Optimal Data Fusion in Multiple Sensor Detection Systems

There is an increasing interest in employing multiple sensors for surveillance and communications. Some of the motivating factors are reliability, survivability, increase in the number of targets under consideration, and increase in required coverage. Tenney and Sandell have recently treated the Bayesian detection problem with distributed sensors. They did not consider the design of data fusion algorithms. We present an optimum data fusion structure given the detectors. Individual decisions are weighted according to the reliability of the detector and then a threshold comparison is performed to obtain the global decision.     

Fault Detection in Dynamic Systems via Decision Fusion

Due to the growing demands for system reliability and availability of large amounts of data, efficient fault detection techniques for dynamic systems are desired. In this paper, we consider fault detection in dynamic systems monitored by multiple sensors. Normal and faulty behaviors can be modeled as two hypotheses. Due to communication constraints, it is assumed that sensors can only send binary data to the fusion center. Under the assumption of independent and identically distributed (1ID) observations, we propose a distributed fault detection algorithm, including local detector design and decision fusion rule design, based on state estimation via particle filtering. Illustrative examples are presented to demonstrate the effectiveness of our approach.     

多传感器数据融合中的数据配准研究

数据配准是多传感器数据融合的先期处理过程。本文在研究了传统的最小二乘算法的基础上，提出了基于三维坐标系中的极大似然配准算法，解决了最小二乘配准算法对于传感器相距较远时无法解决的问题。最后通过计算机仿真证明了此算法的有效性。     

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.     

航空发动机部件性能参数融合预测

为了改善目前单独采用基于模型和数据驱动的部件健康参数预测精度,提高数据驱动方法的故障诊断的泛化能力,提出一种自调整决策融合机制,对航空发动机部件性能蜕化在连续蜕化空间进行融合诊断。传感器测量值同时输入到机载自适应模型和数据驱动的诊断模块中,分别利用卡尔曼滤波算法和自适应遗传算法优化的支持向量回归机(AGA-SVR)对主要部件性能进行预测,再利用自调整决策权重的量子粒子群寻优(QPSO)进行决策级融合诊断。以某型涡扇发动机为对象进行气路部件蜕化的仿真研究表明,与单独使用基于模型和数据驱动的诊断方法相比,采用决策融合机制有效地提高了部件故障诊断精度。     

决策融合功能与体系结构研究

介绍了决策融合系统的概念、功能范围,并详细探讨了决策融合结构模型及实现方法。     

Estimation of Phase Difference in Multiple Sensor Arrays

The likelihood functional for estimating parameter differences in coherent multiple-sensor receivers is developed assuming Gaussian statistics on both signal and noise. The development relies on a matrix formulation and a subsequent factorization of a parameter constraint matrix from the signal matrix. A two-antenna phase-difference radar example is presented for cases of uncorrelated and antenna-correlated noise.     

低成本无人机传感器配置方案的设计与仿真

以降低无人机制造成本为目标,在保证无人机安全自主飞行的前提下,提出了基于GPS和垂直陀螺、GPS和三轴速率陀螺及GPS和低成本惯性组件的3种低成本传感器配置方案,并针对每种方案在工程中遇到的问题,采用低通滤波、高通滤波和卡尔曼滤波等数据融合算法予以解决,最后在MATLAB平台下对每种传感器配置方案进行仿真验证.研究对比表明,对于自身稳定性较好的无人机,该3种传感器配置方案均能够实现姿态控制、高度控制、滚转控制以及航迹控制.     

基于D-S证据理论的目标属性辨识研究

D—S证据组合理论已经成为不确定性推理的一种重要方法，基于该理论的多传感器决策层信息融合已得到广泛应用。本文在简要介绍D—S证据组合理论框架基础上，阐述了基于D—S证据组合理论的信息融合一般步骤及决策层判决方法；分析了发生证据严重冲突时，Dempster证据组合规则出现的不可靠和不合理的本质原因，介绍了针对D—S证据组合规则进行修正的几种主要方法；最后，提出了需要继续深入探讨的问题。     

基于运动目标的机载多源传感器数据融合算法

在机载信息融合领域,针对复杂的战场态势环境对机载多源传感器造成的不利影响,提出了一种基于运动目标的机载多源传感器数据融合算法,包括误差估计与补偿、目标关联、估计融合3个部分。采用最小均方误差参数估计方法从数值不变的系统误差中,定量获取量测偏差的确定性部分再通过模糊隶属度函数建立关联矩阵作为目标关联的依据,以最小隶属关系为约束,利用拍卖算法求得多目标关联的最优匹配方案,最后通过IMM 自适应滤波方法,将误差配准与目标航迹估计整合进行,有效提高滤波的精度。仿真结果表明,经过上述算法处理后的融合目标精度高于任意单传感器目标探测精度。     

一种事件驱动型无线传感器网络的数据编码及融合算法

基于事件驱动的区域监测是无线传感器网络的一类典型应用,该网络中包括两种类型的数据,分别为对网络状态进行监控的周期性监测数据和事件发生时应传送的事件消息.基于簇结构,利用簇头和簇成员两种角色的节点,分别针对上述两种类型的数据提出不同的编码方式和对应的融合机制,同时详细分析了该编码方法和融合机制的优缺点.     

Benefits and challenges of Integrated Sensor Systems

Projection of avionics system costs shows unacceptable escalation as a percentage of flyaway cost. Time sharing of RF modules between Radar, EW and CNI offers savings. The Air Forces' PAVE PACE program defined the benefits and initial architecture approaches. From this, an optimum Integrated Sensor System (ISS) design was defined that reduces the life cycle cost of the fleet of vehicles using the common modules. The ISS program will design, build and test modules to prove the approach. Challenges to overcome include system complexity, real time control, test and calibration, and diagnostics. The most stressing requirements were determined by analyzing requirements for Radar, EW and CNI. Open interface specifications and module partitioning were developed that can meet all the requirements     

多平台信息融合与智能化传感器管理技术综述

多平台信息融合与智能化多传感器管理是多平台协同作战能力和网络中心战的关键技术之一。本文主要介绍了多平台信息融合与智能化传感器管理技术的概念、军事需求及发展趋势;阐述了多平台信息融合与智能化多传感器管理系统的体系结构、功能性能要求及所涉及的关键技术。     

基于损伤标尺的电子设备预测维修决策优化

基于故障预测信息进行维修决策是预测性维修等新型维修模式的主要特征之一,可以有效提高装备使用可用度、降低寿命周期费用。面向单部件电子系统,针对故障预测中的损伤标尺方法,在完美换件维修的假设下,以单位时间成本、平均使用可用度与平均效费比为指标,提出了一种预测维修决策优化模型。对于与外场可更换单元(LRU)寿命独立的损伤标尺,选择预测距离与Weibull分布的形状参数为决策变量,对于与LRU寿命相关的损伤标尺,选择累积损伤因子与随机标准差为决策变量,应用Monte Carlo方法仿真研究了各个决策变量对维修效能指标的影响。结果表明:应用与LRU寿命独立损伤标尺的预测维修策略的效果优于事后维修策略,但劣于年龄换件策略,揭示了该方法的本质特性;应用与LRU寿命相关损伤标尺的预测维修策略的效果在一定条件下优于年龄换件策略。最后分析了维修决策的优选方法。     

武器装备采办模糊多属性群体决策方法

针对武器装备采办的模糊多属性群体决策问题,文章假设定性属性指标都是梯形模糊数状态,运用模糊数学理论和广义海明权距离,提出了一种定性判断和定量分析相结合的武器装备采办模糊多属性群体决策方法,并给出了一个方法应用及求解计算的实际例子,算例结果证明了方法有效。     

Low-Sensitivity Design of Optimal Linear Control Systems

The quadratic performance criterion, linear optimal control problem is reformulated to incorporate constraints on trajectory sensitivity. The open-loop solution is obtained for sensitivity functions defined for small plant-parameter variations. This approach has provided a beginning for other attempts to solve the low-sensitivity analytical design problem, as reported in the references.     

电容成像传感器优化设计及其试验研究

为了减小电容层析成像(Electrical Capacitance Tomography,ECT)传感器相邻极板间耦合电容引起电容测量时的噪声值,设计了差分电极传感器系统并对差分电极与测量电极距离进行参数优化。实验系统采用现场可编程门阵列(Field Programmable Gate Array,FPGA)直接数字频率生成模块生成数字量的正弦激励信号,通过D/A转化为正负交流信号分别对测量电极和差分电极进行激励。差分电极与测量电极到管道中点的距离比例约1:1.2时传感器灵敏度最佳,仿真图像误差降低至0.23,图像相关系数提升到0.84;实验中空场时的系统平均信噪比比普通传感器提升了5.10dB,满场时的系统平均信噪比提升了4.50dB,相邻电极对的静止电容减少至38%,而电容变化占用最多测量值,即62%。差分电极传感器系统经过电极之间距离的优化设计,传感器系统性能得到提升,通过实验验证其可行性,并且能够应用在滑油监测。     

多传感器数据融合技术飞行试验方法研究

多传感器数据融合技术正在逐步应用到飞行器航电系统中,新的设计理念和制造技术的出现也给航电系统的飞行试验带来了难度和挑战。本文分析了数据融合技术的作战应用,在此基础上,建立了数据融合技术评价指标,设计了基本的试飞方法,为将来先进航电系统的试飞建立了理论基础。