Polarimetric Characteristics of sea ice in the sea of Okhotsk observed by airborne L-band SAR

The Phased-Array L-Band SAR (PALSAR) aboard the Advanced Land Observing Satellite (ALOS) is capable of globally acquiring fully polarimetric data. In order to confirm the ability of L-band polarimetric synthetic aperture radar (SAR) to investigate sea ice before the ALOS launch, we conducted a field experiment using an airborne Polarimetric and Interferometric SAR (Pi-SAR) in the Sea of Okhotsk in 1999. This paper presents the analyzed results of data acquired in that experiment. The extracted polarimetric parameters of several ice types suggested that polarimetric coherences and phase differences between right-right (RR) and left-left (LL) are good candidates for discriminating ice types. The polarimetric anisotropy as well as the beta angle of the first eigenvector calculated in the polarimetric decomposition procedure are alternative parameters that are sensitive to ice type differences. Due to the low depolarization characteristics of open water, it could be discriminated from sea ice by scattering entropy in all incidence angle ranges. From the relation between ice thickness and the polarimetric parameters, we found that backscattering coefficients and vertical (VV) to horizontal (HH) backscattering ratio are highly correlated with ice thickness. Since the ratio is sensitive to ice surface dielectric constants, a simple simulation using the integral equation method surface model was conducted by using the physical parameters of typical sea ice. A two-dimensional ice thickness map was derived from an empirical relation between the VV-to-HH backscattering ratio and ice thickness.     

Unsupervised segmentation of polarimetric SAR data using thecovariance matrix

A method for unsupervised segmentation of polarimetric synthetic aperture radar (SAR) data into classes of homogeneous microwave polarimetric backscatter characteristics is presented. Classes of polarimetric backscatter are selected on the basis of a multidimensional fuzzy clustering of the logarithm of the parameters composing the polarimetric covariance matrix. The clustering procedure uses both polarimetric amplitude and phase information, is adapted to the presence of image speckle, and does not require an arbitrary weighting of the different polarimetric channels; it also provides a partitioning of each data sample used for clustering into multiple clusters. Given the classes of polarimetric backscatter, the entire image is classified using a maximum a posteriori polarimetric classifier. Four-look polarimetric SAR complex data of lava flows and of sea ice acquired by the NASA/JPL airborne polarimetric radar (AIRSAR) are segmented using this technique     

Speckle filtering in polarimetric SAR data based on the subspace decomposition

In this paper, a new approach to speckle filtering of synthetic aperture radar (SAR) data is presented. We define a parameter space consisting of two orthogonal subspaces-the signal subspace and the noise subspace. Then, the full polarimetric information from the signal subspace is obtained after speckle filtering. In this way, edges of different kinds of targets are preserved. The effectiveness of this method is demonstrated using the National Aeronautics and Space Administration Jet Propulsion Laboratory airborne L-band polarimetric SAR data.     

Detection of storm-damaged forested areas using airborne CARABAS-II VHF SAR image data

Strong winds cause severe damage worldwide to forested land every year. The devastating storms that struck large parts of Europe in late 1999 destroyed the equivalent of several years of normal forest harvesting, amounting to very large economical sums. Therefore, rapid mapping of damaged areas is of major importance for assessment of short-term actions as well as for long-term reforestation purposes. In this paper, the use of airborne CARABAS-II very high frequency (VHF) (20-90 MHz) synthetic aperture radar (SAR) imagery for high spatial resolution mapping of wind-thrown forests has been investigated and evaluated. The investigation was performed at a test site located in southern Sweden and dominated by Norway spruce forests. A regression model estimating radar backscattering amplitude prior to the storm was developed. The estimated amplitudes were compared to measured amplitudes after the storm. The results clearly show that the backscattering amplitude, at a given stem volume, is considerably higher for wind-thrown forests than for unaffected forests. Furthermore, the backscattering from fully harvested storm-damaged areas was, as expected, significantly lower than from unaffected stands. These findings imply that VHF SAR imagery has potential for mapping wind-thrown forests. However, to prevent ambiguities in increased backscattering caused by normal stem volume growth or wind-fellings, multitemporal change detection techniques using VHF SAR images acquired prior to and after wind-fellings would be preferable.     

The Bayesian hierarchical classifier (BHC) and its application to short vegetation using multifrequency polarimetric SAR

Given an image of a scene comprised of a number of distinct terrain classes, the optimum Bayesian classifier (OBC) provides the highest possible classification accuracy of the imaged scene, provided we have a priori knowledge of the probability density function (pdf) of the sensor's output for each terrain class. If the imaging sensor consists of multiple channels, application of OBC requires knowledge of the joint pdf of the observations made by all the channels. In practice, the volume of data needed in order to generate an accurate multidimensional pdf far exceeds the size of available datasets. The data-size requirement may be relaxed by assuming the pdfs to be Gaussian in form, but such an assumption leads to suboptimum classification performance. This paper addresses the data size issue by (1) taking advantage of the maximum-entropy density estimation (MEDE) technique introduced in a companion paper and (2) using marginal pdfs in a hierarchical approach. Using multidate synthetic aperture radar observations, it was shown that the Bayesian hierarchical classifier introduced in this paper can classify short vegetation classes with an accuracy of 93%, without retraining, compared with an accuracy of 84% for the maximum-likelihood estimator (with Gaussian assumption) and only 74% with ISODATA.     

Radar imaging of moving targets in foliage using multifrequency multiaperture polarimetric SAR

Because of the low signal-to-clutter ratio, it is a difficult problem to detect and image moving targets in foliage. In this paper, a multifrequency multiaperture polarimetric synthetic aperture radar (MFMA POLSAR) system is proposed for imaging of moving targets in foliage. The MFMA POLSAR extends the multifrequency antenna array SAR (MF-SAR) system to multiple polarizations. Full polarization is used in MFMA POLSAR to achieve an optimal polarization adaptive to the environment such that the images obtained by different apertures are of the best coherence that is used to obtain the highest accuracy of the phase estimation. It is also shown that the MFMA POLSAR cannot only accurately locate both the slow and the fast moving targets but also reveal moving targets in foliage.     

A test statistic in the complex Wishart distribution and its application to change detection in polarimetric SAR data

When working with multilook fully polarimetric synthetic aperture radar (SAR) data, an appropriate way of representing the backscattered signal consists of the so-called covariance matrix. For each pixel, this is a 3/spl times/3 Hermitian positive definite matrix that follows a complex Wishart distribution. Based on this distribution, a test statistic for equality of two such matrices and an associated asymptotic probability for obtaining a smaller value of the test statistic are derived and applied successfully to change detection in polarimetric SAR data. In a case study, EMISAR L-band data from April 17, 1998 and May 20, 1998 covering agricultural fields near Foulum, Denmark are used. Multilook full covariance matrix data, azimuthal symmetric data, covariance matrix diagonal-only data, and horizontal-horizontal (HH), vertical-vertical (VV), or horizontal-vertical (HV) data alone can be used. If applied to HH, VV, or HV data alone, the derived test statistic reduces to the well-known gamma likelihood-ratio test statistic. The derived test statistic and the associated significance value can be applied as a line or edge detector in fully polarimetric SAR data also.     

机载导航系统在海上飞行中的应用

机载导航系统对海上飞行作用十分重大,系统向飞行员提供了大量的领航数据,其数据实时改变,如果按照其数据飞行,就意为着飞机的航向要跟着不断地变化,频繁地改变航向并不有利于飞行。所以,飞行员要充分利用机载导航系统的数据,根据领航原理人工引领飞机航行,这样,既能充分发挥机载导航系统数据多、自动测量的优势,又能充分发挥人的作用,完好地完成领航任务。飞机在海上飞行时,地标少,可以利用机载导航系统的数据,实施检查航迹、修正航迹、控制飞机转弯、空域飞行、从海上归航等飞行任务。     

On airborne measurement of the sea surface wind vector by a scatterometer (altimeter) with a nadir-looking wide-beam antenna

A pilot needs operational information about wind over sea as well as wave height to provide safety for a hydroplane landing on water. Near-surface wind speed and direction can be obtained with an airborne microwave scatterometer, a radar designed for measuring the scatter characteristics of a surface. Mostly narrow-beam antennas are applied for such wind measurement. Unfortunately, a microwave narrow-beam antenna has considerable size that hampers its placement on flying apparatus. In this connection, a possibility to apply a conventional airborne radar altimeter as a scatterometer with a nadir-looking wide-beam antenna in conjunction with Doppler filtering for recovering the wind vector over sea is discussed, and measuring algorithms of sea surface wind speed and direction are proposed. The obtained result can be interesting for many studies in oceanography, meteorology, air-sea interaction, and climate change and for creation of an airborne radar system for amphibious airplane safe landing on the sea surface, in particular for search and rescue operations in coastal areas.     

Classification of particles in stratiform clouds using the 33 and95 GHz polarimetric cloud profiling radar system (CPRS)

This paper describes the identification of regions of ice, cloud droplets, rain, mixed-phase hydrometers, and insects in stratiform clouds using 33 and 95 GHz radar measurements of reflectivity, linear-depolarization ratio (LDR), dual-wavelength ratio, and velocity from a single-antenna radar system. First, the radar system, experiment, and data products are described. Then, regions are classified using a rule-based classifier derived primarily from LDR, velocity, and altitude. Next, a region-dependent attenuation-correction algorithm is developed to remove attenuation biases in the reflectivity estimate, and histograms of the corrected data are presented for each data product and class. The labeled regions and attenuation-corrected data are then used to train a neural net and maximum likelihood classifier. These agree with the rule-based classifier 96% and 94% of the time, respectively. Finally, the paper evaluates the importance of measuring dual-frequency parameters, velocity, and depolarization ratio     

Automated georeferencing and orthorectification of Amazon basin-wide SAR mosaics using SRTM DEM data

Frequently large synthetic aperture radar (SAR) mosaics are not precisely georeferenced because topographic distortions are not removed during the mosaicking process due to the lack of adequate digital elevation models (DEMs). The Shuttle Radar Topography Mission (SRTM) has recently provided high-resolution DEM data with nearly global coverage and makes it possible to rectify SAR mosaics. Though techniques are available for rectifying individual scenes of SAR imagery using DEM data, these methods encounter difficulties when rectifying SAR mosaics because abrupt geometric discontinuities occur in SAR mosaics at scene boundaries. This paper introduces an automated method to removing topographic distortions from SAR mosaics and producing orthorectified mosaics, without accessing original SAR images. The procedures include SAR image simulation from DEMs, two-staged image matching between SAR mosaics and the simulated image, automated tie-point derivation and screening, piecewise image rectification for localized adjustment, and production of orthorectified mosaics. The method is used to orthorectify both high-water and low-water Global Rain Forest Mapping project SAR mosaics covering the entire Amazon basin. Validation results show that one-pixel (i.e., 92 m) positioning accuracy (root mean square error) was achieved in both cases, compared to 14-16 pixel errors (i.e., 1288-1472 m) of the original mosaics.     

Estimation of bare surface soil moisture and surface roughnessparameter using L-band SAR image data

An algorithm based on a fit of the single-scattering integral equation method (IEM) was developed to provide estimation of soil moisture and surface roughness parameter (a combination of rms roughness height and surface power spectrum) from quad-polarized synthetic aperture radar (SAR) measurements. This algorithm was applied to a series of measurements acquired at L-band (1.25 GHz) from both AIRSAR (Airborne Synthetic Aperture Radar operated by the Jet Propulsion Laboratory) and SIR-C (Spaceborne Imaging Radar-C) over a well-managed watershed in southwest Oklahoma. Prior to its application for soil moisture inversion, a good agreement was found between the single-scattering IEM simulations and the L-band measurements of SIR-C and AIRSAR over a wide range of soil moisture and surface roughness conditions. The sensitivity of soil moisture variation to the co-polarized signals were then examined under the consideration of the calibration accuracy of various components of SAR measurements. It was found that the two co-polarized backscattering coefficients and their combinations would provide the best input to the algorithm for estimation of soil moisture and roughness parameter. Application of the inversion algorithm to the co-polarized measurements of both AIRSAR and SIR-C resulted in estimated values of soil moisture and roughness parameter for bare and short-vegetated fields that compared favorably with those sampled on the ground. The root-mean-square (rms) errors of the comparison were found to be 3.4% and 1.9 dB for soil moisture and surface roughness parameter, respectively     

Simultaneous in situ measurement of film thickness and temperatureby using multiple wavelengths pyrometric interferometry (MWPI)

Film thickness and temperature are two of the most important quantities in semiconductor manufacturing. They play a fundamental role in many standard production techniques like chemical vapor deposition (CVD, LPCVD, PECVD), thermal oxidation and diffusion. They are especially important for more recently developed technologies like molecular beam epitaxy (MBE), metal organic MBE (MOMBE), metal organic CVD (MOCVD), chemical beam epitaxy (CBE), etc. In this paper, an optical in situ method for simultaneous film thickness and temperature measurements-named multiple wavelengths pyrometric interferometry (MWPI)-is introduced, which is capable of high resolution (up to 0.1 nm for thickness and 0.025 K for temperature) and for real time data evaluation. It can be used for process control as well as in situ quality inspection without time delay or additional handling mechanisms and is suitable for monitoring single films as well as multilayer structures. MWPI is insensitive to vibration, rotation and misalignment of the wafer. Due to its optical basis it is also insensitive to hostile environments like high temperature and/or chemical reactive gases     

Estimating the effective number of looks in interferometric SAR data

The probability density function (pdf) of the multi-look interferometric phase between two complex synthetic aperture radar (SAR) images is parameterized by the number of looks and the complex correlation coefficient. In practice, adjacent pixels in a real SAR interferogram, are statistically dependent due to filtering, and hence, the number of looks is usually smaller than the number of samples averaged. It has been shown that compensation with an effective number of looks, rather than an intractable rederivation of the pdf, can account for the statistical dependence. This paper addresses the challenge of how to determine a suitable value for the effective number of looks. It is shown that an optimum value can be found via a maximum-likelihood estimator (MLE) based on the interferometric phase pdf. However, since such an MLE is computationally intensive and numerically unstable, an estimator based on the method of moments (MoM) possessing similar fidelity is proposed. MoM is fast and robust and can be used in operational applications, such as determining constant false alarm rate (CFAR) detection thresholds for moving-target detection in SAR along-track interferometry.     

Automatic detection and validity of the sea-ice edge: an application of enhanced-resolution QuikScat/SeaWinds data

Sea-ice edge detection is an essential task at the different national ice services to secure navigation in ice-covered seas. Comparison between the Remund and Long ice mask image from enhanced-resolution QuikScat/SeaWinds (QS) products and the analyzed ice edge from high-resolution RADARSAT synthetic aperture radar has shown that the automatically determined QS ice mask underestimates the Arctic ice extent. QS data was statistically analyzed by colocating the data with ice charts around Greenland and with the National Aeronautics and Space Administration Team's Special Sensor Microwave/Imager (SSM/I) ice concentration algorithm over the whole Arctic region. All variables, i.e., the backscatter in vertical and horizontal polarization, the active polarization ratio (APR) and the daily standard deviation, are sensitive to ice types and are strongly correlated with ice concentration when the relationship is expressed in exponential form. Our study showed that the APR is especially suitable for ice-ocean separation, and a threshold of -0.02 was determined. An ice edge algorithm based on this APR threshold was developed using the other variables with conservative season-dependent thresholds to eliminate additional ocean noise. Also, the history of the ice cover is considered in order to detect single ice fields that are separated from the main Arctic pack ice. Validation with RADARSAT 1 and with the Advanced Very High Resolution Radiometer showed that the new algorithm successfully detects very low ice concentrations of about 10% during the entire year. The validity of the detected ice edge for near-real-time issues is also discussed in relation to the ice motion in the Marginal Ice Zone and the integration time necessary to produce the enhanced-resolution images. The new algorithm improves the automatic global ice edge resolution by a factor of two when compared to SSM/I products and could be used in both model initialization and data assimilation.     

Effect of multiple scattering on the phase signature of wet subsurface structures: applications to polarimetric L- and C-band SAR

We propose a two-layer integral equation model (IEM) model including multiple-scattering terms to reproduce the phase signature of buried wet structures that we observed on L-band synthetic aperture radar (SAR) images. We have good agreement between the extended (single+multiple scattering) IEM model and previous results obtained using a single-scattering IEM model combined with finite-difference time-domain simulations. We show that the multiple scattering not only significantly influences the copolarized phase difference but can also be related to the soil moisture content. In order to assess the validity of our extended model, we performed radar measurements on a natural outdoor site and showed that they could be fairly well fitted to the extended model. A parametric analysis presents the dependence of the copolarized phase difference on roughness parameters (rms height and correlation length) and radar parameters (frequency and incidence angle). Our study also shows that the phase signature should allow detection of buried wet structures down to a larger depth for C-band (3.8 m) than for L-band (2.6 m). This signature could then be used to map subsurface moisture in arid regions using polarimetric SAR systems.     

利用大洋浮标数据和NCEP再分析资料对FY-2C红外分裂窗通道的绝对辐射定标

介绍利用大洋浮标数据和NCEP再分析资料对FY-2C红外分裂窗通道进行在轨绝对辐射定标的方法,并选择了2006年10个时次的卫星数据进行辐射定标试验.将利用这种方法获得的定标结果与FY-2C卫星数据产品中提供的定标查找表进行比较分析,结果表明两套不同的定标系数反演的大气层顶(TOA)亮度温度的主要差别集中在云顶、冰雪覆盖区域等低温像元;而在常温区的陆表和海表像元定标结果差别较小,反演的TOA亮温差在2K左右.提出的替代定标方法可以极大地提高定标频次,为实现FY-2C红外分裂窗通道的实时绝对辐射定标提供了重要的方法基础.     

远红外辐射器治疗带状疱疹的疗效分析

本文报道了远红外辐射器治疗带状疱疹５０例的疗效观察。采用对照研究的方法，结果证明，无论在皮疹的消退还是神经痛的缓解方面，治疗组都明显优于对照组，经统计学处理，两者间有非常显著的差别，证明远红外辐射治疗带状疱疹是有效的。     

Study of specific absorption rate (SAR) induced in two child head models and in adult heads using mobile phones

This paper gives a first comparison of specific absorption rate (SAR) induced in a child-sized (CS) head and an adult head using a dual-band mobile phone. In the second study, the visible human head is considered and comparison of SAR induced in a CS or child-like (CL) head and an adult head using a dual-band mobile phone is given. All the peaks of average SAR over a mass of 10 and 1 g in the head and the power budget are determined in the two comparisons using the finite-difference time-domain method. The differences between the results for adult and CS or CL heads are given at 900 and 1800 MHz. No important differences are noted for the peak SAR averaged over 10 g (SAR10 g), between the two adult head models, as well as between the two child head models. The peak SAR10 g in the brain of the CS or CL head is slightly more significant than that for the adult one.