Systematic methods for knowledge acquisition and expert systemdevelopment [for combat aircraft]

Nine cooperating rule-based systems, collectively called AUTOCREW which were designed to automate functions and decisions associated with a combat aircraft's subsystems, are discussed. The organization of tasks within each system is described; performance metrics were developed to evaluate the workload of each rule base and to assess the cooperation between the rule bases. Simulation and comparative workload results for two mission scenarios are given. The scenarios are inbound surface-to-air-missile attack on the aircraft and pilot incapacitation. The methodology used to develop the AUTOCREW knowledge bases is summarized. Issues involved in designing the navigation sensor selection expert in AUTOCREW's NAVIGATOR knowledge base are discussed in detail. The performance of seven navigation systems aiding a medium-accuracy inertial navigation system (INS) was investigated using Kalman filter covariance analyses. A navigation sensor management (NSM) expert system was formulated from covariance simulation data using the analysis of variance (ANOVA) method and the ID3 algorithm     

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。     

贝叶斯假设理论检测发动机传感器故障

贝叶斯多重假设检验是将被检测传感器的M个可能状态,作相应M个假设H_i,其先验概率分别为P(H_i)(i=1,2,…,M),故障决策就是从给定观测量M,寻求H_j为真,由贝叶斯风险函数H_i(i=1,2,…,M,i≠j)个假设中的最小值确定最可能发生的假设H_l。      

飞行传感器的故障检测与识别

 飞行传感器是飞行控制和导航系统中的薄弱环节,它们的故障率一般是比较高的。为了提高系统的可靠性,对传感器的故障应能实时地检测和识别,并重构传感器所测量的信号(修正)。为此,在系统中常采用传感器的硬件余度和解析余度。本文介绍了飞行传感器硬件余度和解析余度的原理以及几种实用的余度方案,对解析余度中的统计决策原理和故障检测的鲁棒性问题也作了简单介绍。     

BIT技术在导航系统中的应用优势

介绍了BIT技术的定义、分类和关键技术,阐述了导航系统故障检测的特点,探讨了BIT技术在导航系统应用,能够增强导航系统内部各子系统故障诊断能力,信息融合能力,并为冗余设计和系统重构提供基础等方面的优势.     

Detection of interference/jamming and spoofing in a DGPS-aidedinertial system

Previous research at the Air Force Institute of Technology (AFIT) has resulted in the design of a differential Global Positioning System (DGPS) aided INS-based (inertial navigation system) precision landing system (PLS) capable of meeting the FAA precision requirements for instrument landings. The susceptibility of DGPS transmissions to both intentional and nonintentional interference/jamming and spoofing must be addressed before DGPS may be safely used as a major component of such a critical navigational device. This research applies multiple model adaptive estimation (MMAE) techniques to the problem of detecting and identifying interference/jamming and spoofing in the DGPS signal. Such an MMAE is composed of a bank of parallel filters, each hypothesizing a different failure status, along with an evaluation of the current probability of each hypothesis being correct, to form a probability-weighted average state estimate as an output. For interference/jamming degradation represented as increased measurement noise variance, simulation results show that, because of the good failure detection and isolation (FDI) performance using MMAE, the blended navigation performance is essentially that of a single extended Kalman filter (EKF) artificially informed of the actual interference noise variance. However, a standard MMAE is completely unable to detect spoofing failures (modeled as a bias or ramp offset signal directly added to the measurement). This work describes a moving-bank pseudoresidual MMAE (PRMMAE) to detect and identify such spoofing. Using the PRMMAE algorithm, spoofing is very effectively detected and isolated; the resulting navigation performance is equivalent to that of an EKF operating in an environment without spoofing     

Enhanced space integrated GPS/INS (SIGI)

Safe, reliable, and low cost space-based navigation is being provided with embedded INS/GPS systems such as the space integrated GPS/INS (SIGI). The SIGI is being used for various space vehicle applications such as launch vehicles, orbital vehicles, and re-entry vehicles. This paper describes current space vehicle navigation capabilities. The SIGI is being enhanced to provide additions to these existing capabilities with such items as higher processing and a commercial-off-the-shelf operating system. This will allow hosting of various software applications such as advanced navigation functions, flight control, guidance and vehicle management algorithms. The SIGI can host redundancy management functions by incorporating a cross channel data link card (CCDL) using a high speed firewire bus. The SIGI can then be used as a redundancy management platform which has application to current space vehicle avionics topologies incorporating distributed processing architectures     

An autonomous celestial navigation method for LEO satellite based on unscented Kalman filter and information fusion

A reliable and secure navigation system and assured autonomous capability of satellite are in high demand in case of emergencies in space. Celestial navigation is a fully autonomous navigation method for satellite. To near earth satellite, the earth direction is the most important measurement and the horizon sensing accuracy is the most important factor which effects celestial navigation accuracy. According to the mode of acquiring horizon measurement, satellite celestial navigation methods can be broadly classified into two approaches: directly sensing horizon using earth sensor and indirectly sensing horizon by observation of starlight atmospheric refraction. For these two methods are complementary to each other, a new Unscented Kalman Filter (UKF) based information fusion method is proposed here for hybriding them. Compared to the traditional celestial navigation method, this method can provide better navigation performance and higher reliability. The hardware-in-loop test results demonstrate the feasibility and effectiveness of this method, in most cases the accuracy is sufficient for near earth civilian satellite and moreover it can be used as a backup system to provide redundancy.     

容错多传感器组合导航系统发展综述

对容错组合导航系统的基本理论、联邦滤波器的设计方法、特点进行了分析；指出联邦滤波器在时间和空间上为组合导航系统的容错设计提供了条件；同时对组合导航系统故障诊断、故障隔离和系统重构方法进行了研究。     

采用序列概率比方法检测航空发动机传感器软故障

提出基于卡尔曼滤波和序列概率比方法进行某型涡扇发动机控制系统传感器软故障检测新方法.研究了采用修正的序列概率比方法处理滤波残差,检测传感器软故障;并将该方法与残差加权二乘算法WSSR(Weighted Sum of Squared Residual)检测传感器软故障过程进行了对比.仿真结果表明,序列概率比方法较WSSR法所需决策时间短,适合于航空发动机传感器软故障检测.      

基于部件跟踪滤波器的解析余度技术

研究一种以发动机部件跟踪滤波器(CTF)为基础的解析余度技术, 它将CTF与故障检测、隔离和适应逻辑进行了有效的综合, 以改进发动机数控系统的可靠性。仿真表明, 本文所设计的解析余度技术, 在传感器无故障时, 机载模型能正确跟踪发动机的变化。当传感器发生故障时, 在不损坏机载模型的情况下, 又能及时、有效地进行硬、软故障的检测、隔离与适应。      

卫星-惯性-星光最优组合导航系统在航天飞机导航中的应用

 文中对航天飞机星光-惯性导航系统进行了简要分析从最优系统组成原理、余度管理方法、系统性能分析等方面研究了卫星-惯性-星光组合导航系统的概念设计。     

INS/GPS组合导航系统故障检测问题研究

提出了一种新的故障检测方案。该方案由卡尔曼滤波 ,得到新息序列 ,利用大数定律对新息序列的稳定性进行检验 ,来判别系统是否出现了故障。同时提出了故障状态下卡尔曼滤波的修正算法。数值仿真结果表明 ,该方法能有效地检测出 INS/GPS组合导航系统的故障 ,保证了 INS/GPS组合导航系统的安全性和可靠性     

采用一组卡尔曼滤波器检测发动机传感器故障

在发动机全功能数字电子控制系统中,提高传感器工作的可靠性是十分重要的,除了不断对传感器本身的性能加以改进提高外,现在广泛地采用了余度技术。近二十年来对解析余度(Analyt ical Redundancy)进行了广泛的研究,解析余度(AR)方法是基于各状态变量之间存在的解析关系,在系统可观条件下,利用无故障的输出测量值去估计(构造)已故障传感器正常工作状态时的输出信息,从而实现对故障的检测、隔离与重构,保证控制系统具有预定的控制性能。      

X-33 redundancy management system

The X-33 is an unmanned advanced technology demonstrator with a mission to validate new technologies for the next generation of Reusable Launch Vehicles. Various system redundancies are designed in the X-33 to enhance the probability of successfully completing its mission in the event of faults and failures during flight. One such redundant system is the Vehicle and Mission Computer that controls the X-33 ea, and manages the avionics subsystems. Historically, redundancy management and applications such as flight control and vehicle management tended to be highly coupled. One of the technologies that the X-33 will demonstrate is the Redundancy Management System (RMS) that uncouples the applications from the redundancy management details, in the same way that real-time operating systems have uncoupled applications from task scheduling, communication and synchronization details     

基于多模态感知与融合的无人车韧性导航系统

针对野外复杂环境下的无人车自主导航需要,建立了一种基于多源融合定位、语义建图与运动规划的智能导航系统.首先,针对IMU、轮式里程计、视觉SLAM与激光雷达SLAM等测量子系统,设计了误差状态扩展卡尔曼滤波器进行融合定位.其次,基于改进的CNN语义分割网络生成环境的语义图像,与3D激光雷达点云融合,并使用最大概率更新算法构建语义3D地图.接着,在语义和几何信息投影获得可通行性代价的基础上,提出了一种语义动态窗口的局部路径规划方法.最后,将以上感知、定位与规划方法整合成完整的智能导航系统,在城市与野外典型场景的测试中,相对定位误差小于0.4％D,具备一定的韧性导航定位和智能感知规划能力.     

基于自联想网络的发动机传感器解析余度技术

本文提出了一种基于自联想神经网络的传感器解析余度技术。在这种网络中,冗余传感器的信息被压缩、重组进入网络的第一部分,网络的第二部分将压缩信息恢复出来。基于数据融合原理,若一个传感器发生故障,其它传感器仍可提供足够的信息代替发生故障的传感器。理论分析和用于涡轴发动机的仿真结果表明,这种特殊结构的自联想网络具有良好的过滤噪声和故障信号的作用,特别适合于用作不易建模的复杂对象的传感器信号重构     

基于遍历性的组合导航系统故障检测方法研究

理想情况下,基于卡尔曼滤波的组合导航系统在无故障时的滤波残差为白噪声,故障时通常用2χ法来检测,但用这种方法检测往往具有较大的虚警。因此,针对无故障时卡尔曼滤波器的滤波残差是白噪声这一特点,提出了一种新的故障检测方法来判断系统是否发生了故障,在应用时大大降低了虚警,取得了较好的效果。     

Optimum Integration of Aircraft Navigation Systems

A current problem in aircraft navigation is determining how to effect alow cost navigation system consistent with required mission operationswhich will render a high degree of accuracy and reliability. One wayto achieve this is through optimum integration of equipment,subsystems, and computer mechanizations. Consistent with this approach,the overall objectives of this paper are to show the advantages of anoptimally integrated aircraft navigation system, and to illustrate howto effect a low cost navigation system with high accuracy performance.An integrated aircraft navigation system employing a Kalman optimumestimation filter is configured and analyzed in detail. The results ofthe analysis clearly indicate how to achieve high accuracy performanceusing low cost subsystems; namely, via optimum systems integration.     

航空发动机控制系统传感器FDIA系统仿真

基于卡尔曼滤波器组,建立了航空发动机控制系统传感器故障诊断系统,实现了对单个传感器故障的检测、隔离与重构(FDIA),确保了发动机控制系统即使在传感器故障发生的情况下,依然能安全可靠地工作.同时利用Simulink建立一个通用的发动机传感器故障诊断仿真平台,在此仿真平台上,对故障的诊断进行仿真验证,并分析了测量噪声对故障诊断系统性能的影响,为发动机在线传感器故障诊断系统的实现提供理论依据.