基于Unity的船浪实时交互运动可视化系统

为解决现有航海模拟器中船浪运动分离导致的视景感受体验差的问题, 开发了一套船浪实时交互的船舶运动可视化仿真系统. 通过海浪谱建模技术构建海面波浪运动场景; 在建立船舶受力模型的基础上, 通过检测船舶与水面的碰撞实现船舶对波浪力的响应以计算船舶对波浪运动的实时响应姿态变化; 同时为增强仿真系统的真实感, 使用波动公式计算船舶与水体碰撞产生的水波及其扩散增强模拟真实感. 船浪运动耦合的航海模拟器与传统航海模拟器相比, 在大海况条件下能够为使用者提供更加真实的视景与运动体验. 研究成果视景真实感强, 船浪交互实时性好, 对于恶劣航海条件下的航海过程有良好的仿真效果.     

基于MFC/Vega的可见光目标运动模拟器

视景仿真是虚拟现实技术最主要的表现形式,使用Visual C 的Microsoft Foundation class可以更简单地开发基于Vega的视景仿真系统.文中利用三维建模工具MultiGen Creator、视景仿真工具Vega和MFC设计了可见光目标运动模拟器系统,该系统模拟了跟踪目标的运动,用于测试光电设备的跟踪速度.首先介绍了Vega软件平台的基本结构;其次简单介绍了可见光目标运动模拟器的组成和功能;最后对可见光目标运动模拟器的框架及有关的模块进行了具体实现.     

电脑仿真技术应用于船舶驾驶的实践教学

本操纵模拟器配备了船舶操作台以及相应的设备,高质量画面的宽视场角视景,可以为操作者提供逼真的训练和试验环境,能全面满足STCW78/95公约相关模拟器性能标准的要求。本文介绍了仿真操纵模拟器的设计思路,以及该系统的研发与应用价值。     

船舶操纵模拟器视景中的山形建模

船舶操纵模拟器是一种能够部分模仿海上真实情况,专门为满足与培训、技术研究等目的而设计研制的装置,其核心技术之一是海上视景模拟,而地形地貌是海上视景中的重要组成部分,根据船舶操纵模拟器实时视景显示的需要,在分析航行舰艇对可视范围内重要岛屿与背景山脉的几何精神要求的基础上,提出了基于待高线的山形堆积建模和山形轮廓建模方法,并给出了山形轮廓图形的误差定义、有效适用范围,以及船舶操纵模拟器中地形建模的误差准则,该方法生成图形的数据量较小,其图形更新速率与几何精度能达到船舶操纵模拟器实时视景显示的要求。     

全垫升气垫船四自由度运动仿真

为了研究全垫升气垫船的操纵性,建立了气垫船的运动仿真模型.通过船模风洞试验和平面运动机构试验分别得到了气垫船的空气动力系数和水动力系数,建立了空气动力和水动力数学模型;对各个方向的合外力进行合成,依照牛顿动量和动量矩定理,建立了全垫升气垫船的运动数学模型.利用冻结一解冻算法编制了气垫船运动仿真程序,并进行了操纵仿真试验,研究了气垫船的直线航行与回转运动的操纵特性.仿真结果表明所建立气垫船模型是合理的,所采用的算法是有效的.     

海面场景虚拟仿真方法

虚拟自然环境的计算机生成是视景仿真领域的研究难点.在海洋作战视景仿真以及航海视景仿真中,海浪形态的模拟占据相当大的比重.文中重点研究了几种常用海浪视景建模仿真方法,并指出了各种方法的优缺点和适用场合.讨论了海浪建模中的LOD技术,以及海面环境中光照效果的模拟技术.指出了海面环境视景仿真进一步的研究方向.     

基于虚拟现实技术的飞行视景仿真

飞行视景仿真是飞行仿真的一个重要组成部分，它的视觉效果和逼真程度将直接影响整个飞行模拟器的逼真度。讨论了飞行视景系统的构成、视景的生成与显示，并介绍了几种开发视景系统的工具软件，重点讨论了虚拟现实技术在飞行视景仿真中的应用和关键技术。     

交互式履带起重机模拟器系统关键技术研究

关于起重机仿真系统优化设计问题,在现有履带起重机系统的研究基础之上,建立了起重机系统的运动学/动力学简化模型。对机构的运动和受力状态,视景系统要求利用OSG图形系统进行实时渲染,生成具有真实感的虚拟环境,利用机电控制技术将各子系统可靠集成,建立起整个模拟器系统,实现了起重机的交互式操作的仿真环境,应用Matlab RTW进行建模与实时仿真分析,为工程机械领域提供了一种新的操作培训方法。通过仿真证明了实时仿真模型的正确性以及模拟器系统的可用性。     

大型运输机综合训练器虚拟仿真环境的设计

某型运输机综合训练模拟器具有飞行场景复杂、仿真仪表多、人机交互信息量大等特点.虚拟仿真环境的建立,是开发该模拟器的关键.介绍了综合训练模拟器的体系结构和虚拟仿真环境的开发方法.采用对全包线范围内的气动参数进行动态插值的方法,建立了兼顾模拟精度的准定常六自由度全量飞机运动模型;阐述了场景建模的方法和视景驱动程序的框架;给出了虚拟仪表的开发路线和人机交互的实现方法.与整个系统联调表明,该系统结构合理可靠,采用的运动模型和仿真算法满足了系统的实时性和精确度要求,图像显示效果逼真.     

某型飞机空中加受油训练模拟器的研制

根据加受油模拟训练的实际需求,提出了某型飞机空中加受油训练模拟器的功能,设计了模拟器的体系结构,并说明了模拟器模拟座舱、飞行仿真、伞套运动、运动平台、信号采控、操纵负荷、视景、教员控制台、计算机网络、音响通讯等分系统的实现。该模拟器采用实物与图像相结合的半实物仿真方式,空中对接环节临场感强、效果逼真,对实装飞行帮助很大,受训飞行员对该模拟器评价较好。该模拟器的投入使用,对提高仿真训练的质量效益,促进部队战斗力建设具有十分重要的价值和意义。     

Evaluation of SeaWiFS chlorophyll algorithms in the Southwestern Atlantic and Southern Oceans

Bio-optical measurements of spectral upwelling radiance and surface chlorophyll-a concentration have been conducted during 15 cruises between 1995 and 2004. The bio-optical data were divided into two sub-sets: the Southwestern Atlantic Ocean (SwAO), comprising a variety of biogeochemical provinces, from the oligotrophic waters in the South Atlantic gyre to the coastal waters influenced by La Plata River and Patos Lagoon discharge, and the Southern Ocean (SO) data set, comprising sampling stations south of the mean position of the Polar Front, with most stations being located in the vicinity of the Antarctic Peninsula. We derived regional chlorophyll algorithms for both regions and comparisons were made with the NASA's OC4v4 (operational algorithm) and OC2v4. For the Southwestern Atlantic region, the NASA OC4v4 algorithm presented a reasonable performance (r²=0.87, rmse-L=0.475, N=136) as compared to the revised algorithm for SwAO data (r²=0.89, rmse-L=0.426, N=136). A few stations under strong river plume influence were not considered in the analyses. These were detected by a higher reflectance at 670 nm, at low in situ chlorophyll concentration (<2 mg m⁻³). These results show that empirical algorithms applied to in-situ radiance data have a limited ability to extract accurate chlorophyll estimates below a 30% uncertainty level. For Southern Ocean stations, a 2-band linear-type model was generated (r²=0.64, rmse-L=0.347, N=77), which significantly improved the bias (6.4%) as compared to NASA's OC4v4 algorithm (bias=−21.7%). An evaluation of some published high-latitude algorithms on our data set has shown a better performance by taxon-specific models, even from distant regions. A validation experiment of the normalized spectral water-leaving radiances and chlorophyll-a SeaWiFS products was also conducted using the FURG-SwAO/SO data set, through a match-up exercise. Despite the relatively low number of pairs of radiometric measurements, SeaWiFS estimations compare well with in situ data (0.77<r²<0.98, N=21), although the satellite estimate show a marked bias (−35.6%) in the blue band nL_w (412). Regarding the chlorophyll-a concentration, an overall agreement was observed (r²=0.77, rmse-L=0.66, N=28), with a mean absolute percentage difference of 66%, which is above the goal generally accepted of 35% for satellite ocean color chlorophyll estimates. For the studied Southern Ocean area (mainly the Bransfield Strait), NASA's OC4v4 algorithm systematically underestimates chlorophyll above 0.2 mg m⁻³, as previously demonstrated by other researchers.     

Assessment of apparent and inherent optical properties derived from SeaWiFS with field data

The knowledge of the absorption and scattering characteristics of the ocean supports diverse applications for studying biological and physical processes of marine ecosystems. The determination of the related inherent optical properties from remote sensing is addressed for a site located in the northern Adriatic Sea using coincident SeaWiFS images and field measurements. The proposed methodology first combines regional algorithms to determine the spectra of irradiance reflectance and diffuse attenuation coefficient from the normalized water leaving radiance by accounting for the bidirectional structure of the light field. These spectra are then used as inputs to an inverse model that yields the absorption, scattering, and backscattering coefficients of seawater (considered without the contribution of pure water). The uncertainties associated with the different steps in the sequence of calculations are quantified and discussed. Specifically, the analysis of 48 match-ups comparing in situ irradiance reflectance with that derived from remote sensing water leaving radiance shows mean absolute differences below 20% between 490 and 555 nm and approximately 30% at 443 and 670 nm. Lower discrepancies are obtained if more stringent criteria for the selection of match-ups are implemented (12-15% and 20-22%, respectively). The results obtained with 42 match-ups show a reasonable agreement for the absorption coefficient from 412 to 490 nm (approximately 35%), the scattering coefficient from 443 to 555 nm (approximately 30%), and the attenuation coefficient in the spectral range 412-555 nm (approximately 30%). Based on 17 match-ups, the comparison for the backscattering coefficient gives mean absolute differences in the range of 31-53%. The comparison between field and derived scattering properties suggests that the particulate scattering phase function inherent to the inverse model is not appropriate for the site considered. Finally, in the framework of the selected inversion scheme, uncertainties associated with the satellite derived irradiance reflectance in the blue and the determination of K_d at 490 nm through an empirical band ratio algorithm appear as the elements where improvements would be particularly needed to derive high quality spectra of inherent optical properties.     

Sampling biases in MODIS and SeaWiFS ocean chlorophyll data

Although modern ocean color sensors, such as MODIS and SeaWiFS, are often considered global missions, in reality it takes many days, even months, to sample the ocean surface enough to provide complete global coverage. The irregular temporal sampling of ocean color sensors can produce biases in monthly and annual mean chlorophyll estimates. We quantified the biases due to sampling using data assimilation to create a “truth field”, which we then sub-sampled using the observational patterns of MODIS and SeaWiFS. Monthly and annual mean chlorophyll estimates from these sub-sampled, incomplete daily fields were constructed and compared to monthly and annual means from the complete daily fields of the assimilation model, at a spatial resolution of 1.25° longitude by 0.67° latitude.The results showed that global annual mean biases were positive, reaching nearly 8% (MODIS) and > 5% (SeaWiFS). For perspective the maximum interannual variability in the SeaWiFS chlorophyll record was about 3%. Annual mean sampling biases were low (< 3%) in the mid-latitudes (between − 40° and 40°). Low interannual variability in the global annual mean sampling biases suggested that global scale trend analyses were valid.High latitude biases were much higher than the global annual means, up to 20% as a basin annual mean, and over 80% in some months. This was the result of the high solar zenith angle exclusion in the processing algorithms. Only data where the solar angle is < 75° are permitted, in contrast to the assimilation which samples regularly over the entire area and month. High solar zenith angles do not facilitate phytoplankton photosynthesis and low chlorophyll concentrations occurring here are missed by the data sets. Ocean color sensors selectively sample in locations and times of favorable phytoplankton growth, producing overestimates of chlorophyll.The biases derived from lack of sampling in the high latitudes varied monthly, leading to artifacts in the apparent seasonal cycle from ocean color sensors. A false secondary peak in chlorophyll occurred in May-August, which resulted from lack of sampling in the Antarctic.Persistent clouds, characteristic in the North Pacific, also produced overestimates, again by selectively sampling only the high growth periods. In contrast, areas characterized by thick aerosols showed chlorophyll underestimates to nearly − 30% in basin monthly means. This was the result of selective sampling in lower aerosol thickness periods, which corresponded with lower phytoplankton growth periods.A combination of MODIS and SeaWiFS sampling was most effective at reducing mid-latitude biases due to inter-orbit gaps, sun glint, and sensor tilt changes. But these biases were low using a single sensor, suggesting multiple sensors had little effect in reducing global and regional monthly and annual mean biases.Ocean color data are an invaluable source of information about global biological processes. However, these results suggest that sampling errors need to be considered in applications involving global and regional mean chlorophyll biomasses as well as seasonal variability and regional trend analysis.     

Two-component modeling of the optical properties of a diatom bloom in the Southern Ocean

Diatom cells have distinctive optical characteristics, originating from their relatively large cell size, fucoxanthin content and silica cell wall. It has been proposed that diatom-dominated phytoplankton blooms can be identified by optical remote sensing and that specifically tuned chlorophyll and primary production algorithms should be applied in regions where these blooms are present. However there have been few studies on how the optical properties of diatom blooms change as they progress from active growth to senescence, and it is unlikely that measurements on laboratory cultures encompass the full range of physiological states found in natural waters. We have therefore examined the inherent optical properties (IOPs) of the waters around the island of South Georgia at the end of the spring diatom bloom. Considerable variability was found in the relationships between the inherent optical properties and analytically determined chlorophyll a concentrations even in the surface layer, which meant that the usual bio-optical assumptions for Case 1 waters did not apply. To account for this variability, phytoplankton absorption and scattering were modeled as a two-component mixture, with the components representing actively growing and senescent material. The specific inherent optical properties of the two components were derived by linear regression of total IOPs against chlorophyll concentration and a fraction of the suspended mineral concentration. These specific IOPs were used to develop radiative transfer models of diatom blooms in varying stages of growth and senescence. Remote sensing reflectances calculated using this technique confirmed the tendency of the standard algorithms employed in SeaWiFS, MODIS and MERIS data processing to under-estimate near-surface chlorophyll concentrations in diatom blooms. However the inclusion of increasing proportions of senescent material had a significant effect on algorithm performance only at chlorophyll concentrations below 10 mg m^− 3. Optical depths predicted by the model around South Georgia were 9 +/− 2 m at 512 nm, indicating that a large fraction of the phytoplankton biomass was located below the depth from which the remote sensing signals originated.     

Ocean sand ridge signatures in the Bohai Sea observed by satellite ocean color and synthetic aperture radar measurements

Satellite measurements from Synthetic Aperture Radar (SAR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua platform are used to study the ocean sand ridges in the eastern Bohai Sea in China. Even though the imaging mechanisms for SAR and MODIS-Aqua remote sensing are different, the sand ridges are shown to have exactly the same patterns in images from both sensors. Therefore, the location, extension and coverage of the ocean sand ridges can be detected and cross-examined by both SAR and MODIS-Aqua observations. Satellite images show quite different sand ridge distribution pattern from the published bathymetry map (based on in situ data) that shows six sand ridges in the area. 10 finger-shaped sand ridges are identified from satellite observations. The tidal-current/sand-ridge interaction driven physical and optical changes are assessed and evaluated. The existence of sand ridges causes enhanced water diffuse attenuation coefficient K_d(490) and elevated normalized water-leaving radiance at the red and near-infrared (NIR) wavelengths. The sea surface over the sand ridges experiences significant seasonal variability of water turbidity and shows remarkable differences from nearby ocean regions. During winter, K_d(490) values are about 2-3 m^− 1 over the ridges, while the maximum K_d(490) in the neighboring oceans is approximately 1.5 m^− 1. In summer, the enhancement of the sea surface turbidity is less significant than that which occurs in winter.     

几类特殊图的匹配可扩性

如果图G的每一个偶匹配都可以扩充为G的一个完美匹配，则称图G是偶匹配可扩的。论文主要刻画了图Cm×Pn、Pm×Pn和双轮图的匹配可扩性，从而为研究这些图的可扩性奠定了基础。     

立体视觉匹配技术

立体视觉匹配技术是计算机视觉领域中最为关键的研究分支。根据匹配基元的不同,立体视觉匹配算法分为区域匹配、特征匹配和相位匹配三大类。其中,相位匹配是近二十年才逐步发展起来的一类匹配算法。以往关于立体匹配算法的综述文章对相位匹配这类新型算法几乎没有系统的阐述,而且很少从算法设计的角度分析和比较现有的立体视觉匹配技术。该文将算法设计过程分成三个步骤,在各个步骤中采用由个性至共性的分析手段,对三类立体视觉匹配算法进行了详细的评述,包括它们的理论依据、基本特性和改进策略的分析和比较,表明各类匹配算法的设计具有自身的发展特性。另一方面,“不适定”视觉问题普遍存在于各类匹配算法中,因此它们对算法设计的优化又存在着许多共性。文章通过由点至面的分析过程,旨在为算法设计者从综合思考的角度去优化算法提供技术借鉴,包括匹配基元自身缺陷的克服和普遍存在的不适定视觉问题的解决。此外,算法的完善和更佳算法模型的推出还依赖于科学的算法评价手段,文中根据不同用途对算法评价方法进行了分类,使算法性能的评估有了科学的指导方法。     

基于数据模型演化过程中模式匹配算法研究

论文对国内外关于模式匹配的研究进行综合分析,主要从模式匹配的角度对复杂模式匹配过程进行了研究,并着重对结构化的模式匹配进行了研究,对结构相似度和语言相似度进行综合;在语言匹配的基础上,对结构匹配进行分类匹配,采用自顶向下分别从非叶子节点和叶子节点进行模式匹配,非叶子节点匹配结果对叶子节点匹配结果有传递指导作用.该方法是一种利用元素间的结构信息来辅助模式匹配的新方法.最终达到提高模式匹配结果准确率的目的.     

影像匹配中的若干基本问题研究

影像匹配算法的有效性依赖于对一些共同的基本问题的解决,即选择正确的匹配基元,寻找基元间的本质属性,制定相应的匹配准则（约束条件）,采用合理的匹配策略,设计良好的算法结构等等。首先分析了3种常用匹配基元的特点并提出匹配基元的选取依据,接着归纳出了5种常用的匹配准则,对分层匹配、全局搜索等4种匹配策略进行了讨论,最后设计了一种3个阶段、9个步骤的影像匹配算法结构。实验结果表明：匹配效果良好,对这些基本问题的研究有利于建立通用的影像算法模型,设计更高效的影像匹配算法。