MODIS EVI时间序列数据和光谱角聚类的冬小麦遥感估产分区方法研究

农作物遥感估产区划是农作物遥感估产的基础,它为估产研究和实践提供了重要的科学依据。以冬小麦生育期内的MODIS EVI时间序列作为分区数据,选择江苏省为试验区,探讨了一种改进的光谱角制图和K均值聚类相结合(光谱角聚类)的分区方法,并在冬小麦遥感估产中进行了试验。结果表明：光谱角聚类分区方法充分利用了MODIS时间序列数据所反映的农作物生长进程,可以充分体现气候差异所带来的冬小麦区域差异;与传统分区相比,基于光谱角聚类分区方法所得到的遥感估产结果具有较高的决定系数R2(0.702 6比0.624 8)和较低的均方根误差RMSE(343.34比381.34 kg·hm-2),体现了该分区方法在冬小麦遥感估产中的优势。光谱角聚类分区方法仅以获取便利的低分辨率时间序列遥感数据为分区数据,且能很好的将冬小麦划分为特征性质一致的区域,所得遥感估产模型的精度和稳定性也较好,为冬小麦遥感估产分区提供了一种有效方法,有利于进行冬小麦遥感估产研究。     

Blind estimation of shallow water acoustic channel

This paper proposed a method for blind estimation of underwater channels in shallow water environment by using received data at a single hydrophone or from single beam. First,the received signal is used for source signal reconstruction by means of signal-dependent TF(Time-Frequency)distribution,in association with instantaneous frequency estimation and TF inversion.Then the shallow-water channel estimation is achieved via WRELAX technique by use of the received signal and the estimated source signal.Finally,the results of numerical simulation and experimental test from real data taken in South China Sea trial have proved satisfactory.It is shown that the proposed method is useful for underwater channel estimation.     

Crack level estimation approach for planetary gearbox based on simulation signal and GRA

The planetary gearbox is a critical mechanism in helicopter transmission systems. A crack level estimation methodology for planetary gearbox has been devised by integrating a physical model for simulation signal generation, a statistic algorithm for feature selection and a grey relational analysis (GRA) algorithm for damage level estimation. The physical model is used to generate simulation datasets for developing and evaluating the diagnostic scheme that will be further calibrated with real world test data during application. The proposed method was calibrated with historical test data and then validated with real-time test data. The estimation results coincide with the actual test records, showing the effectiveness and accuracy of this method in providing a novel way for more accurate health monitoring and condition prediction.     

GPU based parallel framework for receiver coil sensitivity estimation in SENSE reconstruction

Magnetic Resonance Imaging (MRI) uses non-ionizing radiations and is safer as compared to CT and X-ray imaging. MRI is broadly used around the globe for medical diagnostics. One main limitation of MRI is its long data acquisition time. Parallel MRI (pMRI) was introduced in late 1990's to reduce the MRI data acquisition time. In pMRI, data is acquired by under-sampling the Phase Encoding (PE) steps which introduces aliasing artefacts in the MR images. SENSitivity Encoding (SENSE) is a pMRI based method that reconstructs fully sampled MR image from the acquired under-sampled data using the sensitivity information of receiver coils. In SENSE, precise estimation of the receiver coil sensitivity maps is vital to obtain good quality images. Eigen-value method (a recently proposed method in literature for the estimation of receiver coil sensitivity information) does not require a pre-scan image unlike other conventional methods of sensitivity estimation. However, Eigen-value method is computationally intensive and takes a significant amount of time to estimate the receiver coil sensitivity maps. This work proposes a parallel framework for Eigen-value method of receiver coil sensitivity estimation that exploits its inherent parallelism using Graphics Processing Units (GPUs). We evaluated the performance of the proposed algorithm on in-vivo and simulated MRI datasets (i.e. human head and simulated phantom datasets) with Peak Signal-to-Noise Ratio (PSNR) and Artefact Power (AP) as evaluation metrics. The results show that the proposed GPU implementation reduces the execution time of Eigen-value method of receiver coil sensitivity estimation (providing up to 30 times speed up in our experiments) without degrading the quality of the reconstructed image.     

Sub-pixel fire detection using Landsat-TM thermal data

Landsat-TM data has limitations in measuring high temperature fire zones. The thermal data saturate for temperatures above 68 °C and intense fires occupying less than a pixel requires modification of the methodology. The present paper describes the utility of Landsat-TM thermal data for estimation of surface temperature of sub-pixel fire. The method requires knowledge of the fire area. The temperature estimation from the method is found to be in good agreement with ground observations.     

Methods of estimation of equilibrium charge distribution of ions in solid and gaseous media

The new version of theoretical estimation of equilibrium charge distribution of ions passing through the matter is proposed. This estimation is based on the correction of charge exchange cross sections for gases taking into account the density effect. The results of calculations are compared with experimental data and with empirical estimation based on the averaging of experimental data for charge distributions of ions in gases and solids. The theoretical method describes the experimental oscillations of width of the charge distribution in contrast to the empirical method.     

波束形成与独立分量分析融合的宽带高分辨方位估计方法

针对波束域高分辨方位估计存在方位估计偏差大等缺点,提出了将波束形成与独立分量分析融合的宽带高分辨方位估计方法:(1)阵元域数据转换到波束域后,对多波束数据利用基于二阶统计量的独立分量分析算法处理,(2)将波束域独立分量分析融合方法输出结果重构回阵元域信号,(3)对重构后的阵元域数据,使用约束最优化方法改进的MUSIC算法做高分辨方位估计。最后利用ICS (Interactre Circuts&System)声呐模拟器数据和海试数据对算法进行了验证。结果表明:本文方法在弱目标检测、观测区域外强干扰抑制、方位分辨率方面都优先于波束域MUSIC和波束MVDR方法。      

压缩光场重建与深度估计

针对光场深度估计过程中数据量大、边缘处深度估计结果不准确问题,利用压缩感知原理重建光场,提出一种新的多信息融合的光场图像深度估计算法。利用压缩感知重建算法重建5×5视角光场数据,获取光场数据后首先移动子孔径实现重聚焦,然后利用角度像素块散焦线索和匹配线索计算出场景初始深度和置信度。计算图像边缘信息,通过融合初始深度、置信度、边缘信息获取最终深度。实现压缩光场仿真重建,并对仿真光场数据和公开光场数据进行深度估计,实验结果表明:可以仿真重建出5×5视角光场数据,且仿真重建的光场可用于深度估计。该深度估计算法在场景边缘处的深度估计结果边界清晰,层次分明,验证了重建光场深度估计的可行性与准确性。     

Spectral reflectance estimation for electronic endoscope

A method of spectral reflectance estimation for electronic endoscopes is described. A new approach is proposed for the overfitting problem. We use a small training set. Initially, cross-validation is used to select model parameters. Then, for additional validation of the method a color image acquired under the same illumination as the training data is used. This additional color image gives a clear solution for both the estimation of spectra and the estimation of color reproduced from these spectra. Experiments confirm that the method predicts spectral reflectance and colors well. Accurate reproduction of endoscope images in different viewing conditions and under another light source was implemented using this approach.     

A robust and accurate center-frequency estimation (RACE) algorithm for improving motion estimation performance of SinMod on tagged cardiac MR images without known tagging parameters

A robust and accurate center-frequency (CF) estimation (RACE) algorithm for improving the performance of the local sine-wave modeling (SinMod) method, which is a good motion estimation method for tagged cardiac magnetic resonance (MR) images, is proposed in this study. The RACE algorithm can automatically, effectively and efficiently produce a very appropriate CF estimate for the SinMod method, under the circumstance that the specified tagging parameters are unknown, on account of the following two key techniques: (1) the well-known mean-shift algorithm, which can provide accurate and rapid CF estimation; and (2) an original two-direction-combination strategy, which can further enhance the accuracy and robustness of CF estimation. Some other available CF estimation algorithms are brought out for comparison. Several validation approaches that can work on the real data without ground truths are specially designed. Experimental results on human body in vivo cardiac data demonstrate the significance of accurate CF estimation for SinMod, and validate the effectiveness of RACE in facilitating the motion estimation performance of SinMod.     

用于红移测量的基于密度估计的模板匹配法

文章给出了一种基于密度估计的模板匹配法来确定红移,将确定红移问题转化为寻找密度最大点问题。该方法首先利用基于均值漂移的谱线自动提取方法提取出特征谱线;再根据提取出的特征波长序列与模板的谱线表,由红移公式构造出一个数据集Z;最后,寻找数据集中的密度最大点,对密度最大点的ε-邻域中的点进行平均得到红移值。该方法利用了特征波长和谱线类型信息,可以处理各种类型的天体。在构造数据集时忽略谱线类型不匹配及特征波长明显不匹配的情况,这就去除了很大的干扰并且加快了运行速度。试验结果表明：该方法的稳定性较好,正确率也较高。     

Maximum a posteriori deconvolution of ultrasonic signals using multiple transducers

A new method for deconvolution of ultrasonic pulse-echo measurements employing multiple-transducer setup is proposed in the paper. An optimal way of estimating the material reflection sequence for a linear signal generation model using maximum a posteriori estimation is proposed. The method combines the measurements from a number of transducers covering different frequency bands yielding an optimal estimate of the reflection sequence. The main idea of this approach is to complement the information unavailable from one transducer in some frequency bands with the information from the other transducers. The method is based on the assumption that the measurements are performed using transducers with identical apertures and apodization, which are located exactly at the same position relative to the test object during the measurement. An error analysis presented in the paper proves that when the above assumptions are fulfilled, the proposed method, by utilizing more data for estimation, consistently yields more accurate reflection sequence estimates than the classical Wiener filter. Experimental evidence is presented using both simulated and real ultrasonic data as a verification of the correctness of the multiple-transducer model and the estimation scheme. An illustration of the advantages of the method is also given using real ultrasonic data.     

Experimental three dimensional strain estimation from ultrasonic sectorial data

Most of the studies devoted to elastography are focused on the estimation of the axial component of the strain. However when subjected to any load, whatever the direction, soft biological media deform in the three spatial dimensions. The aim of our work is to build a three dimensional strain mapping from data acquired with a 3D clinical sectorial probe. The estimation of radial strain is based on the estimation of local scaling factors. A method of cross-correlation of interpolated signals between adjacent radiofrequency lines was used to estimate the angular displacement and strain. For the sectorial strain estimation, the same displacement estimation technique has been implemented. The method has been tested on experimental data acquired on calibrated phantoms and compared to simulation.     

High-resolution azimuth estimation algorithm based on data fusion method for the vector hydrophone vertical array

To aim at the problem that the horizontal directivity index of the vector hydrophone vertical array is not higher than that of a vector hydrophone,the high-resolution azimuth estimation algorithm based on the data fusion method was presented.The proposed algorithm first employs MUSIC algorithm to estimate the azimuth of each divided sub-band signal,and then the estimated azimuths of multiple hydrophones are processed by using the data fusion technique.The high-resolution estimated result is achieved finally by adopting the weighted histogram statistics method.The results of the simulation and sea trials indicated that the proposed algorithm has better azimuth estimation performance than MUSIC algorithm of a single vector hydrophone and the data fusion technique based on the acoustic energy flux method.The better performance is reflected in the aspects of the estimation precision,the probability of correct estimation,the capability to distinguish multi-objects and the inhibition of the noise sub-bands.     

矢量水听器垂直阵列数据融合高分辨方位估计算法

为了实现矢量水听器垂直阵列对目标的高分辨方位估计,提出了基于MUSIC子频带最优加权数据融合方法。该方法采用MUSIC算法对划分的各窄带信号进行方位估计,并在各子频带对多基元方位估计结果进行最优加权最小二乘融合处理,最后通过加权直方图统计法得到最终方位估计结果。对算法进行的仿真及海上试验数据处理结果表明:本文算法在方位估计精度、方位估计正确概率、多目标分辨以及对噪声子频带的抑制能力方面都优于单个基元MUSIC以及多基元复声强器融合算法。      

Geoacoustic inversion in a dispersive waveguide using warping operators

This paper presents a single receiver geoacoustic inversion method adapted for low-frequency impulsive sources. It is applied to light bulb data collected during the Shallow Water 2006 experiment. The inversion is carried out by extracting dispersion curves from the received signal, and comparing them to simulated replicas. To achieve dispersion curve estimation in the time-frequency domain, modal separability is improved using a signal processing method called warping. The inversion scheme allows for a reliable estimation of the New Jersey Shelf sediment properties (compressional sound speed and density). It also provides an accurate estimation of the source/receiver range.     

The auto-measurement of the gap of LCD glass plates using sub-pixel accuracy estimation

In this paper, the distance between laser spots has been measured using sub-pixel accuracy estimation and the accuracy has been tested in a noise environment. Here, the correlation like method (CLM) is used for the distance measurement between two laser spots and to count the estimation precision effect under noise factor by relevant CLM theorems. From the maximum value of the data series, then the position of the center of laser spot can be derived by interpolation. The estimation precision effect under noise factor and DC offset are tested and analyzed by a computer system. Also, for improving the estimation precision, a Kalman filter, which is often applied for random estimation and control theorem, is adopted. The innovation research combines CLM, and Kalman filter in sub-pixel accuracy estimation is more precise. This method can be used for measuring the gap of LCD glass plates, of optical strain gauge and the characteristics of spectral, quickly and can be automated.     

用于单载波频域均衡水声通信的可分近似稀疏信道估计

针对单载波频域均衡水声通信中信道估计易受噪声干扰的问题,提出了一种低复杂度的信道估计方法。考虑水声信道的时域稀疏特性,导出频域输入、输出信号与信道冲激响应的关系式,并引入稀疏正则项,构造稀疏信道估计的目标函数。然后利用可分近似对目标函数进行迭代优化,再经过稀疏化与去偏处理,得到信道传递函数的最终估计。最后,利用数值仿真和海试数据对所提出方法的性能和运算效率进行评估。较之传统信道估计方法,所提出的方法在估计精度和计算复杂度方面具有一定的优势。      

Improved Dividend Estimation from Intraday Quotes

Liquid financial markets, such as the options market of the S&P 500 index, create vast amounts of data every day, i.e., so-called intraday data. However, this highly granular data is often reduced to single-time when used to estimate financial quantities. This under-utilization of the data may reduce the quality of the estimates. In this paper, we study the impacts on estimation quality when using intraday data to estimate dividends. The methodology is based on earlier linear regression (ordinary least squares) estimates, which have been adapted to intraday data. Further, the method is also generalized in two aspects. First, the dividends are expressed as present values of future dividends rather than dividend yields. Second, to account for heteroscedasticity, the estimation methodology was formulated as a weighted least squares, where the weights are determined from the market data. This method is compared with a traditional method on out-of-sample S&P 500 European options market data. The results show that estimations based on intraday data have, with statistical significance, a higher quality than the corresponding single-times estimates. Additionally, the two generalizations of the methodology are shown to improve the estimation quality further.     

A path integral method for data assimilation

Described here is a path integral, sampling-based approach for data assimilation, of sequential data and evolutionary models. Since it makes no assumptions on linearity in the dynamics, or on Gaussianity in the statistics, it permits consideration of very general estimation problems. The method can be used for such tasks as computing a smoother solution, parameter estimation, and data/model initialization.Speedup in the Monte Carlo sampling process is essential if the path integral method has any chance of being a viable estimator on moderately large problems. Here a variety of strategies are proposed and compared for their relative ability to improve the sampling efficiency of the resulting estimator. Provided as well are details useful for its implementation and testing.The method is applied to a problem in which standard methods are known to fail, an idealized flow/drifter problem, which has been used as a testbed for assimilation strategies involving Lagrangian data. It is in this kind of context that the method may prove to be a useful assimilation tool in oceanic studies.