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     

Bayesian and Dempster-Shafer target identification for radarsurveillance

This paper considers the problem of target track identification in a radar surveillance system. To build a target identifier alongside a tracker, four features which are available for real-time processing in an air surveillance system are used here: target identity (TID) from a friend-and-foe identification (IFF) system, elevation measurement from the radar, target speed, and acceleration estimated by a tracker. These four features are combined to classify air targets into five different air target categories: friendly commercial, friendly military, hostile commercial (or unknown airline), hostile military, and false targets (clutter). Two popular statistic-based techniques, namely, the Bayesian and Dempster-Shafer methods, are applied to develop radar target identification algorithms for our application. Real-life as well as simulated air surveillance radar data are used to evaluate the practicality and effectiveness of this track identification approach in a radar surveillance system     

Recursive mode star identification algorithms

Star identification can be accomplished by several different available algorithms that identify the stars observed by a star tracker. However, efficiency and reliability remain key issues and the availability of new active pixel cameras requires new approaches. Two novel algorithms for recursive mode star identification are presented here. The first approach is derived by the spherical polygon search (SP-search) algorithm, it was used to access all the cataloged stars observed by the sensor field-of-view (FOV) and recursively add/remove candidate cataloged stars according to the predicted image motion induced by camera attitude dynamics. Star identification is then accomplished by a star pattern matching technique which identifies the observed stars in the reference catalog. The second method uses star neighborhood information and a catalog neighborhood pointer matrix to access the star catalog. In the recursive star identification process, and under the assumption of "slow" attitude dynamics, only the stars in the neighborhood of previously identified stars are considered for star identification in the succeeding frames. Numerical tests are performed to validate the absolute and relative efficiency of the proposed methods.     

Identification of a discrete-time dynamical system

A novel generalized minimum variance (GMV) system identification algorithm is developed, and its performance is gauged against the established generalized least squares (GLS) estimation algorithm. The emphasis of the proposed GMV algorithm is on the rigorous treatment of measurement noise for dynamical system identification. A careful analysis of the measurement situation on hand yields a novel fixed-point calculation-based parameter estimation algorithm. The novel and established algorithms are compared in carefully performed and reproducible experiments which include measurement noise. Differences are apparent under small (measurement) sample operation, whereas under sufficient excitation, the algorithms produce statistically similar results     

一种圆锥运动条件下的等效旋转矢量算法研究

传统旋转矢量姿态算法一般采用陀螺的角增量信号来构造积分算法,当应用于输出为角速率的光纤陀螺捷联系统时,通过角速率提取角增量,算法会损失一定精度。提出了一种以陀螺角速率信号与角增量信号同时作为输入的改进旋转矢量姿态算法,进一步补偿了圆锥误差,提高了计算精度。仿真结果表明,该算法与传统二子样算法相比较,计算量相当,姿态精度、速度精度、位置精度有大幅度的提升。     

不稳定飞机气动参数辨识的一种实用方法

地是飞行器气动参数辨识最广泛采用的一种方法。但对于气动高度不稳定的飞机，辨识算法往往因状态方程组和灵敏度方程组积分发散而无法进行。为克服这一数值困难，将方程解耦技术引入输出误差法，发展了高度不稳定飞机气动参数辨识的一种实用方法－－基于方程解耦的误差法。并对某鸭式布局飞机的纵向劝仿真数据进行了辨识仿真计算，计算结果证实了所述方法的有效性。     

信息融合图像识别算法及其在三维飞机图像识别中的应用研究

将D S证据推理与不变矩理论相结合,提出了信息融合图像识别算法,并应用于三维飞机图像的识别。构造了基本置信指派函数,建立了分类规则,针对Dempster组合规则只适用于高置信度、低冲突性的情况,应用可解决证据冲突的加权分配冲突法及吸收法,完成了三维飞机图像识别的仿真,比较了3种组合规则的识别效果,结果表明吸收法识别率最高。     

基于D—S证据理论的航空发动机故障诊断

航空发动机滑油中舍有摩擦副产生的磨损微粒。通过滑油介质中所含磨损微粒中元素的分析．运用Dempster-Shafer证据融合诊断方法,对航空发动机的磨损状态等进行有效的诊断,确定发动机的磨损程度,以及发动机的磨损部位,从而可对发动机的故障排除作参考。在融合过程中提出了先对每个元素的磨损量和磨损率进行融合,再总体融合的方法。针对Dempster—Sharer证据融合的局限,应用了两种改进的融合方法,并进行比较。实例表明,Dempster—Shafer证据融合是一种有效的航空发动机滑油磨损的故障诊断方法。     

民用航空发动机状态监视和故障诊断系统研究

北京飞机维修工程公司、北京航空航天大学、中国民航学院、东方航空公司联合发展了用计算机进行发动机状态监视和故障诊断的系统EMD, 已在国内最大的两家航空公司试用成功。对B767、B747、A310共13架大型客机的40台发动机进行状态监视和故障诊断, 取得良好的经济效益。      

Hybrid partition- and network-level scheduling design for distributed integrated modular avionics systems

Distributed Integrated Modular Avionics (DIMA) develops from Integrated Modular Avionics (IMA) and realizes distributed integration of multiple sub-function areas. Time-triggered network provides effective support for time synchronization and information coordination in DIMA systems. However, inconsistency between processing resources and communication network destroys the time determinism benefiting from partitions and time-triggered mechanism. To ensure such time determinism and achieve guaranteed real-time performance, system design should collectively provide a global communication scheme for messages in network domain and a corresponding execution scheme for partitions in processing domain. This paper firstly establishes a general DIMA model which coordinates partitioned processing and time-triggered communication, and then proposes a hybrid scheduling algorithm using Mixed Integer Programming to produce feasible system schemes. Furthermore, incrementally integrating new functions causes upgrades or reconfigurations of DIMA systems and will generate integration cost. To control such cost, this paper further develops an optimization algorithm based on Maximum Satisfiability Problem and guarantees that the scheduling design for upgraded DIMA systems inherit their original schemes as much as possible. Finally, two typical cases, including a simple fully connected DIMA system case and an industrial DIMA system case, are constructed to illustrate our DIMA model and validate the effectiveness of our hybrid scheduling algorithms.     

非线性系统中多传感器目标跟踪融合算法研究

 研究了在非线性系统中 ,基于转换坐标卡尔曼滤波器的多传感器目标跟踪融合算法。通过分析得出 :在非线性系统的多传感器目标跟踪中 ,基于转换坐标卡尔曼滤波器 ( CMKF)的分布融合估计基本可以重构中心融合估计。仿真实验也证明了此结论。由此可见分布的 CMKFA是非线性系统中较优的分布融合算法     

基于递推平方根法的神经网络模型辨识

提出一种基于递推平方根法的神经网络模型辨识方法,对Davidon最小二乘法和阻尼最小二乘法进行了改进,既保持了二者简单易行、收敛性的优点,又能提高精度,减少计算量,适合于应用在非线性系统的辨识和自适应控制中。与常规的Davidon最小二乘法和阻尼最小二乘法进行仿真比较,体现出了这种方法的有效性,尤其是在输入及隐含节点个数较多的情况,其优点比较明显。     

Implicit Adaptive Control for a Class of MIMO Systems

Two implicit model reference adaptive control algorithms for multi-input multi-output systems are developed. These algorithms do not require either satisfaction of the perfect model following conditions or explicit parameter identification. The first algorithm ensures asymptotic stability of the output error provided that the output stabilized plant transfer matrix is strictly positive real. The second algorithm guarantees a bounded error under less restrictive conditions. The algorithms are applied to the lateral axis of an F-8 aircraft.     

Concerns about Hash Cracking Aftereffect on Authentication Procedures in Applications of Cyberspace

In the Crypto 2004 Conference (Wang et al., 2004), one of the big news was that a fundamental technique in cryptography - one of the hash algorithms, Message Digest 5 (MD5) had been cracked. Soon after this event, it was announced that the secure hash algorithm (SHA-1) had been cracked as well. This series of information shocked the researches in the field of cryptography, and raised the attention of every related organization of security application mechanisms. Most agencies are still looking into the impact this may have, and are considering their future responses and solutions in the wake of these developments in the hash structure of cryptanalysis. Based on this information, this paper will discuss in detail the broken MD5 and SHA-1, which both are reported to have been cracked, and will investigate any impact, and propose recommendations for the applications in cyber-space, such as password authentication and forensic software, when using a hash algorithm     

Hybrid Simulation System Study of SINS/CNS Integrated Navigation

In flight tests, to demonstrate the performance of integrated navigation systems, which are strapdown inertial navigation systems/celestial navigation systems (SINS/CNS), will involve a lot of effort and a heavy financial budget. So, it is important to design a functional self-contained hardware in a loop simulation system on the ground for solving the verification of SINS/CNS integrated navigation systems. Aiming at solving the main program, a high precision, versatile and better real-time performance hybrid simulation system of SINS/CNS integrated navigation is presented. The system adopts the design of hardware-functional modularization and software-flow integration, and makes use of a trajectory generator to produce simulated nominal trajectory data which is a uniform reference to signal process, and employs unique time synchronization algorithms to collect actual errors data of inertial sub-system and celestial sub-system. By combining with nominal trajectory data, the data smoothing, all-sky autonomous star map identification and integrated navigation algorithm based on unscented Kalman filtering (UKF), this system can accomplish a lot of system performance testing. It has the features of flexibility and extensibility and can be used to effectively reduce the experimental expense and shorten the development time of integrated navigation system, which is significant for studying algorithm performance, system speciality, and practical application of integrated navigation system.     

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。     

失效概率矩独立全局灵敏度分析的高效算法

失效概率矩独立全局灵敏度分析对指导可靠性优化至关重要，本文从乘法降维及Edgeworth级数展开的角度提出一种失效概率矩独立全局灵敏度指标分析的高效算法。所提算法通过Edgeworth级数展开将失效概率矩独立全局灵敏度指标的求解转化为输出无条件及条件前四阶整数矩的求解。对于输出的无条件及条件四阶矩的计算，基于乘法降维的思想，本文推导了重复利用计算输出的无条件矩的输入输出样本来计算条件矩以及外层关于输入变量一维积分的计算公式，使得仅需重复利用输出无条件前四阶矩求解产生的积分网格内的数据即可同时求得输出的前四阶条件矩以及外层关于输入变量的一维积分。所提算法大大提高了失效概率矩独立全局灵敏度的分析效率。航空发动机涡轮盘以及汽车前轴的分析结果验证了所提算法的高效性及准确性。     

铣削过程在线辨识与极点配置自适应控制

 研究了铣削加工过程的建模、参数在线辨识及自适应控制问题,为铣削过程建立了二阶离散传递函数模型,提出了一种修正的带遗忘因子递推最小二乘参数辨识算法,从而解决了普通递推最小二乘辨识算法中由于递推计算协方差矩阵衰退或膨胀引起辨识结果失真的问题,采用极点配置设计原理,为铣削过程推导了自适应控制的控制律。仿真和实验表明,修正的最小二乘辨识算法和极点配置自适应控制律是正确和可靠的,自适应控制器可获得所需的响应性能。     

A grid algorithm for autonomous star identification

An autonomous star identification algorithm is described that is simple and requires less computer resources than other such algorithms. In simulations using an 8/spl times/8 degree field of view (FOV), the algorithm identifies the correct section of sky on 99.7% of the sensor orientations where spatial accuracy of the imaged star is 1 pixel (56.25 arc seconds) in standard deviation and the apparent brightness deviates by 0.4 units stellar magnitude. This compares very favorably with other algorithms in the literature.