基于模糊贝叶斯网的空战传感器资源管理方法

空战中目标状态信息的不确定性、目标与我机相对态势是影响机载传感器资源分配问题的重要影响因素.针对此问题,提出一种基于模糊贝叶斯网(FBN)的空战传感器资源管理方法,以空战传感器资源管理中涉及的影响因素因果关系作为建网依据,将目标信息增量、目标威胁、飞行员指令作为证据变量驱动网络进行概率推理,从而获取空战传感器资源的分配结果.仿真结果表明,与传统方法相比,方法的自适应变间隔采样策略能够根据目标威胁及飞行员指令影响,管理空战态势不同阶段的传感器资源以满足空战作战任务需求.     

导弹集群协同作战任务规划系统

以领弹/攻击弹等新概念作战方式为例,讨论基于C4ISR系统下的导弹集群协同作战的总体框架,对信息融合系统、态势评估系统、任务规划系统、战毁评估系统及数据链系统等进行了分析,并对任务规划的主要算法,如A*,D*,Voronoi图法等进行了分析比较,最后设计了任务规划系统的硬件体系框架和软件结构模块.     

Smart sensor Web: tactical battlefield visualization using sensor fusion

Smart sensor Web (SSW) is a recent DUSD (S&T) initiative inspired by extraordinary technological advances in sensors and microelectronics and by the emergence of the Internet as a real-time communication tool. The overall vision for SSW is an intelligent, Web-centric distribution and fusion of sensor information that provides greatly enhanced situational awareness, on demand, to warfighters at lower echelons. Emphasis is on multi-sensor fusion of large arrays of local sensors, joined with other assets, to provide real-time imagery, weather, targeting information, mission planning, and simulations for military operations on land, sea, and air. This paper gives an overview of this new initiative, highlights some of the technology challenges in sensor/information fusion, and presents a program approach for near-term demonstrations and long-term solutions, involving the DoD, National Labs, commercial industry, and academia.     

Sensor fusion for intelligent alarm analysis

The purpose of an intelligent alarm analysis system is to provide complete and manageable information to a central alarm station operator by applying alarm processing and fusion techniques to sensor information. This paper discusses the sensor fusion approach taken to perform intelligent alarm analysis for the Advanced Exterior Sensor (AES). The AES is an intrusion detection and assessment system designed for wide-area coverage, quick deployment, low false/nuisance alarm operation, and immediate visual assessment. It combines three sensor technologies (visible, infrared, and millimeter wave radar) collocated on a compact and portable remote sensor module. The remote sensor module rotates at a rate of 1 revolution per second to detect and track motion and provide assessment in a continuous 360° field-of-regard. Sensor fusion techniques are used to correlate and integrate the track data from these three sensors into a single track for operator observation. Additional inputs to the fusion process include environmental data, knowledge of sensor performance under certain weather conditions, sensor priority, and recent operator feedback. A confidence value is assigned to the track as a result of the fusion process. This helps to reduce nuisance alarms and to increase operator confidence in the system while reducing the workload of the operator     

Expert Systems in the Fighter of the 1990s

In the Advanced Tactical Fighter (ATF) to be deployed in the 1990s, the role of expert systems will enhance mission success. This paper discusses the utilization of two expert systems for handling multisensor data fusion and situation assessment. In multisensor data fusion, each sensor operates over a different region of the surveillance volume asynchronously and provides different measurements. In some instances, more than one sensor may yield the same measurement but with a different measurement accuracy. In this regard, the paper describes, in layman's terms, a system block diagram for processing the autonomous sensor track files and the possible need for a ``smart' fusion processor. This expert system is shown to manage the sensor outputs in both the temporal and spatial domains to maximize target identification confidence as well as kinematic state vector accuracy. The paper delineates the features needed by the fusion expert in order to assign a quality factor to each composite track file entry. A second expert system uses the output from fusion and other mission-related data to formulate the best picture of the surveillance volume at hand. This second expert system will show how historical data and real-time sensor data are merged for purposes of display parameters to the pilot, weapon cueing, countermeasures response management, and feedback to the fusion expert processor for individual sensor communication and data collection direction. The paper concludes with a tabular summary of the subprocesses of which these two expert systems may consist.     

Smart Sensor Web: Web-based exploitation of sensor fusion forvisualization of the tactical battlefield

Smart Sensor Web (SSW) is a recent DUSD (S&T) initiative inspired by extraordinary technological advances in sensors and microelectronics and by the emergence of the Internet as a real time communication tool. The overall vision for SSW is an intelligent, Web-centric distribution and fusion of sensor information that provides greatly enhanced situational awareness, on demand, to warfighters at lower echelons. Emphasis is on multi-sensor fusion of large arrays of local sensors, joined with other assets, to provide real-time imagery, weather, targeting information, mission planning, and simulations for military operations on land, sea, and air. This paper gives an overview of this new initiative, highlights some of the technology challenges in sensor/information Fusion, and presents a program approach for near-term demonstrations and long-term solutions, involving the DoD, National Labs, commercial industry, and academia     

基于小生境遗传算法的分布式OS-CFAR检测系统优化与性能分析

 利用小生境遗传算法,对不同检测窗长度和检测信噪比的三传感器分布式 OS-CFAR检测系统进行了优化设计,给出了一组针对不同检测环境与融合方式的搜索结果。分析表明,对于非一致环境下分布式 OS-CFAR检测系统,小生境遗传算法是一种良好的优化算法。利用搜索结果,研究了不同融合方式下环境变化对分布式 OS-CFAR检测系统的性能影响,结果表明,“或”融合对检测环境的非一致变化具有较强的鲁棒性,而“3选2”融合和“与”融合对检测环境的变化比较敏感。     

基于改进D-S证据理论的航空发动机转子故障决策融合诊断研究

针对单一传感器的测量信息难以准确、全面地反映航空发动机转子、轴承和齿轮的工作状况,进而造成振动故障诊断难度大的问题,提出安装多个振动传感器组成传感器网络,建立基于多传感器信息的发动机转子故障决策融合诊断系统。由于多传感器系统不可避免地会存在各传感器信息不一致、信息冲突的情形,因此针对该融合诊断系统的信号测量、信息预处理、特征提取、故障诊断及决策融合5个环节,重点研究了决策融合环节的Dempster-Shafer（D-S）证据决策融合方法存在的冲突证据融合失效问题。通过分析原因,从避免“一票否决”现象和证据加权平均两个方面进行改进,提出了改进D-S证据融合方法,并应用于航空发动机转子的模拟故障决策融合诊断中。结果表明基于D-S证据理论对3个传感器的单一诊断结果进行决策融合,能得到比任一单个传感器更准确、可靠的结果;而改进D-S证据融合方法由于能在一定程度上克服冲突证据融合带来的失效问题,且能同时兼顾处理好非冲突证据的融合,故其对于证据冲突和非冲突情形都取得了较好的融合效果,因此总的分类正确率要高于常规D-S算法和PCR5算法。     

飞机线束数字化制造系统研究与开发

针对某线束企业目前线束工艺缺乏有效校验、设计效率低、生产过程管理和技术状态控制薄弱的现状,在分析航空线束工艺设计和制造现状的基础上提出建立数字化制造系统,利用信息技术为工艺设计提供智能辅助支持,实现对生产过程的显性化管理和对技术状态的有效控制。通过建立数字化制造系统,在提高线束工艺设计的效率、加强对工艺文件的技术状态管理、提升对线束生产过程的控制能力等方面取得了明显的进步,并通过实例验证系统的实用性和有效性。     

A multi-rate sensor fusion approach using information filters for estimating aero-engine performance degradation

Gas-path performance estimation plays an important role in aero-engine health management, and Kalman Filter(KF) is a well-known technique to estimate performance degradation. In previous studies, it is assumed that different kinds of sensors are with the same sampling rate, and they are used for state estimation by the KF simultaneously. However, it is hard to achieve state estimation using various kinds of sensor measurements at the same sampling rate due to a complex network and physical characteristic differences between sensors, especially in an advanced multisensor architecture. For this purpose, a multi-rate sensor fusion using the information filtering approach is proposed based on the square-root cubature rule, which is called Multi-rate Squareroot Cubature Information Filter(MSCIF) to track engine performance degradation. Soft measurement synchronization of the MSCIF is designed to provide a sensor fusion condition for multiple sampling rates of measurement, and a fault sensor is isolated by maximum likelihood validation before state estimation. The contribution of this paper is to supply a novel multi-rate informationfilter approach for sensor fault tolerant health estimation of an aero-engine in a multi-sensor system. Tests are conducted for aero-engine performance degradation estimation with multiple sampling rates of sensor measurement on both digital simulation and semi-physical experiment.Experimental results illustrate the superiority of the proposed algorithm in terms of degradation estimation accuracy and robustness to sensor failure in a multi-sensor system.     

计算机辅助计划管理和决策总体设计

 介绍一种新机研制计划管理和决策支持系统的总体设计方案及其实现的具体措施。详细介绍了几个主要模块的设计思想。     

基于喘振信息数据融合的发动机温度传感器

针对热电偶（阻）型温度传感器呈现较强的惯性，提出一种基于矩阵奇异分解的传感器数据融合方法，将喘振信息与温度传感器输出信号相融合，分别消除了发动机进口温度T1约1．2％和涡轮后燃气温度L约0．8％的静态误差；同时，还提出了利用喘振信息消除温度传感器动态误差的技术，补偿了热电偶（阻）的惯性延迟。实验和仿真结果表明，该数据融合方法和动态补偿技术不仅算法简单有效，而且温度补偿准确，提高了发动机电子调节器工作的可靠件．     

Fuzzy logic applications to multisensor-multitarget correlation

A consistent tactical picture requires data fusion technology to combine and propagate information received from diverse objects and usually vague situations. The information may be contained in two types of data; numerical data received from sensor measurements, and linguistic data obtained from human operators and domain experts. In real world situations, the numerical data may be noisy, inconsistent, and incomplete, and the linguistic information is imprecise and vague. To deal with these two types of data simultaneously, fuzzy sets and fuzzy logic provide a methodology to obtain an approximate but consistent tactical picture in a timely manner for very complex or ill-defined engineering problems. A functional paradigm for fuzzy data fusion is presented. It consists of four basic elements: (1) fuzzification of crisp elements, (2) fuzzy knowledge base derived from numerical input/output relations and humans, (3) fuzzy inference mechanism based on a class of fuzzy logic, (4) defuzzification of fuzzy outputs into crisp outputs for use by a plant. For real-time practical systems, the on-line determination of a fuzzy membership function from a given set of crisp inputs is vital. To this end, a methodology for estimating an optimal membership function from crisp input data has been implemented. This is based on the possibility/probability consistency principle as proposed by L.A. Zadeh. A relationship between the fuzzy membership function and the confidence level of statistical input data has been developed and it serves as a design parameter for fuzzification. This technique has been applied to a two-dimensional multisensor-multitarget tracking system. Fuzzy system performance evaluations have been presented. With simulated data in the laboratory environment, the simulation has been performed to evaluate the Mission Avionics Sensor Synergism (MASS) Systems. These results show better performance for the data correlation function using the fuzzy logic techniques.     

基于证据理论的模糊信息融合及其在目标识别中的应用

信息融合系统中的不确定性信息常常表现为模糊性和随机性信息。提出了一种在证据理论框架下实现模糊信息融合的方法。该方法首先基于随机集理论刻画模糊信息的隶属函数,获得了模糊观测下具有概然特性的似然函数,该似然函数表示在收集的模糊信息下确定为某一目标的可能性,在数值上表示了传感器信息对某一命题支持的程度,利用似然函数确定传感器输出的基本概率指派,最后利用Dempster-Shafer组合规则实现多传感器信息融合。     

Optimal Decision Fusion in Multiple Sensor Systems

The problem of optimal data fusion in the sense of the Neyman-pearson (N-P) test in a centralized fusion center is considered. The fusion center receives data from various distributed sensors. Each sensor implements a N-P test individually and independently of the other sensors. Due to limitations in channel capacity, the sensors transmit their decision instead of raw data. In addition to their decisions, the sensors may transmit one or more bits of quality information. The optimal, in the N-P sense, decision scheme at the fusion center is derived and it is seen that an improvement in the performance of the system beyond that of the most reliable sensor is feasible, even without quality information, for a system of three or more sensors. If quality information bits are also available at the fusion center, the performance of the distributed decision scheme is comparable to that of the centralized N-P test. Several examples are provided and an algorithm for adjusting the threshold level at the fusion center is provided.     

Expert System Applications to the Cockpit of the '90s

There is a strong requirement for a new generation of avionics systems with a more integrated hardware and software structure. This integrated avionics system will use significant increases in computer automation with more innovative signal processing, sensor fusion and expert system software to reduce pilot workload, while improving total system performance and reliability. Expert system software packages will be implemented within the core architecture of these next generation integrated avionics systems to assist the pilot. The expert systems will consider the pertinent information available from the ``sensor' subsystems to assess the current situation. The expert systems then consult their knowledge base and rule base software structures to determine alternative reactions to the perceived situation. Then pending upon the critical of the function, situation and reaction, the expert system could either execute the most favorable reaction or display the suggested alternative courses of action to the pilot. This paper addresses the requirement, the enabling technologies and the potential structure of this next generation of avionics. It concludes with two examples of the potential of future avionics expert systems. The two examples are 1) A Navigation and Route Planning Expert and 2) A Threat Assessment and Threat Reaction Expert. Significant things are happening in technology at an accelerating pace that enable the development of this new generation of avionics.     

Explicit solutions for some simple decentralized detection problems

A decentralized detection problem is considered in which a number of identical sensors transmit a finite-valued function of their observations to a fusion center which makes a final decision on one of M alternative hypotheses. The authors consider the case in which the number of sensors is large, and they derive (asymptotically) optimal rules for determining the messages of the sensors when the observations are generated from a simple and symmetrical set of discrete distributions. They also consider the tradeoff between the number of sensors and the communication rate of each sensor when there is a constraint on the total communication rate from the sensors to the fusion center. The results suggest that it is preferable to have several independent sensors transmitting low-rate (coarse) information instead of a few sensors transmitting high-rate (very detailed) information. They also suggest that an M-ary hypothesis testing problem can be viewed as a collection of M(M-1)/2 binary hypothesis testing problems. From this point of view the most useful messages (decision rules) are those that provide information to the fusion center that is relevant to the largest possible numbers of these binary hypothesis testing problems     

信息融合技术在组合导航系统中的应用

提出了无线电近程导航系统(RSRN S)与IN S/GPS的综合过程,探讨了RSRN S和IN S/GPS综合应用过程中的信息融合技术问题。采用GPS伪距、伪距率以及无线电近程导航定位与IN S组合,建立了卡尔曼滤波方程,设计了飞行轨迹,对相关的信息融合技术进行了初步讨论,并给出了惯性元件精度较低时组合系统的仿真输出。这种组合导航方案可以充分利用各种导航传感器的信息,有效提高导航系统的精度。     

综合航电设备多传感器多级数据融合的敌我属性估计

介绍了C^4 ISR系统中多传感器数据融合的特点和一种空战融合模式,结合实例说明了多传感器各自对目标信息的测量结果进行融合处理,推导了单传感器和多传感器未知命题的周期融合的可信度分配,并根据概率分布函数求出我机和敌机的置信度和拟信度,进行了验证和分析。分析表明,多传感器数据融合可以较全面准确地识别空中目标,达到对目标属性的准确估计。