Polarimetric microwave wind radiometer model function and retrieval testing for WindSat

A geophysical model function (GMF), relating the directional response of polarimetric brightness temperatures to ocean surface winds, is developed for the WindSat multifrequency polarimetric microwave radiometer. This GMF is derived from the WindSat data and tuned with the aircraft radiometer measurements for very high winds from the Hurricane Ocean Wind Experiment in 1997. The directional signals in the aircraft polarimetric radiometer data are corroborated by coincident Ku-band scatterometer measurements for wind speeds in the range of 20-35 m/s. We applied an iterative retrieval algorithm using the polarimetric brightness temperatures from 18-, 23-, and 37-GHz channels. We find that the root-mean-square direction difference between the Global Data Assimilation System winds and the closest WindSat wind ambiguity is less than 20/spl deg/ for above 7-m/s wind speed. The retrieval analysis supports the consistency of the Windrad05 GMF with the WindSat data.     

A nonlinear optimization algorithm for WindSat wind vector retrievals

WindSat is a space-based polarimetric microwave radiometer designed to demonstrate the capability to measure the ocean surface wind vector using a radiometer. We describe a nonlinear iterative algorithm for simultaneous retrieval of sea surface temperature, columnar water vapor, columnar cloud liquid water, and the ocean surface wind vector from WindSat measurements. The algorithm uses a physically based forward model function for the WindSat brightness temperatures. Empirical corrections to the physically based model are discussed. We present evaluations of initial retrieval performance using a six-month dataset of WindSat measurements and collocated data from other satellites and a numerical weather model. We focus primarily on the application to wind vector retrievals.     

The WindSat spaceborne polarimetric microwave radiometer: sensor description and early orbit performance

The global ocean surface wind vector is a key parameter for short-term weather forecasting, the issuing of timely weather warnings, and the gathering of general climatological data. In addition, it affects a broad range of naval missions, including strategic ship movement and positioning, aircraft carrier operations, aircraft deployment, effective weapons use, underway replenishment, and littoral operations. WindSat is a satellite-based multifrequency polarimetric microwave radiometer developed by the Naval Research Laboratory for the U.S. Navy and the National Polar-orbiting Operational Environmental Satellite System Integrated Program Office. It is designed to demonstrate the capability of polarimetric microwave radiometry to measure the ocean surface wind vector from space. The sensor provides risk reduction for the development of the Conical Microwave Imager Sounder, which is planned to provide wind vector data operationally starting in 2010. WindSat is the primary payload on the Department of Defense Coriolis satellite, which was launched on January 6, 2003. It is in an 840-km circular sun-synchronous orbit. The WindSat payload is performing well and is currently undergoing rigorous calibration and validation to verify mission success.     

Deep-space calibration of the WindSat radiometer

The WindSat microwave polarimetric radiometer consists of 22 channels of polarized brightness temperatures operating at five frequencies: 6.8, 10.7, 18.7, 23.8, and 37.0 GHz. The 10.7-, 18.7-, and 37.0-GHz channels are fully polarimetric (vertical/horizontal, /spl plusmn/45/spl deg/ and left-hand and right-hand circularly polarized) to measure the four Stokes radiometric parameters. The principal objective of this Naval Research Laboratory experiment, which flys on the USAF Coriolis satellite, is to provide the proof of concept of the first passive measurement of ocean surface wind vector from space. This paper presents details of the on-orbit absolute radiometric calibration procedure, which was performed during of a series of satellite pitch maneuvers. During these special tests, the satellite pitch was slowly ramped to +45/spl deg/ (and -45/spl deg/), which caused the WindSat conical spinning antenna to view deep space during the forward (or aft portion) of the azimuth scan. When viewing the homogeneous and isotropic brightness of space (2.73 K) through both the main reflector and the cold-load calibration reflector, it is possible to determine the absolute calibration of the individual channels and the relative calibration bias between polarimetric channels. Results demonstrate consistent and stable channel calibrations (with very small brightness biases) that exceed the mission radiometric calibration requirements.     

微波辐射计反演海表面温度和风场研究进展

海表面温度（SST）和海面风场是重要的海面气象水文参数,与海面的大部分物理过程关系密切。卫星遥感探测技术可以同时获得全球范围内的海表面温度和海面风场数据。其中,微波辐射计遥感海表面温度和风场具有不受云层遮挡的优势,本文就其发展过程作简要介绍。     

全极化微波辐射计数字相关器下变频算法设计

全极化微波辐射计是一种用于海洋表面风场测量的新型被动微波遥感器,数字相关器是全极化辐射计的核心部件。针对全极化微波辐射计接受到的数字信号采样率较高的问题,提出应用多相滤波的算法以降低数字信号速率,从而满足FPGA时序约束的要求。之后为进一步节省乘法器资源和提高处理速率,滤波部分采用分布式算法,两种方法结合完成下变频模块处理,通过Matlab软件对下变频算法进行了仿真。仿真结果表明算法是可行的。     

Evaluation of WindSat wind vector performance with respect to QuikSCAT estimates

The WindSat instrument was launched on January 6, 2003 as part of a risk reduction effort to assess the potential of using spaceborne fully polarimetric radiometry to measure the marine wind vector. Microwave radiometry on the Special Sensor Microwave/Imager onboard the Defense Meteorological Satellite Program satellites has long provided wind speed measurements. Fully polarimetric radiometry offers the additional possibility of obtaining wind direction as well. By contrast, the QuikSCAT satellite uses active microwave measurements to estimate the wind vector from space. It represents the most comprehensive satellite dataset against which to compare WindSat measurements. In this paper, we systematically compare temporally and spatially coincident WindSat and QuikSCAT wind vector measurements against the design goals of the WindSat instrument, taking into consideration expected differences related to instrument precision and the spatial and temporal variability of the wind field.     

Fully polarimetric microwave radiometer for remote sensing

The design, characteristics, and operation of the Helsinki University of Technology Fully Polarimetric Radiometer (FPoR) are described. The developed 36.5-GHz radiometer can be used for airborne remote sensing; however, ground-based and laboratory measurements are also possible. A direct cross-correlation technique with analog correlators, which measures all four Stokes parameters simultaneously, is applied. This paper is the first successful demonstration of an analog direct cross-correlation technique for polarimetric remote sensing radiometry. The radiometer was subjected to a variety of laboratory tests, and considerable attention is given to analysis of the characteristics of the instrument. Owing to the effective active temperature control system of the receiver, the radiometric stability of the instrument was found to be very high; test results showing stabilities below 10 mK and of 4-40 mK on time scales of 800 and 8000 s, respectively, are presented. Furthermore, the absolute accuracy of the system is analyzed to be at a sub-Kelvin level for most measurement conditions. A maritime wind vector experiment was carried out over the Gulf of Finland. The feasibility and performance of the applied correlation technique and the whole radiometer system were verified for fully polarimetric airborne measurements. The obtained brightness temperatures of the first three Stokes parameters show typical harmonic behavior with respect to the surface wind; the results suggest, however, that the model coefficients presented earlier for oceans may not be directly applicable for different conditions.     

Soil moisture retrieval using the C-band polarimetric scanning radiometer during the Southern Great Plains 1999 Experiment

The Advanced Microwave Scanning Radiometer (AMSR) holds promise for retrieving soil moisture in regions with low levels of vegetation. Algorithms for this purpose have been proposed, but none have been rigorously evaluated due to a lack of datasets. Accordingly, the Southern Great Plains 1999 Experiment (SGP99) was designed to provide C-band datasets for AMSR algorithm development and validation. Ground observations of soil moisture and related variables were collected in conjunction with aircraft measurements using a C-band radiometer similar to the AMSR sensor (6.92 GHz), the Polarimetric Scanning Radiometer with its C-band scanhead (PSR/C). The study region has been the focus of several previous remote sensing field experiments and contains vegetation conditions compatible with the expected capabilities of C-band for soil moisture retrieval. Flights were conducted under a wide range of soil moisture conditions, thus providing a robust dataset for validation. A significant issue found in data processing was the removal of anthropogenic radio-frequency interference. Several approaches to estimating the parameters of a single-channel soil moisture retrieval algorithm were used. PSR/C soil moisture images show spatial and temporal patterns consistent with meteorological and soil conditions, and the dynamic range of the PSR/C observations indicates that the AMSR instrument can provide useful soil moisture information.     

High-resolution passive polarimetric microwave mapping of oceansurface wind vector fields

The retrieval of ocean surface wind fields in both one and two dimensions is demonstrated using passive polarimetric microwave imagery obtained from a conical-scanning airborne polarimeter. The retrieval method is based on an empirical geophysical model function (GMF) for ocean surface thermal emission and an adaptive maximum likelihood (ML) wind vector estimator. Data for the GMF were obtained using the polarimetric scanning radiometer/digital (PSR/D) on the NASA P-3 aircraft during the Labrador Sea Deep Convection Experiment in 1997. To develop the GMF, a number of buoy overflights and GPS dropsondes were used, out of which a GMF of 10.7, 18.7, and 37.0 GHz azimuthal harmonics for the first three Stokes parameters was constructed for the SSM/I incident angle of 53.1°. The data show repeatable azimuthal harmonic coefficient amplitudes of ~2-3 K peak-to-peak, with a 100% increase in harmonic amplitudes as the frequency is increased from 10.7 to 37 GHz. The GMF is consistent with and extends the results of two independent studies of SSM/I data and also provides a model for the third Stokes parameter over wind speeds up to 20 m/s. The aircraft data show that the polarimetric channels are much less susceptible to geophysical noise associated with maritime convection than the first two Stokes parameters. The polarimetric measurement technique used in the PSR/D also demonstrates the viability of digital correlation radiometry for aircraft or satellite measurements of the full Stokes vector. The ML retrieval algorithm incorporates the additional information on wind direction available from multiple looks and polarimetric channels in a straightforward manner and accommodates the reduced SNRs of the first two Stokes parameters in the presence of convection by weighting these channels by their inverse SNR     

The accuracy of preliminary WindSat vector wind measurements: comparisons with NDBC buoys and QuikSCAT

Two preliminary, six-month long global WindSat vector wind datasets are validated using buoys and QuikSCAT measurements. Buoy comparisons yield speed and direction root mean square accuracies of 1.4 m/s and 25/spl deg/ for the "NESDIS0" product and 1.3 m/s and 23/spl deg/ for the more recently produced "B1" product from the Naval Research Laboratory. WindSat along- and across-wind random component errors of 0.7-1.0 and 2.6-2.8 m/s (respectively) are larger than those calculated for QuikSCAT in the same period. Global WindSat-QuikSCAT comparisons generally confirmed the buoy analyses. While simple rain flags based directly on WindSat brightness temperature measurements alone are shown to overflag for rain systematically, the advanced "Environmental Data Record" rain flag in the B1 product matches well with Special Sensor Microwave/Imager rain detection frequency and preserves the accuracy of the unflagged vector wind measurements.     

A new wind vector algorithm for C-band SAR

Ocean wind speed and wind direction are estimated simultaneously using the normalized radar cross sections /spl sigma//sup 0/ corresponding to two neighboring (25-km) blocks, within a given synthetic aperture radar (SAR) image, having slightly different incidence angles. This method is motivated by the methodology used for scatterometer data. The wind direction ambiguity is removed by using the direction closest to that given by a buoy or some other source of information. We demonstrate this method with 11 ENVISAT Advanced SAR sensor images of the Gulf of Mexico and coastal waters of the North Atlantic. Estimated wind vectors are compared with wind measurements from buoys and scatterometer data. We show that this method can surpass other methods in some cases, even those with insufficient visible wind-induced streaks in the SAR images, to extract wind vectors.     

融合矢量量化与LBP的图像检索算法

基于内容的图像检索算法一直是图像领域研究的热门课题,因此提出一种新的融合矢量量化与LBP的图像检索算法。首先,将彩色图像转化到HSI颜色空间,进行矢量量化编码,统计图像码字出现的频数,形成颜色直方图,完成颜色特征的提取;然后,再将彩色图像转化成灰度图像,利用局部二进制模式(LBP)算法提取纹理特征;最后,相似度计算采用颜色特征和纹理特征相似度加权平均,并且改变颜色特征和纹理特征的权值,多次实验,得到使查准率最高的权值。实验结果表明,算法能有效地提升图像检索性能。     

相干测风激光雷达中多核DSP并行风速反演算法的实现

针对高重复频率相干测风激光雷达中风速反演时数据量大、计算量大、实时性要求高等问题提出了基于多核数字信号处理器（DSP）的并行风速反演算法。该算法的核心思想是,利用高速数据处理板卡DSPC-8681上的4颗8核DSP处理器采用单指令多数据流的方式进行并行计算和同步,使用最大似然离散谱峰值计算出视向风速。在激光脉冲重复频率为10 kHz的条件下实现了相干测风激光雷达中实时的风速反演。通过实验验证,激光雷达的视向探测距离达到3 600 m,距离分辨率为60 m,风速测量范围为30 m/s,时间分辨率为1 s,转动圆盘校准的速度测量精度优于0.48 m/s。     

ERS-1 scatterometer measurements. II. An algorithm forocean-surface wind retrieval including light winds

For pt.I see ibid., vol.36, no.2, p.603-22 (1998). An algorithm for retrieving European Remote Sensing Satellite (ERS-1) scatterometer winds, denoted the Rufenach-Bates-Tosini (RBT) algorithm, is developed and used to retrieve winds collocated within ±25 km of buoy measurements in two oceanic regions, equatorial and midlatitude. An improvement in the retrieved RBT winds over the European Space Agency (ESA) winds is due mainly to a geophysical model employing the full available wind-speed range, including the lightest winds. This model, denoted BMOD5, is tuned by using the scatterometer and buoy measurements, resulting in two different models for the midlatitude and equatorial regions. The RBT retrieved winds exhibit (1) a larger number of solutions (wind vectors) and (2) smaller biases in wind speed than the ESA wind product. The increase in the number of retrieved winds is primarily due to lighter winds employed, 0.2 m/s to 18 m/s; whereas, the ESA winds are truncated near 3 m/s. The ESA winds underestimate the highest winds significantly, by about 20%, and overestimate the lightest winds. The RBT wind bias is less than a few percent at the highest winds and a few tenths of a m/s at the lowest winds. Both algorithms retrieve 180° ambiguous directions almost as often as the true direction. Regression fits to the winds using the RBT algorithm produce standard deviations of 1 m/s and 25° near the equator for winds varying from 0.2-10 m/s and 1.2 m/s and 250 at midlatitudes for winds varying from 0.2-18 m/s, provided that the ambiguities are removed     

An algorithm for uniform vector quantizer design

A vector quantizer maps ak-dimensional vector into one of a finite set of output vectors or "points". Although certain lattices have been shown to have desirable properties for vector quantization applications, there are as yet no algorithms available in the quantization literature for building quantizers based on these lattices. An algorithm for designing vector quantizers based on the root latticesA_{n}, D_{n}, andE_{n}and their duals is presented. Also, a coding scheme that has general applicability to all vector quantizers is presented. A four-dimensional uniform vector quantizer is used to encode Laplacian and gamma-distributed sources at entropy rates of one and two bits/sample and is demonstrated to achieve performance that compares favorably with the rate distortion bound and other scalar and vector quantizers. Finally, an application using uniform four- and eight-dimensional vector quantizers for encoding the discrete cosine transform coefficients of an image at0.5bit/pel is presented, which visibly illustrates the performance advantage of vector quantization over scalar quantization.     

用微波辐射计测量大气积分水汽的改进算法

提出选择具有最佳频率组合的双通道微波辐射计,通过测量路径上的湿延迟来解算积分水汽含量的改进算法。由于在湿延迟测量模式中,消除了云中液态水对湿延迟测量的\     

一种改进的矢量量化码字搜索算法

该文利用图像矢量的平均值和方差,结合了最近邻域搜索算法,构造了一种新的快速矢量量化编码算法。将一个输入矢量分为两个子矢量,分别计算原始矢量、两个子矢量的和以及方差值,利用在这些数值基础上建立的一组三角不等式来排除不可能的码字。仿真结果表明新算法在所需时间和计算复杂度方面优于改进的EENNS算法,为矢量量化算法的研究提供了一种新的思路。     

An algorithm for determining the radiance reflected from the roughsea surface using MODIS-N satellite radiometer data

A new algorithm is suggested for determining the radiance B_r (&thetas;, φ) reflected from the rough sea surface. The knowledge of B_r(&thetas;, φ) is needed for excluding the reflected solar radiation from the signal at the space receiver. Information on the reflected radiance is also required when estimating the state of the sea surface from space. The information (on reflected radiance) is important for problems such as estimating the chlorophyll concentration in sea water. The suggested algorithm was constructed based on direct measurements of the radiance coefficient ρ published in V. G. Akimov ei al. (1993) and J. A Shaw et al. (1997). The experimental results show that the slope distribution of sea surface elements depends not only on the wind speed near the sea surface but also on the stability of the lower part of the marine atmospheric boundary layer. It is shown that the failure to account for this effect causes an error of ±30% when estimating B_r(&thetas;, φ)     

A polarimetric survey of radio-frequency interference in C- and X-bands in the continental united states using WindSat radiometry

Transmissions from ground-based systems in C- and X-bands present a significant challenge to the use of these bands for passive microwave remote sensing from aircraft and satellites. Because future missions plan to continue to use these frequencies, it is important to characterize and understand the nature of interference in as much of the candidate spectrum as possible. This paper presents a statistical analysis of interference observed in the continental U.S. using six months of data collected from the C- and X-band channels of the WindSat microwave radiometer. Our findings are consistent with those of previous studies by Li et al. and Njoku et al., which are based on data obtained from the Advanced Microwave Scanning Radiometer-EOS using somewhat similar center frequencies and bandwidths. Results show significant radio-frequency interference (RFI) at C-band, including brightnesses in horizontal and vertical polarizations in excess of 330 K, while X-band RFI is less obvious through direct examination of measured linearly polarized brightnesses. Evidence of lower levels of RFI is provided through use of the spectral and polarization indexes of Li et al., which reveal likely RFI contributions at X-band as well. Further confirmation of X-band RFI is obtained through analysis of the polarimetric channels, which are shown to provide direct evidence of RFI in contrast to the linearly polarized channels. A temporal analysis of the largest C-band RFI sources is also provided in an attempt to further understand their properties.