximately 74 km/sup 2/ of clutter (56 km/sup 2/ of mixed clutter plus 18 km/sup 2/ of highly cultural clutter) and 136 tactical target images (divided equally between tanks and howitzers).     

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     

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。     

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     

Studies of target detection algorithms that use polarimetric radardata

Algorithms are described which make use of polarimetric radar information in the detection and discrimination of targets in a ground clutter background. The optimal polarimetric detector (OPD) is derived. This algorithm processes the complete polarization scattering matrix (PSM) and provides the best possible detection performance from polarimetric radar data. Also derived is the best linear polarimetric detector, the polarimetric matched filter (PMF), and the structure of this detector is related to simple polarimetric target types. New polarimetric target and clutter models are described and used to predict the performance of the OPD and the PME. The performance of these algorithms is compared with that of simpler detectors that use only amplitude information to detect targets. The ability to discriminate between target types by exploring differences in polarimetric properties is discussed     

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)     

一种改进的FMCW SAR RD成像算法

FMCWSAR将调频连续波与合成孔径成像技术结合于一体,是一种新近被提出来的成像雷达体制,它以其体积小、重量轻、成本低、分辨率高等一系列优点,引起越来越多的关注。然而,在FMCWSAR系统中,雷达连续不断地发射信号,调制信号周期相对较长,停一走（STOP AND GO）近似不再成立,所以要用合适的算法来实现成像。针对FMCW SAR的特点,详细推导了停一走近似失效时FMCW SAR的信号模型及处理过程,提出了一种改进的RD算法。此方法是通过补偿连续运动引入的多普勒频移,消除连续运动的影响。     

A state-of-the-art review in radar polarimetry and its applicationsin remote sensing

The authors assess the state of the art, focusing on their own contributions. Covered areas are the electromagnetic inverse problem in radar polarimetry, coherent polarization radar theory, partially coherent polarization radar theory, vector (polarization) inverse scattering approaches, the polarimetric matched filter approach, polarimetric Doppler radar applications in meteorology and oceanography, and image fidelity in microwave vector diffraction tomographic imaging     

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...     

Adaptive polarimetric target detection with coherent radar. I.Detection against Gaussian background

The derivation of a completely adaptive polarimetric coherent scheme to detect a radar target against a Gaussian background is presented. A previously proposed Generalized Likelihood Ratio Test (GLRT) polarimetric detector is extended to the case of a general number of channels; this exploits the polarimetric characteristics of the received radar echoes to improve the detection performance. Together with the fully adaptive scheme, a model-based detector is derived that has a lower estimation loss. A complete theoretical expression is derived for the detection performance of both proposed polarimetric detectors. They are shown to have Constant False Alarm Rate (CFAR) when operating against Gaussian clutter, but to be sensitive to deviations from the Gaussian statistic. The application to recorded radar data demonstrates the performance improvement achievable in practice     

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     

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