天波超视距雷达微多径测高信号模型研究

当前天波超视距雷达基于低通滤波的测高信号模型存在近似,影响了目标高度测量的精度.为了提高天波超视距雷达目标高度测量的精度,提出了新的基于数据截断的天波雷达测高信号模型.仿真结果表明,随着信噪比增加,传统信号模型误差迅速增大,新模型误差基本保持不变,说明传统信号模型存在模型误差,证实了新模型的有效性.该模型的提出为改进天波雷达测高方法研究提供了基础.

直接地理编码与星载干涉SAR测高不确定度的等效性分析

现有的考虑地球曲率影响的INSAR测高模型主要有星载干涉SAR测高模型和直接地理编码两种。星载干涉SAR测高模型首先利用SAR干涉获取非模糊干涉相位,然后根据考虑地球曲率的空间几何关系直接计算地形高度。而直接地理编码模型则是在SAR干涉获取非模糊干涉相位的基础上,利用两个斜距方程和一个多普勒方程给出地面点的3维坐标值。由于两种模型得到地形高程的途径不同,因此很难直接比较这两种模型的地形测高不确定度。该文在采用矩阵形式推导出直接地理编码模型地形高程不确定度显示表达式的基础上,通过引入斜距平面坐标系,定量化地证明了直接地理编码模型的高程测量不确定度公式与考虑地球曲率的SAR干涉测高模型的测高不确定度公式是相同的,从而说明了这两种模型在用于地形高程测量时具有相同的精度。最后采用计算机仿真验证了理论分析的正确性。

J_2摄动对分布式卫星SAR系统测高精度影响分析

建立精确的分布式卫星SAR系统测高模型,对系统的分析和设计具有重要的意义.在考虑地球扁率的前提下,建立了一种精确的分布式卫星SAR系统测高模型,并进行了测高精度分析.同时考虑分布式卫星SAR系统在轨运行过程中受到各种摄动力的影响,为了考察在轨运行情况下系统的测高性能,以摆式构形的分布式卫星SAR系统为例,在Js摄动情况下进行测高精度的数学仿真.结果表明在考虑J2摄动情况下,随着系统运行时间的增加,摆式构形的分布式卫星SAR系统测高精度变化幅值逐渐增大.针对J2摄动对系统测高精度的影响,提出了通过提高系统基线,方位角,和干涉相位角的测量精度来保证系统正常工作的方法.

无基点海洋重力测量数据归算补救方法

针对海洋重力测量中可能出现基点信息缺失(也就是无有效基点信息,统称无基点)的一些特殊情况,在分析评估国际上近期发布的全球重力位模型和卫星测高重力模型的可靠性及有效性基础上,提出了利用前述两类模型作为海域重力场中长波控制基准,进而开展无基点海洋重力测量数据归算的补救方法研究,给出了数据归算的流程和步骤,分析评估了补救处理方法的适用条件和精度水平,使用海上实际观测数据对推荐的补救方法进行了有效性验证,证明将两类模型应用于无基点海洋重力测量数据补救处理是有效可行的。

无人机载北斗反射信号的海面测高性能评估

近年来,无人机的快速发展赋予了全球导航卫星系统卫星反射(Global Navigation Satellite Systems-Reflectometry,GNSS-R)信号机载观测平台更大的发展空间。针对目前对北斗卫星导航系统(BDS)反射信号(特别是B3频段)机载海面测高研究较少的现状,使用自研无人机机载微小型北斗反射信号探测仪,接收北斗B1、B3频段反射信号的多普勒时延图(Delay Doppler Map,DDM),建立机载DDM海面高度反演模型对海面高度进行实时反演。将反演结果分别与实测数据、丹麦科技大学(DTU)全球海面高度模型的结果进行对比,通过均方根误差(RMSE)与平均绝对误差(MAE)描述测高结果的精度。使用无人机在山东省威海市山东大学威海分校附近的黄海海域进行了三次实验,实现了无人机载北斗B1、B3频段反射信号(BDS-R)海面高度反演,反演精度达到了分米级;验证了研发的微小型北斗反射信号探测仪用于机载海面测高的有效性。

Adaptive moving target detection algorithm based on Gaussian mixture model

In order to enhance the reliability of the moving target detection, an adaptive moving target detection algorithm based on the Gaussian mixture model is proposed. This algorithm employs Gaussian mixture distributions in modeling the background of each pixel. As a result, the number of Gaussian distributions is not fixed but adaptively changes with the change of the pixel value frequency. The pixels of the difference image are divided into two parts according to their values. Then the two parts are separately segmented by the adaptive threshold, and finally the foreground image is obtained. The shadow elimination method based on morphological reconstruction is introduced to improve the performance of foreground image＇s segmentation. Experimental results show that the proposed algorithm can quickly and accurately build the background model and it is more robust in different real scenes.

Relationship between Rice Planthopper Occurrence Area in China and Atmospheric Circulation Indices

[Objective] This study aimed to establish models based on atmospheric cir- culation indices for forecasting the area attacked by rice planthopper every year, and to provide guide for preventing and controlling planthopper damage. [Method] The data related to rice planthopper occurrence and atmospheric circulation were collected and analyzed with the method of stepwise regression to establish the prediction models. [Result] The factors significantly related to the area attacked by rice plan-thopper were selected. Two types of prediction models were established. One was for Sogatella furcifera （Horvath）, based on Atlantic-Europe circulation pattern W in October in that year, Pacific polar vortex area index in October in that year, North America subtropical high index in August in that year, Atlantic-Europe circulation pattern W in June in that year, northern boundary of North America subtropical high in February in that year, Atlantic-Europe polar vortex intensity index in October in that year and Asia polar vortex intensity index in November in the last year; the other type of prediction models were for Nilaparvata lugens （Stal）, based on the Eastern Pacific subtropical high intensity index in July in that year, northern hemi- sphere polar vortex area index in October in the last year, Asia polar vortex strength index in November in the last year, north boundary of North America-At- lantic subtropical high in September in that year, north boundary of North Africa-At- lantic-North America subtropical high in January in that year, sunspot in September of the last year and eastern Pacific subtropical high area index in September in that year. [Conclusion] With the stepwise regression, the forecasting equations of the rice planthopper occurrence established based on the atmospheric circulation indices could be used for actual forecast.

Small-Signal Equivalent Circuit Modeling of a Photodetector Chip

A small-signal equivalent circuit model and the ted. The equivalent lumped circuit, which takes the main extraction techniques for photodetector chips are presen- factors that limit a photodetector＇s RF performance into consideration,is first determined based on the device＇s physical structure. The photodetector＇s S parameters are then on-wafer measured, and the measured raw data are processed with further calibration. A genetic algorithm is used to fit the measured data, thereby allowing us to calculate each parameter value of the model. Experimental resuits show that the modeled parameters are well matched to the measurements in a frequency range from 130MHz to 20GHz, and the proposed method is proved feasible. This model can give an exact description of the photodetector chip＇s high frequency performance,which enables an effective circuit-level prediction for photodetector and optoelectronic integrated circuits.

Construction of crash prediction model of freeway basic segment based on interactive influence of explanatory variables

In order to improve the prediction precision of the safety performance function （SPF） of freeway basic segments, design and crash data of 640 segments are collected from different institutions. Three negative binomial （NB） regression models and three generalized negative binomial （GNB） regression models are built to prove that the interactive influence of explanatory variables plays an important role in fitting goodness. The effective use of the GNB model in analyzing the interactive influence of explanatory variables and predicting freeway basic segments is demonstrated. Among six models, the two models （one is the NB model and the other is the GNB model. ） which consider the interactive influence of the annual average daily traffic （AADT） and length are more reasonable for predicting results. Furthermore, a comprehensive study is carried out to prove that when considering the interactive influence, the NB and GNB models have almost the same fitting performance in estimating the crashes, among which the GNB model is slightly better for prediction performance.

卫星测高重力模型在海空重力测量误差检测中的应用

针对海空重力测量常见的粗差和系统误差干扰问题,在分析评估国际上近期发布的卫星测高重力模型的可靠性和有效性基础上,提出了利用卫星测高重力模型作为比对控制基准,分步检测海空重力测量大粗差、小粗差和系统偏差的方法、流程及计算模型,分析比较了不同检测方法的技术特点和适用条件,使用海上实际观测数据对推荐的检测方法进行了有效性验证,证明将卫星测高重力模型应用于海空重力测量粗差和系统误差检测是可行和有效的.

Review of Digital Elevation Model (DEM) Based Research on China Loess Plateau

The Loess Plateau is one of the hot research areas for its specific geographical features. In resent years, with the establishment of national multi-scale DEMs and the perfection of DEM based digital terrain analysis methods, new thoughts and methodologies have been constructed for the Loess Plateau research. This paper introduces the characteristics of DEM data, analyses the development stages of DEM applied in the Loess Plateau research, and discusses its further possible research direction. More discussions are focused on slope spectrum and its concept, as well as the significance in the Loess Plateau research.

A Case Study of Using External DEM in InSAR DEM Generation

Synthetic aperture radar interferometry (InSAR) has been used as an innovative technique for digital elevation model (DEM) and topographic map generation. In this paper, external DEMs are used for InSAR DEM generation to reduce the errors in data processing. The DEMs generated from repeat-pass InSAR are compared. For steep slopes and severe changes in topography, phase unwrapping quality can be improved by subtracting the phase calculated from an external DEM. It is affirmative that the absolute height accuracy of the InSAR DEM is improved by using external DEM. The data processing was undertaken without the use of ground control points and other manual operation.

Dynamic soft sensor development based on Gaussian mixture regression for fermentation processes

The dynamic soft sensor based on a single Gaussian process regression(GPR) model has been developed in fermentation processes.However,limitations of single regression models,for multiphase/multimode fermentation processes,may result in large prediction errors and complexity of the soft sensor.Therefore,a dynamic soft sensor based on Gaussian mixture regression(GMR) was proposed to overcome the problems.Two structure parameters,the number of Gaussian components and the order of the model,are crucial to the soft sensor model.To achieve a simple and effective soft sensor,an iterative strategy was proposed to optimize the two structure parameters synchronously.For the aim of comparisons,the proposed dynamic GMR soft sensor and the existing dynamic GPR soft sensor were both investigated to estimate biomass concentration in a Penicillin simulation process and an industrial Erythromycin fermentation process.Results show that the proposed dynamic GMR soft sensor has higher prediction accuracy and is more suitable for dynamic multiphase/multimode fermentation processes.

Establishment and tests of EnOI assimilation module for WAVEWATCH Ⅲ

In this paper, we propose a parallel data assimilation module based on ensemble optimal interpolation （EnOI）. We embedded the method into the full-spectral third-generation wind-wave model, WAVEWATCH III Version 3.14, producing a wave data assimilation system. We present our preliminary experiments assimilating altimeter significant wave heights （SWH） using the EnOI-based wave assimilation system. Waters north of 15°S in the Indian Ocean and South China Sea were chosen as the target computational domain, which was two-way nested into the global implementation of the WAVEWATCH III. The wave model was forced by six-hourly ocean surface wind velocities from the cross-calibrated multi-platform wind vector dataset. The assimilation used along-track SWH data from the Jason-2 altimeter. We evaluated the effect of the assimilation on the analyses and hindcasts, and found that our technique was effective. Although there was a considerable mean bias in the control SWHs, a month-long consecutive assimilation reduced the bias by approximately 84% and the root mean-square error （RMSE） by approximately 65%. Improvements in the SWH RMSE for both the analysis and hindcast periods were more significant in July than January, because of the monsoon climate. The improvement in model skill persisted for up to 48 h in July. Furthermore, the SWH data assimilation had the greatest impact in areas and seasons where and when the sea-states were dominated by swells.

Orthorectification of IKONOS and Impact of Different Resolution DEM

IKONOS image has been wildly used in city planning, precision agriculture and emergence response. However, the accuracy of IKONOS Geo product is limited due to distortion caused by terrain relief. Orthorectification was performed to remove the distortion and the impact of different DEM on orthorectification were evaluated. 38 ground control points (GCPs) and 25 independent check points (ICPs) were collected. DEMs were generated from 1∶10 000 and 1∶50 000 topographic maps. Results show that RMS error at the check points is 1.554 0 m using DEM generated from 1∶10 000 topographic map, which can meet the accuracy requirement of IKONOS Precision product (1.9 m RMSE). While RMS error is 2.572 4 m using DEM generated from 1∶50 000 topographic map.

Moving object detection method based on complementary multi resolution background models

A novel moving object detection method was proposed in order to adapt the difficulties caused by intermittent object motion,thermal and dynamic background sequences.Two groups of complementary Gaussian mixture models were used.The ghost and real static object could be classified by comparing the similarity of the edge images further.In each group,the multi resolution Gaussian mixture models were used and dual thresholds were applied in every resolution in order to get a complete object mask without much noise.The computational color model was also used to depress illustration variations and light shadows.The proposed method was verified by the public test sequences provided by the IEEE Change Detection Workshop and compared with three state-of-the-art methods.Experimental results demonstrate that the proposed method is better than others for all of the evaluation parameters in intermittent object motion sequences.Four and two in the seven evaluation parameters are better than the others in thermal and dynamic background sequences,respectively.The proposed method shows a relatively good performance,especially for the intermittent object motion sequences.

Assimilation of High Frequency Radar Data into a Shelf Sea Circulation Model

High Frequency(HF) radar current data is assimilated into a shelf sea circulation model based on optimal interpolation(OI) method. The purpose of this work is to develop a real-time computationally highly efficient assimilation method to improve the forecast of shelf current. Since the true state of the ocean is not known, the specification of background error covariance is arduous. Usually, it is assumed or calculated from an ensemble of model states and is kept in constant. In our method, the spatial covariances of model forecast errors are derived from differences between the adjacent model forecast fields, which serve as the forecast tendencies. The assumption behind this is that forecast errors can resemble forecast tendencies, since variances are large when fields change quickly and small when fields change slowly. The implementation of HF radar data assimilation is found to yield good information for analyses. After assimilation, the root-mean-square error of model decreases significantly. Besides, three assimilation runs with variational observation density are implemented. The comparison of them indicates that the pattern described by observations is much more important than the amount of observations. It is more useful to expand the scope of observations than to increase the spatial interval. From our tests, the spatial interval of observation can be 5 times bigger than that of model grid.

Simulation of mold filling and prediction of gas entrapment on practical high pressure die castings

Element parameters including volume filled ratio,surface dimensionless distance,and surface filled ratio for DFDM(direct finite difference method)were proposed to describe shape and location of free surfaces in casting mold filling processes.A mathematical model of the filling process was proposed specially considering the mass,momentum and heat transfer in the vicinity of free surfaces.Furthermore,a method for gas entrapment was established by tracking flow of entrapped gas.The model and method were applied to practical ADC1 high pressure die castings.The gas entrapment prediction was compared with the fraction and maximum size of porosities in the different casting parts.The comparison shows validity of the proposed model and method.The study indicates that final porosities in high pressure die castings are dependent on both gas entrapment during mold filling process and pressure transfer within solidification period.

Comparison of TOPEX/POSEIDON altimeter derived wave period with ocean buoy data in the East China Sea and South China Sea

Altimeter wave period data obtained from continental shelf seas are analyzed in this paper. Empirical models are introduced for zero up-crossing and peak wave period calculation with TOPEX/POSEIDON data. Their performances are assessed using independent validation dataset in four sites in the open ocean of China. To provide more accurate wave period estimation, new coefficients are applied to reliable in situ data. Comparison of our estimated the wave periods with new linear calibrations based on independent data of Seapac 2100 deployed in the East China Sea and South China Sea showed that the accuracy was improved over estimates determined from earlier empirical models. Regional analysis indicated that the wave period model works better under wind sea condition.