基于亮度温度模型的多光谱真温反演算法研究

针对传统的非接触式真温反演算法存在反演速度慢和精度低等问题,提出新的基于亮度温度模型的约束真温反演算法(constrained true temperature inversion algorithm,CTTIA)。 在建模过程中,发现发射率和亮度温度存在内在联系:由亮度温度到发射率的普适规律和由发射率到亮度温度的普适规律。通过仿真实验发现当发射率的样本数量巨大时,CTTIA不但可以为实验提供理论指导,还可大大提升发射率样本的选取效率。在1 800 ℃和2 000 ℃两个温度点下建立9个波长通道对被测目标进行测量计算。结果表明,CTTIA与二次测量算法 (second measurement method,SMM) 相比,精度基本相同,反演时间最高节约了82%。说明该方法的研究是非常关键且重要的,是很有研究价值的。     

Tissue cooling and its effect on brightness temperatures by contact-type microwave applicators

Contact of an applicator on the skin surface may cool the tissues so that the resulting brightness temperature measured by the applicator is varied. The tissue cooling effect on the brightness temperature was quantitatively evaluated. From the experimental results, it was concluded that an accurate temperature control was needed in order to reduce the errors in the brightness temperature. A new method of temperature control which permits continuous measurement of the thermal responses of a human body was attempted, and advantages and disadvantages of the method are discussed. The research results may be practical and useful for the accurate measurement of brightness temperature.     

Spatial resolution enhancement of terrestrial features usingdeconvolved SSM/I microwave brightness temperatures

A method for enhancing the 19-, 22-, and 37-GHz measurements of the SSM/I (Special Sensor Microwave/Imager) to the spatial resolution and sampling density of the high-resolution 85-GHz channel is presented. An objective technique for specifying the tuning parameter, which balances the tradeoff between resolution and noise, is developed in terms of maximizing cross-channel correlations. Various validation procedures are performed to demonstrate the effectiveness of the method, which, it is hoped, will provide researchers with a valuable tool in multispectral applications of satellite radiometer data     

The influence of clouds on microwave brightness temperatures viewing downward over open seas

Microwave brightness temperatures for the case of downward viewing from above the earth's atmosphere over water for the 1- to 2-cm wavelength range are calculated for comparison with observations. A model of the troposphere which contains homogeneous layer clouds of varied thickness and liquid water content is used to compute estimates of the influence which clouds would have on real observations. It is assumed that only pure absorption is important for the cloud droplet-size distributions and droplet densities used. Results of the computations indicate that most water clouds will contribute a measurable amount to the microwave emission of the atmosphere and, in some cases, can be the principal source of received radiation. Comparisons of the computed cases with measurements obtained with a high flying aircraft are shown to be in reasonable agreement. These results are significant because they demonstrate that water clouds cannot be neglected in the application of passive microwave techniques to remote probing of the earth's atmosphere and because they indicate that quantitative measures of cloud liquid water contents and cloud thickness might be acquired through multi-frequency measurements.     

Sensitivity, spatial heterogeneity, and scaling of C-band microwave brightness temperatures for land hydrology studies

Soil moisture is one of the most important hydrological variables that characterizes the land surface water and energy balance. Measurements from space suffer from the problem of subpixel heterogeneity, i.e., soil moisture has spatial variability at all scales; therefore, it is important to realize the exact physical implication of the single value of the satellite measurements. In this paper, we study the sensitivity of C-band passive microwave brightness temperatures to various land surface variables. The issue of heterogeneity and its role in interpretation of single spatially averaged value of satellite brightness temperature is investigated. Finally, we use the brightness temperatures from the Scanning Multichannel Microwave Radiometer to characterize spatial variability and to understand the variation of this variability with scale.     

Retrieval of land and sea brightness temperatures from mixedcoastal pixels in passive microwave data

A technique is presented to separate uncontaminated land and sea brightness temperatures from mixed coastal pixels in 37-GHz vertically polarized passive microwave data from the Special Sensor Microwave Imager (SSM/I) instrument. Combining a mathematical model of the instrument response over several neighboring footprints with a GIS representation of the coastline yields a relationship between land and sea brightness temperatures and radiation measurements made at the satellite. Inverting this relationship allows separate land and sea brightness temperature values to be derived for each mixed coastal pixel in the original image. The technique has been successfully applied to 37-GHz vertically polarized SSM/I imagery for test areas covering the Gulf of Aden and the British Isles. Errors in the retrieved brightness temperatures were estimated to be of the order of 1-2 K     

The beamfilling algorithm for retrieval of hydrometeor profileparameters from passive microwave measurements

The horizontal inhomogeneity of the atmosphere within a satellite microwave radiometer's field of view (FOV) has always been considered as a source of rainfall retrieval errors. The hydrometeor profile retrieval algorithm presented exploits it to obtain an approximation of a radiative transfer model, which allows relatively simple inversion. The atmosphere within the FOV is treated as a combination of horizontally homogeneous domains. Assuming that one of known “basic” hydrometeor profiles occurs in each domain, the inverse problem is reduced to a determination of “beamfilling coefficients.” The online procedure includes determination of beamfilling coefficients and a footprint-averaged hydrometeor profile as a linear combination of “basic” ones. Off-line procedures involve the selection of a minimum number of necessary “basic” brightness temperature vectors and correction of “basic” hydrometeor profiles to provide the best retrieval accuracy for a given cloud/radiative simulation. The performance of the algorithm is tested for both numerical simulations and TRMM/TMI data. Numerical simulation has allowed a comparison of the information content of radiometer measurements from SSM/I, TMI, and the future AMSR. The effectiveness of the algorithm is being tested for rain water integral and rain rate retrievals from TRMM TMI measurements     

An updated analysis of the ocean surface wind direction signal in passive microwave brightness temperatures

We analyze the wind direction signal for vertically (v) and horizontally (h) polarized microwave radiation at 37 GHz, 19 GHz, and 11 GHz; and an Earth incidence angle of 53/spl deg/. We use brightness temperatures from SSM/I and TMI and wind vectors from buoys and the QUIKSCAT scatterometer. The wind vectors are space and time collocated with the radiometer measurements. Water vapor, cloud water and sea surface temperature are obtained from independent measurements and are uncorrelated with the wind direction. We find a wind direction signal that is noticeably smaller at low and moderate wind speeds than a previous analysis had indicated. We attribute the discrepancy to errors in the atmospheric parameters that were present in the data set of the earlier study. We show that the polarization combination 2v-h is almost insensitive to atmospheric changes and agrees with the earlier results. The strength of our new signals agrees well with JPL aircraft radiometer measurements. It is significantly smaller than the prediction of the two-scale sea surface emission model for low and intermediate wind speeds.     

Visibility of local thermal structures and temperature retrieval by microwave radiometry

For the first time, the geometrical characteristics (depth and size) and the temperature of a local thermal volume located in a homogeneous lossy material can be deduced from radiometric data. An example devoted to physical models (the lossy material is water) is based on the processing of radiometric data at 1.5 and 3 GHz.     

Impact of horizontal and vertical heterogeneities on retrievals using multiangle microwave brightness temperature data

This paper investigates the impact of heterogeneity at the land surface on geophysical parameters retrieved from multiangle microwave brightness temperature data, such as would be obtained from the Soil Moisture and Ocean Salinity (SMOS) mission. Synthetic brightness temperature data were created using the Common Land (land surface) Model, coupled with a microwave emission model and set within the framework of the North American Land Data Assimilation System (NLDAS). Soil moisture, vegetation optical depth, and effective physical temperature were retrieved using a multiobjective calibration routine similar to the proposed SMOS retrieval algorithm for a typical on-axis range of look angles. The impact of heterogeneity both in the near-surface profiles of soil moisture and temperature and in the land cover on the accuracy of the retrievals was examined. There are significant errors in the retrieved parameters over regions with steep gradients in the near-surface soil moisture profile. These errors are approximately proportional to the difference in the soil water content between the top (at 0.7 cm) and second layer (at 2.7 cm) of the land surface model. The errors resulting from heterogeneity in the land cover are smaller and increase nonlinearly with increasing land-surface heterogeneity (represented by the standard deviation of the optical depth within the pixel). The most likely use of retrieved soil moisture is through assimilation into an LDAS for improved initiation of weather and climate models. Given that information on the soil moisture profile is already available within the LDAS, the error in the retrieved soil moisture as a result of the near-surface profile can be corrected for. The potential errors as a result of land-surface heterogeneity can also be assessed for use in the assimilation process.     

弱信号亮温光谱的污染气体快速识别算法

基于被动傅里叶变换红外光谱仪设计开发了一种新的快速气体识别算法, 利用改进的动量梯度下降法对实测 的亮温光谱进行快速的光谱拟合。该方法不需要预先测得背景光谱, 能直接从实测光谱中扣除大气气体和天空等背 景的干扰, 在提取出污染气体成分以及浓度的同时, 能实时得到大气中主要气体的浓度程长积, 此方法适用于低空背 景下弱信号的污染气体识别分析。     

The magnetic field dependency of brightness temperatures atfrequencies near the O2 microwave absorption lines

The dependence of microwave brightness temperatures on the Earth's magnetic field at frequencies within a few megahertz of the O₂ absorption line centers is examined in detail. The azimuthal angular dependence is shown to factor from the radiative transfer equation while the dependence on the angle between the propagation direction and the Earth's field direction is described by a linear or quadratic polynomial in the square of the cosine of this angle in some typical cases of potential interest for a mesospheric sounder. Dependences of the brightness temperature matrix on the magnitude of the Earth's field are derived and shown to be different according to whether linear or circular polarization is used     

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。     

One-dimensional variational retrieval algorithm of temperature, water vapor, and cloud water profiles from advanced microwave sounding unit (AMSU)

The measurements from satellite microwave imaging and sounding channels are simultaneously utilized through a one-dimensional (1-D) variation method (1D-var) to retrieve the profiles of atmospheric temperature, water vapor and cloud water. Since the radiative transfer model in this 1D-var procedure includes scattering and emission from the earth's atmosphere, the retrieval can perform well under all weather conditions. The iterative procedure is optimized to minimize computational demands and to achieve better accuracy. At first, the profiles of temperature, water vapor, and cloud liquid water are derived using only the AMSU-A measurements at frequencies less than 60 GHz. The second step is to retrieve rain and ice water using the AMSU-B measurements at 89 and 150 GHz. Finally, all AMSU-A/B sounding channels at 50-60 and 183 GHz are utilized to further refine the profiles of temperature and water vapor while the profiles of cloud, rain, and ice water contents are constrained to those previously derived. It is shown that the radiative transfer model including multiple scattering from clouds and precipitation can significantly improve the accuracy for retrieving temperature, moisture and cloud water. In hurricane conditions, an emission-based radiative transfer model tends to produce unrealistic temperature anomalies throughout the atmosphere. With a scattering-based radiative transfer model, the derived temperature profiles agree well with those observed from aircraft dropsondes.     

用HJ-1B卫星数据反演地表温度的修正单通道算法

目前用于地表温度反演的单通道算法主要针对窄视场传感器建立.HJ-1B卫星红外相机为宽视场传感器,其热红外通道(IRS4)观测天顶角可达±33°以上,在地表温度反演时必须剔除传感器观测角度的影响.以大气辐射传输模拟为基础,建立了基于传感器观测天顶角-大气函数系数的修正单通道算法.针对HJ-1B卫星与Terra卫星过境时间...     

一种改善LED显示屏亮度均匀性的算法

基于显示屏控制技术与校正原理,提出了一种改善LED显示屏亮度均匀性的算法.通过CCD相机采集显示屏RGB图像,用数学形态学和模板匹配法确定灯点的位置并根据发光区域的灰度值计算其相对亮度,生成每个灯点的校正参数,用脉冲宽度调制控制灯点的亮度.实验结果表明提出的算法能有效改善显示屏的亮度均匀性,提高显示屏的显示质量并延长其使用寿命.     

TOPEX/Poseidon Microwave Radiometer (TMR). II. Antenna patterncorrection and brightness temperature algorithm

For pt.I see ibid., vol.33, no.1, p.125-37 (1995). The calibrated antenna temperatures measured by the TOPEX Microwave Radiometer are used to derive radiometric brightness temperatures in the vicinity of the altimeter footprint. The basis for the procedure devised to do this-the antenna pattern correction and brightness temperature algorithm-is described in the paper, along with its associated uncertainties. The algorithm is based on knowledge of the antenna pattern, the ground-based measurements of which are presented along with their analyses. Using the results of these measurements, the authors perform an error analysis that yields the net uncertainties in the derived TMR footprint brightness temperatures. The net brightness temperature uncertainties range from 0.79 to 0.88 K for the three TMR frequencies, and include the radiometer calibration uncertainties which range from 0.54 to 0.57 K. the authors also derive an estimate of the uncertainty incurred by using brightness temperatures measured in the ~40 km TMR footprint to estimate path delay in the ~3 km altimeter footprint. The RMS difference in path delay averaged over the largest TMR footprint relative to that in the altimeter footprint is estimated to be about 0.3 cm. Finally, the authors discuss the error associated with using unequal beams at the three TMR frequencies to derive path delays, and describe an approach using along-track averaging of the algorithm brightness temperatures to reduce this error     

Retrieving soil moisture from simulated brightness temperatures bya neural network

The authors present the retrievals of surface soil moisture (SM) from simulated brightness temperatures by a newly developed error propagation learning backpropagation (EPLBP) neural network. The frequencies of interest include 6.9 and 10.7 GHz of the advanced microwave scanning radiometer (AMSR) and 1.4 GHz (L-band) of the soil moisture and ocean salinity (SMOS) sensor. The land surface process/radiobrightness (LSP/R) model is used to provide time series of both SM and brightness temperatures at 6.9 and 10.7 GHz for AMSRs viewing angle of 55°, and at L-band for SMOS's multiple viewing angles of 0°, 10°, 20°, 30°, 40°, and 50° for prairie grassland with a column density of 3.7 km/m². These multiple frequencies and viewing angles allow the authors to design a variety of observation modes to examine their sensitivity to SM. For example, L-band brightness temperature at any single look angle is regarded as an L-band one-dimensional (1D) observation mode. Meanwhile, it can be combined with either the observation at the other angles to become an L-band two-dimensional (2D) or a multiple dimensional observation mode, or with the observation at 6.9 or 10.7 GHz to become a multiple frequency/dimensional observation mode. In this paper, it is shown that the sensitivity of radiobrightness at AMSR channels to SM is increased by incorporating L-band radiobrightness. In addition, the advantage of an L-band 2D or a multiple dimensional observation mode over an L-band 1D observation mode is demonstrated     

A new algorithm for temperature and spectral emissivity retrieval over active fires in the TIR spectral range

The problem of temperature and spectral emissivity assessment from hyperspectral remotely sensed data is discussed with reference to monitoring of active fires and hot targets. A new algorithm, called similar pixel addition, was developed, which allows us to retrieve the temperature of burning areas by employing spectral data collected at thermal infrared (TIR) wavelengths. The new algorithm resolves the uncertainty connected with temperature-emissivity separation assuming a slow spatial variation of emissivity, hence reducing the number of unknowns involved in the inversion of a couple of similar pixels at once. Performance of this procedure is thoroughly discussed and compared with results from two other algorithms operating in the TIR and shortwave infrared spectral ranges. This paper shows results obtained applying the new algorithm to hyperspectral images gathered by the Multispectral Infrared and Visible Imaging Spectrometer in Northern Italy (Alps) over a natural fire that broke out in July 1999. This paper is completed with a theoretical discussion of the involved topics.     

LSA based multi-instance learning algorithm for image retrieval

Focusing on the problem of natural image retrieval, based on latent semantic analysis (LSA) and support vector machine (SVM), a novel multi-instance learning (MIL) algorithm is proposed, where a bag corresponds to an image and an instance corresponds to the low-level visual features of a segmented region. Firstly, in order to transform every bag into a single sample, a collection of “visual-word” is generated by k-means clustering method to construct a projection space, then a nonlinear mapping is defined using these “visual-word” to embed each bag as a point in the projection space, thereby obtaining every bag's projection feature. Secondly, the matrix consisted of all the projection features of training bags is regarded as a term-document matrix, and LSA method is used to obtain the latent semantic feature of each bag. As a result, the MIL problem is converted into a standard single instance learning (SIL) problem that can be solved directly by SVM method. Experimental results on the COREL data sets show that the proposed method, named LSASVM-MIL, is robust, and its performance is superior to other key existing MIL algorithms.