拓展目标量测集合分割算法

针对拓展目标概率假设密度滤波器采用的量测集合所有可能分割方式在实际中几乎不能够实现的问题,提出了一种采用有限混合模型的量测集合近似分割算法,对所有可能分割方式进行近似处理。算法利用有限混合模型拟合量测集合以实现对量测集合的分割,首先利用期望极大化算法极大似然估计混合参数,然后利用量测来源的条件概率分割量测集合,最后以二维场景为例进行了仿真实验。仿真结果表明:新算法在所有时刻上的最优子模式分配和混合分量数目均小于现有的典型量测集合分割算法;在拓展目标跟踪性能上,新算法具有更好的多拓展目标跟踪性能。     

拓展目标混合分量删减算法

针对拓展目标概率假设密度滤波器高斯混合实现中的混合分量增长问题,提出混合分量的极大似然删减算法.该算法利用期望极大化方法实现混合分量的极大似然删减;视量测在混合分量的来源指标集为缺失量;取混合参数的先验分布为依赖于混合权重的分布;在期望步,计算量测在混合分量来源指标的条件概率;在极大化步,通过混合权重置零来实现相关度较小混合分量的删减.仿真结果表明,该混合分量极大似然删减算法优于典型阈值删减算法.     

基于噪声方差估计的高斯混合概率假设密度滤波算法

针对传统的高斯混合概率假设密度(GM-PHD)滤波器在噪声先验特性未知或不准确时跟踪性能会下降,提出了一种基于噪声方差估计的高斯混合概率假设密度(NCE-GM-PHD)滤波算法.该算法可以同时在线估计时变的目标个数、多目标状态以及噪声方差.首先,通过引入遗忘因子和采取有偏估计的方法改进了传统的Sage-Husa自适应滤波器.基于改进的自适应滤波器,推导了带噪声方差估计的GM-PHD滤波算法.仿真结果表明,在非时变或时变量测噪声方差未知的情况下,NCE-GM-PHD算法的跟踪性能优于传统的GM-PHD算法,对噪声变化的适应能力更强.     

标签多伯努利机动目标跟踪与分类算法

针对密集杂波下现有的多机动目标跟踪算法性能衰减严重的问题,提出了一种标签多伯努利目标跟踪与分类算法。首先,引入类别信息对目标状态进行扩维;然后利用类别属性对目标机动模型转移密度进行修正,并推导新的状态转移密度函数,抑制了错误机动模型对目标状态预测的影响;同时,建立目标位置与属性的联合量测似然函数,增大了目标与杂波的区分度,从而增强杂波抑制能力;最后,基于多模型标签多伯努利滤波器框架推导了新的预测、更新方程。仿真实验结果表明:所提算法在高杂波环境下仍能对多机动目标进行有效跟踪,其目标数估计误差及最优子模式分配距离分别约为多模型概率假设密度联合检测、跟踪、分类滤波器的1/2和1/4,为多模型势平衡多伯努利联合检测、跟踪、分类滤波器的3/4和1/2。     

高斯混合扩展目标多伯努利滤波器

针对杂波环境下多扩展目标跟踪中数据关联过程复杂的问题,提出一种可同时估计扩展目标状态和目标数的高斯混合扩展目标多伯努利(GM-ET-MBer)滤波器,该滤波器无需对测量与扩展目标进行关联。首先采用伯努利随机有限集和泊松随机有限集分别描述扩展目标的状态和观测;然后结合扩展目标状态的预测信息,推导了扩展目标状态的更新方程,并在线性高斯条件下采用高斯混合方法递推地对扩展目标的状态进行估计跟踪。与高斯混合扩展目标概率假设密度(GM-ET-PHD)滤波器相比,GM-ET-MBer滤波器有效地提高了对目标数的估计精度。仿真结果表明,GM-ET-MBer滤波器和GM-ET-PHD滤波器对目标数估计的标准偏差分别为0.267 3和0.395 3,可知所提滤波器对目标数的估计更稳定。     

多个不可分辨目标群的联合检测与估计误差界

针对杂波和漏检同时存在时多个不可分辨目标群联合检测与估计的性能评价问题,在随机有限集框架下,利用信息不等式和最优子模式分配距离提出了该问题的误差(下)界。首先将多个不可分辨目标群的状态建模为多Bernoulli随机有限集,并利用Mahler提出的连续个体目标数假设建模群目标测量似然函数;然后,结合最大后验概率检测和无偏估计准则获得了建议的误差界。仿真实验展示了该误差界随杂波密度和传感器检测概率的变化趋势,并利用不可分辨目标群势概率假设密度滤波器和不可分辨目标群势平衡多目标多Bernoulli滤波器对该误差界的有效性进行了验证。实验表明,利用该误差界可以对现有的不可分辨目标群联合检测与估计算法的性能进行有效衡量,使其在不同杂波密度和检测概率下的平均相对误差不超过7%。     

一种改进的高斯混合概率假设密度滤波器

针对近邻目标场景下高斯混合概率假设密度滤波器的滤波精度较差问题,该文提出一种改进的高斯混合概率假设密度滤波器。基于更新后的目标强度中目标身份信息,首先将近似同一目标的多个高斯分量融合为一个新的高斯分量,然后依据目标检测结果对各目标分量的权重进行重新分配以获取一个精确的后验强度。实验结果表明,与相关近邻目标GM-PHD滤波器相比,该文算法的目标状态及数目估计精度具有较大优势,且其滤波性能相对稳定。     

应用Dirichlet分布的概率假设密度多目标跟踪

针对多目标跟踪算法对多目标状态提取的需求,提出了一种基于Dirichlet分布的概率假设密度滤波器多目标状态提取方法.该算法利用负指数Dirichlet分布的不稳定性来极大似然估计多目标状态;利用期望极大化算法搜寻极大似然解,同时利用Dirichlet分布驱使不相关分量消亡;为了平衡成功初始化与减少算法时间开销的要求,利用k-d树初始化Dirichlet分布.仿真结果表明,基于Dirichlet分布的概率假设密度滤波器多目标状态提取算法在多目标跟踪中优于已有算法.     

一种新的多机动目标跟踪的GMPHD滤波算法

针对多机动目标跟踪的传统数据关联算法约束条件苛刻、估计精度低、计算量大等问题,提出了一种基于随机集理论的非数据关联的多机动目标跟踪算法.该算法将高斯混合概率假设密度(GMPHD)滤波与"当前"统计模型的优点相结合,绕过了棘手的数据关联问题,能高效处理目标数较大的机动跟踪问题.在漏检、虚警、多机动目标交叉杂波复杂环境下进行了仿真实验,结果表明,该算法具有较高的跟踪精度和稳健的跟踪性能.     

基于容积原则的概率假设密度滤波算法

为改善多目标跟踪问题中概率假设密度滤波精度与算法运行时间之间的关系,提高目标状态和数目的实时估计性能,提出了基于容积原则的概率假设密度滤波算法. 该算法在高斯混合粒子概率假设密度的框架下,利用容积数值积分原则直接计算非线性随机函数的均值和方差, 产生粒子滤波算法的重要性函数,实现高精度粒子的重构,来近似目标状态和数目的概率分布,并且在高斯混合概率假设密度滤波算法中进行采样和更新. 仿真验证了所提出算法的有效性,其Wasserstein误差距离优化了17.32%,目标数估计均值也提高了23.72%.      

Characterization of Ordovician carbonate reservoirs, southeastern Saskatchewan, Canada

The discovery of the prolific Ordovician Red River reservoirs in 1995 in southeastern Saskatchewan was the catalyst for extensive exploration activity which resulted in the discovery of more than 15 new Red River pools. The best yields of Red River production to date have been from dolomite reservoirs. Understanding the processes of dolomitization is, therefore, crucial for the prediction of the connectivity, spatial distribution and heterogeneity of dolomite reservoirs.The Red River reservoirs in the Midale area consist of 3～4 thin dolomitized zones, with a total thickness of about 20 m, which occur at the top of the Yeoman Formation. Two types of replacement dolomite were recognized in the Red River reservoir: dolomitized burrow infills and dolomitized host matrix. The spatial distribution of dolomite suggests that burrowing organisms played an important role in facilitating the fluid flow in the backfilled sediments. This resulted in penecontemporaneous dolomitization of burrow infills by normal seawater. The dolomite in the host matrix is interpreted as having occurred at shallow burial by evaporitic seawater during precipitation of Lake Almar anhydrite that immediately overlies the Yeoman Formation. However, the low δ18O values of dolomited burrow infills (-5.9‰～ -7.8‰, PDB) and matrix dolomites (-6.6‰～ -8.1‰, avg. -7.4‰ PDB) compared to the estimated values for the late Ordovician marine dolomite could be attributed to modification and alteration of dolomite at higher temperatures during deeper burial, which could also be responsible for its 87Sr/86Sr ratios (0.7084～0.7088) that are higher than suggested for the late Ordovician seawaters (0.7078～0.7080). The trace amounts of saddle dolomite cement in the Red River carbonates are probably related to "cannibalization" of earlier replacement dolomite during the chemical compaction.     

An Index mechanism for multi-scale view in spatial databases

There are numerous geometric objects stored in the spatial databases. An importance function in a spatial database is that users can browse the geometric objects as a map efficiently. Thus the spatial database should display the geometric objects users concern about swiftly onto the display window. This process includes two operations:retrieve data from database and then draw them onto screen. Accordingly, to improve the efficiency, we should try to reduce time of both retrieving object and displaying them. The former can be achieved with the aid of spatial index such as R-tree, the latter require to simplify the objects. Simplification means that objects are shown with sufficient but not with unnecessary detail which depend on the scale of browse. So the major problem is how to retrieve data at different detail level efficiently. This paper introduces the implementation of a multi-scale index in the spatial database SISP (Spatial Information Shared Platform) which is generalized from R-tree. The difference between the generalization and the R-tree lies on two facets: One is that every node and geometric object in the generalization is assigned with a importance value which denote the importance of them, and every vertex in the objects are assigned with a importance value,too. The importance value can be use to decide which data should be retrieve from disk in a query. The other difference is that geometric objects in the generalization are divided into one or more sub-blocks, and vertexes are total ordered by their importance value. With the help of the generalized R-tree, one can easily retrieve data at different detail levels.Some experiments are performed on real-life data to evaluate the performance of solutions that separately use normal spatial index and multi-scale spatial index. The results show that the solution using multi-scale index in SISP is satisfying.     

A computer generator for randomly layered structures

AcomputergeneratorforrandomlylayeredstructuresYUJia shun1,2,HEZhen hua2(1.TheInstituteofGeologicalandNuclearSciences,NewZealand;2.StateKeyLaboratoryofOilandGasReservoirGeologyandExploitation,ChengduUniversityofTechnology,China)Abstract:Analgorithmisintrod…     

海南岛地体及其毗邻陆缘晚中生代—新生代古地磁研究和构造演化

本文叙述了对海南岛及其毗邻大陆边缘白垩纪到第四纪地层岩石进行古地磁研究的全部工作过程。通过分析岩石中剩余磁矢量的磁偏角及磁倾角的变化,提出海南岛白垩纪以来经历的构造演化模式如下:早期伴随顺时针旋转而向南迁移,后期伴随逆时针转动并向北运移。联系该地区及邻区的地质、地球物理资料,对海南岛上述的构造地体运动提出以下认识:北部湾内早期有一拉张作用,主要是该作用使湾内地壳显著伸长减薄,形成北部湾盆地。从而导致了海南岛的早期构造运动,而海南岛后期的构造运动则主要是受南海海底扩张的影响。海南地体运动规律的阐明对于了解北部湾油气盆地的形成演化有重要的理论和实际意义。     

Exciton Seebeck in Molecular Systems

Various applications relevant to the exciton dynamics,such as the organic solar cell,the large-area organic light-emitting diodes and the thermoelectricity,are operating under temperature gradient.The potential abnormal behavior of the exicton dynamics driven by the temperature difference may affect the efficiency and performance of the corresponding devices.In the above situations,the exciton dynamics under temperature difference is mixed with     

Achieving Unusual States of Matter Under High Pressure

The elongation method,originally proposed by Imamura was further developed for many years in our group.As a method towards O(N)with high efficiency and high accuracy for any dimensional systems.This treatment designed for one-dimensional(ID)polymers is now available for three-dimensional(3D)systems,but geometry optimization is now possible only for 1D-systems.As an approach toward post-Hartree-Fock,it was also extended to     

《Chinese Science Bulletin》SUBJECT INDEX TO VOLUME 59(2014)

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An on-line scaling method for improving scalability of a database cluster

The explosive growth of the Internet and database applications has driven database to be more scalable and available, and able to support on-line scaling without interrupting service. To support more client's queries without downtime and degrading the response time, more nodes have to be scaled up while the database is running. This paper presents the overview of scalable and available database that satisfies the above characteristics. And we propose a novel on-line scaling method. Our method improves the existing on-line scaling method for fast response time and higher throughputs. Our proposed method reduces unnecessary network use, i.e. , we decrease the number of data copy by reusing the backup data. Also, our on-line scaling operation can be processed parallel by selecting adequate nodes as new node. Our performance study shows that our method results in significant reduction in data copy time.     

An improved R-tree based on childnode''s probability

R-Tree is a good structure for spatial searching. But in this indexing structure,either the sequence of nodes in the same level or sequence of traveling these nodes when queries are made is random. Since the possibility that the object appears in different MBR which have the same parents node is different, if we make the subnode who has the most possibility be traveled first, the time cost will be decreased in most of the cases. In some case, the possibility of a point belong to a rectangle will shows direct proportion with the size of the rectangle. But this conclusion is based on an assumption that the objects are symmetrically distributing in the area and this assumption is not always coming into existence. Now we found a more direct parameter to scale the possibility and made a little change on the structure of R-tree, to increase the possibility of founding the satisfying answer in the front sub trees. We names this structure probability based arranged R-tree (PBAR-tree).     

Integrating GIS Web services based on mediating architecture

The geographic information service is enabled by the advancements in general Web service technology and the focused efforts of the OGC in defining XML-based Web GIS service. Based on these models, this paper addresses the issue of services chaining,the process of combining or pipelining results from several interoperable GIS Web Services to create a customized solution. This paper presents a mediated chaining architecture in which a specific service takes responsibility for performing the process that describes a service chain. We designed the Spatial Information Process Language (SIPL) for dynamic modeling and describing the service chain, also a prototype of the Spatial Information Process Execution Engine (SIPEE) is implemented for executing processes written in SIPL. Discussion of measures to improve the functionality and performance of such system will be included.