Optimal Detection and Performance of Distributed Sensor Systems

Global optimization of a distributed sensor detection system withfusion is considered, where the fusion rule and local detectors aresolved to obtain overall optimal performance. This yields coupledequations for the local detectors and the fusion center.The detection performance of the distributed system with fusionis developed. The globally optimal system performance is comparedwith two suboptimal systems. Receiver operating characteristics(ROCs) are computed numerically for the problem of detecting aknown signal embedded in non-Gaussian noise.     

Distributed decision fusion in the presence of link failures

The problem of optimal data fusion involving detector unit communication link failures is considered. Two strategies for decision making in presence of link failures are examined and an optimal decision making scheme in the sense of the Neyman-Pearson (N-P) test is proposed. The performance of q+1 reliable links versus q reliable links are examined theoretically, as well as, numerically using the receiver operating characteristics (ROCs)     

Optimum multisensor fusion of correlated local decisions

A distributed detection system consisting of a number of local detectors and a fusion center is considered. Each detector makes a decision for the underlying binary hypothesis testing problem based on its own observation and transmits its decision to the fusion center where the global decision is derived. The local decision rules are assumed to be given, but the local decisions are correlated. The correlation is generally characterized by a finite number of conditional probabilities. The optimum decision fusion rule in the Neyman-Pearson sense is derived and analyzed. The performance of the distributed detection system versus the degree of correlation between the local decisions is analyzed for a correlation structure that can be indexed by a single parameter. System performance as well as the performance advantage of using a larger number of local detectors degrade as the degree of correlation between local decisions increases     

分布式IMA的网络分区方法及其实时性能分析

 针对分布式综合模块化航空电子(IMA)体系结构,在时间、空间分区以及带宽分区的基础上,提出了网络分区的概念,并建立了相应的网络模型、消息模型、流量模型及调度模型。利用网络演算方法,推导了航空电子混合消息集在网络分区下端到端(ETE)延迟的计算公式;搭建典型网络,通过理论计算对比了网络分区与带宽分区的实时性能。计算结果表明:网络分区下两条硬实时数据流的延迟较带宽分区分别降低了33.5%和74.2%;而弱硬实时与软实时数据流的延迟增加约30%。最后通过OPNET仿真对理论分析所得结果进行了验证,证明网络分区方法符合分布式IMA的分布式架构要求,并满足了系统混合关键性的需求。     

通信和测量受限条件下异构多UAV分布式协同目标跟踪方法

研究了通信和测量受限的异构多无人机(UAV)网络化分布式协同目标观测与跟踪问题.该分布式UAV系统采用长机一僚机异构型网络结构,以实现在电子静默和战术隐身条件下扩大探测和打击纵深.提出改进的一致性信息滤波(ICF)算法,实现通信和测量范围内各UAV节点的分布式信息融合.由于一致性算法的收敛性与网络拓扑结构的连通性密切相...     

新一代歼击机超机动飞行的动态逆控制

 根据反馈线性化理论, 讨论了神经网络自适应非线性动态逆控制设计。首先根据时标分离原则, 采用动态逆方法设计快回路和慢回路控制器; 其次提出基于模型逆的神经网络非线性直接自适应控制方案, 设计一种在线神经网络用于补偿模型逆误差。仿真表明, 该控制方案具有较好的自适应能力和鲁棒性。     

Asynchronous distributed detection

Binary parallel distributed-detection architectures employ a bank of local detectors to observe a common volume of surveillance, and form binary local decisions about the existence or nonexistence of a target in that volume. The local decisions are transmitted to a central detector, the data fusion center (DEC), which integrates them to a global target or no target decision. Most studies of distributed-detection systems assume that the local detectors are synchronized. In practice local decisions are made asynchronously and the DFC has to update its global decision continually. In this study the number of local decisions observed by the central detector within any observation period is Poisson distributed. An optimal fusion rule is developed and the sufficient statistic is shown to be a weighted sum of the local decisions collected by the DFC within the observation interval. The weights are functions of the individual local detector performance probabilities (i.e., probabilities of false alarm and detection). In this respect the decision rule is similar to the one developed by Chair and Varshney for the synchronized system. Unlike the Chair-Varshney rule, however, the DFC's decision threshold in the asynchronous system is time varying. Exact expressions and asymptotic approximations are developed for the detection performance with the optimal rule. These expressions allow performance prediction and assessment of tradeoffs in realistic decision fusion architectures which operate over modern communication networks     

Centralized and distributed multisensor integration withuncertainties in communication networks

Algorithms in which each sensor is represented in a local coordinate system and the communication networks between sensors have uncertainties are considered. The algorithms are general and can be applied to various integration tasks. The effects of the communication network uncertainties are minimized in the local estimation and central fusion processes. In the centralized multisensor integration, the local measurements and local measurement models are transferred to the central coordinate system and the optimal integration is obtained at the central process. In contrast, the local measurements, together with the previous central estimate transmitted from the communication network, are locally processed in the distributed multisensor integration algorithm. Because the distributed algorithm uses the communication networks twice, more errors are introduced, so that when the uncertainties are large, the centralized algorithm is preferred. Although the algorithms are developed in the three-dimensional coordinate system, with straightforward extension they can be applied to N-dimensional coordinate systems     

分布式网络技术在燃气轮机性能测试系统中的应用

分析了分布式网络系统及燃气轮机性能测试系统的结构特点,描述了基于系统级、子系统级和工作站级的分布式测试系统的3级结构模型.     

Distributed CFAR detection in homogeneous and nonhomogeneousbackgrounds

The performance of distributed constant false alarm rate (CFAR) detection with data fusion both in homogeneous and nonhomogeneous Gaussian backgrounds is analyzed. The ordered statistics (OS) CFAR detectors are employed as local detectors. With a Swerling type I target model, in the homogeneous background, the global probability of detection for a given fixed global probability of false alarm is maximized by optimizing both the threshold multipliers and the order numbers of the local OS-CFAR detectors. In the nonhomogeneous background with multiple targets or clutter edges, the performance of the detection system is analyzed and its performance is compared with the performance of the distributed cell-averaging (CA) CFAR detection system     

多级涡轮多工况气动优化设计研究

采用将准三维设计和多级局部优化联合的多级涡轮多工况气动优化设计流程对某三级航空发动机涡轮进行多级气动优化设计.优化联合采用人工神经网络和遗传算法对各列叶栅进行三维局部优化,流场计算采用全三维粘性流N-S方程求解.通过优化设计,改善了各列的性能,并对各列间参数进行了优化匹配,两种工况的总效率均提高1%,总流量基本不变,总体性能提高,达到设计要求.      

分布式实时飞行仿真中的联接技术

分布式仿真系统可采用的联接方式主要有物理共享内存总线、消息传递网络和复制共享内存网络三种。物理共享内存总线和消息传递网络在分布式实时仿真中存在技术上的不足．但它们之间具有一定的互补性．复制共享内存网络将它们两者的优点有机地结合起来．成为一种适用于实时系统分布式仿真的理想方式．文章对这些技术分别进行了阐述。最后，针对分布式飞行仿真的特殊要求．介绍了复制共享内存网络的具体应用。     

基于分布式管理架构的应用型网管系统的设计与研究

根据当前IT应用的普及情况,分析了大中型企业中网络资源管理存在的问题,研究了网管软件的相关技术并设计了一套符合当前应用需求的分布式管理架构的应用型网管系统。该系统不但可监测各类操作系统的性能,还可对数据库、WEB服务等应用服务器的性能进行监控。结合网管软件的发展动态,展示了该应用型网管系统的工程应用价值。     

某涡扇发动机分布式控制系统设计与总线性能

针对国内某型涡扇发动机,以该机目前采用的集中式FADEC为基础,依据地域分散原则,设计了一种发动机部分分布式控制系统结构,并对发动机控制系统中的传输信号进行了合理划分;对发动机采用分布式控制进行了总线通信需求分析;选择时间触发CAN总线作为发动机分布式控制系统通信总线,并进行了通信方案设计;利用TrueTime构建了分布式控制仿真系统,研究了网络时延、掉包对发动机性能的影响.研究表明:在250kbit/s和1Mbit/s带宽下,总线利用率分别为50%和12.34%,满足通信要求;250kbit/s带宽下所设计时间触发系统的网络诱导时延为12ms,高压转子转速上升时间延迟0.02s,而网络随机掉包使发动机响应明显变慢,设计时需要加以考虑.      

机载分布式异构网络通信中间件研究

在机载分布式异构网络中,系统间的通信面临着复杂的网络环境.为了实现高效、可靠、安全的信息传输,需要通信中间件的支持.以数据分发服务(DDS)为基础,对发布订阅模型进行研究,将不同网络间的通信映射为数据分发服务中的跨域通信,引入路由服务实现跨域通信,扩展DDS原有的传输插件,用以支持不同的网络,实现了机载分布式异构网络通信中间件.通过实验对跨网络通信的时间延迟进行了测试,结果表明,通信中间件能够适应机载分布式应用的要求.     

结构可靠度逐步逼近径向基神经网络响应面法

提出了逐步逼近径向基神经网络响应面法计算结构可靠度,这种数值方法较好地解决了结构功能函数非线性及结构随机变量非正态分布时采用结构可靠度指标度量结构可靠度存在误差的问题.经过多个数值试验表明,该算法迭代收敛迅速、计算准确性较高、应用过程简单.利用这种方法对含有多个随机变量的结构进行可靠性分析和设计,特别是当结构功能函数具有较强的非线性或结构随机变量分布具有较大的偏斜度时,具有一定的应用价值.      

分布式多处理机系统的结构及应用

本文简要阐述了分布式多处理机系统的三种基本硬件结构、功能、特点及其实现原理，为使该系统在民航等系统的应用和研究更加广泛，文中还对应给出了三种结构的应用实例，简要讨论了当今热门技术微计算机局部网络与本结构的区别及应用领域。     

多传感器决策融合系统中的决策空间优化划分研究

在假定各局部检测器的决策规则已经给定以及在Ｂｈａｔａｃｈａｒｙｙａ距离最大的意义下,对多传感器融合系统中的决策空间优化划分设计进行了研究。首先基于Ｂｈａｔａｃｈａｒｙｙａ距离准则,把对整个系统决策空间的优化划分解耦为分别对各局部检测器决策空间的优化划分;然后从理论上证明了这种划分设计在最大Ｂｈａｔａｃｈａｒｙｙａ距离意义下的最优性,以及这种基于最大Ｂｈａｔａｃｈａｒｙｙａ距离准则进行优化划分设计的合理性;最后,通过对瑞利起伏环境下信号检测融合问题的数值计算表明,本文方法的性能优于基于Ｊ－散度方法的性能。     

Networks of low-Earth orbit store-and-forward satellites

A slotted multiaccess protocol is proposed for networks of low-Earth orbit store-and-forward communications satellites. Networks of this type would provide communication between low cost geographically distributed Earth stations, and would be particularly attractive in areas where conventional terrestrial communications systems were not available. Applications of this type include data acquisition and remote process monitoring. The proposed protocol incorporates time division multiplexing (TDM) on the downlink, slotted Aloha with collision resolution on the uplink, and an automatic repeat request (ARQ) algorithm. Since the network connectivity is intermittent, analysis of networks of this type is difficult. Nevertheless, relationships among the performance parameters for a general network are deduced, and performance of three particular network configurations is studied via simulation