MAP estimation of target manoeuvre sequence with theexpectation-maximization algorithm

Two algorithms are derived for the problem of tracking a manoeuvring target based on a sequence of noisy measurements of the state. Manoeuvres are modeled as unknown input (acceleration) terms entering linearly into the state equation and chosen from a discrete set. The expectation maximization (EM) algorithm is first applied, resulting in a multi-pass estimator of the MAP sequence of inputs. The expectation step for each pass involves computation of state estimates in a bank of Kalman smoothers tuned to the possible manoeuvre sequences. The maximization computation is efficiently implemented using the Viterbi algorithm. A second, recursive estimator is then derived using a modified EM-type cost function. To obtain a dynamic programming recursion, the target state is assumed to satisfy a Markov property with respect to the manoeuvre sequence. This results in a recursive but suboptimal estimator implementable on a Viterbi trellis. The transition costs of the latter algorithm, which depend on filtered estimates of the state, are compared with the costs arising in a Viterbi-based manoeuvre estimator due to Averbuch, et al. (1991). It is shown that the two criteria differ only in the weighting matrix of the quadratic part of the cost function. Simulations are provided to demonstrate the performance of both the batch and recursive estimators compared with Averbuch's method and the interacting multiple model filter     

Parameter identification for state-space models with nuisanceparameters

The problem of identifying parameters in a dynamic model is considered based on the premise that certain parameters not being estimated are not known precisely. A procedure is described for accounting for these imprecisely known nuisance parameters when estimating the primary parameters of interest. The technique uses the asymptotic normality of the estimate together with the implicit function theorem to determine a correction to the estimate uncertainty evaluated from the Fisher information matrix. Efficient evaluation of the correction using Kalman filters is discussed and a numerical example for the X-22A aircraft is presented     

基于隐马尔科夫模型的故障诊断系统研究

在制造行业中,机械设备的状态检测技术能提供关于设备运行状态的实时信息,为避免生产损失和减少设备的致命故障提供保障。提出了一套基于小波变换和隐马尔科夫模型(Hidden Markov Models,HMMs)的故障检测系统。提出了小波模极大值分布(Wavelet Modulus Maxima Distribution),并将之定义为诊断系统的观察量加以验证。同时该系统采用在线模型参数估计和培训算法,通过选取能最大化对数似然度的HMM模型,确定设备所处状态。     

Bearings-only tracking for maneuvering sources

Classical bearings-only target-motion analysis (TMA) is restricted to sources with constant motion parameters (usually position and velocity). However, most interesting sources have maneuvering abilities, thus degrading the performance of classical TMA. In the passive sonar context a long-time source-observer encounter is realistic, so the source maneuver possibilities may be important in regard to the source and array baseline. This advocates for the consideration and modeling of the whole source trajectory including source maneuver uncertainty. With that aim, a convenient framework is the hidden Markov model (HMM). A basic idea consists of a two-levels discretization of the state-space. The probabilities of position transition are deduced from the probabilities of velocity transitions which, themselves, are directly related to the source maneuvering capability. The source state sequence estimation is achieved by means of classical dynamic programming (DP). This approach does not require any prior information relative to the source maneuvers. However, the probabilistic nature of the source trajectory confers a major role to the optimization of the observer maneuvers. This problem is then solved by using the general framework of the Markov decision process (MDP)     

相控阵雷达长时跟踪波束调度与波形优化策略

针对相控阵雷达多目标跟踪波束调度和波形参数优化控制的问题，本文提出了一种基于马尔可夫决策过程（MDP）的相控阵雷达跟踪波束调度与波形参数优化策略，该方法以无迹卡尔曼滤波（UKF）算法为基础来估计目标的状态。首先将本文的序列决策问题建模为马尔可夫决策过程，定义了资源的效费比和长期回报率，然后与当前实际跟踪误差综合考虑作为MDP的回报函数，进而给出了调度的优化模型，最后将长时决策问题转化为动态规划算法结构进行求解，并且提出了一种并行混合遗传粒子群优化算法来求解各决策时刻的最优策略。仿真结果表明了长时策略的先进性以及寻优算法的优越性，与传统的短时策略相比，跟踪精度可提高11.17%。     

基于贝叶斯模型的长码DS-CDMA信号扩频码与信息序列联合估计

 针对长码直接序列扩频码分多址(DS-CDMA)信号的盲解扩,在信号模型分析的基础上,提出了一种基于可逆跳跃的马尔可夫链蒙特卡罗(RJ-MCMC)扩频码和信息序列联合估计算法。该算法分别对建立的联合后验分布模型进行迭代抽样,并有效地在不同维数的子空间中跳转,从而构造一条马尔可夫链,使其平稳分布为待估参数的后验分布,最终拼接得到每个用户的完整扩频序列和信息序列估计。仿真结果表明:该方法在迭代二十几步时达到收敛;并且在功率相同和不同条件下,当信噪比(SNR)大于-9 dB时,估计序列与真实序列的相似度均超过0.95,信息序列的误码率低于0.01;同时算法对不同用户个数和不同调制样式具有较强的适应性,与Fast-ICA算法相比,估计性能平均提高了约3 dB。     

防空作战动静态武器目标分配初步研究

防空作战中的武器目标分配是影响系统作战有效性的重要因素之一。动静态结合的武器目标分配,既考虑了武器对不同目标杀伤效果,又考虑了作战这一动态随机过程的特性。讨论了在合理简化条件下的分配过程,先把对目标群的射击效能作为目标函数制定决策,可将目标分配决策化成一个马尔可夫决策过程,通过策略迭代算法得到最优分配策略从而实现系统效益的最大化。最后进行了简化条件下的算例验证,结果表明,该方法能使武器系统获得最大的射击效能,是一种有效的分配方法。     

Statistical characterization of clutter scenes based on a Markov random field model

The problem of clutter region identification based on Markov random field (MRF) models is addressed. Observations inside each clutter region are assumed homogenous, i.e., observations follow a single probability distribution. Our goal is to partition clutter scenes into homogenous regions and to determine this underlying probability distribution. Metropolis-Hasting and reversible jump Markov chain (RJMC) algorithms are used to search for solutions based on the maximum a posteriori (MAP) criterion. Several examples illustrate the performance of our algorithm.     

一种减少失速保护虚警率的混合滤波方法

针对飞机失速保护设计过程中易出现虚警的情况,提出一种基于FIR和传统滤波器相结合的混合滤波方法。结合飞机本体的运动特征,对参与失速保护逻辑运算的两个重要参数,即侧向加速度和迎角信号进行频率分析,基于信号的特征设计混合滤波器,然后采用Simulink滤波工具箱设计滤波器对信号进行滤波处理。仿真结果表明该方法能够减少虚警率的发生,特别是大背景噪声下的虚警率能够得到较好抑制,验证了滤波器设计正确性,从而提高失速保护功能对适航条款符合性。该滤波器设计方法,不但可以有效解决本文提到的问题,对于其他涉及信号处理的系统设计同样具有借鉴意义。     

基于马尔可夫方法的飞控系统安全性评估

安全性评估是适航符合性验证的重要方法。对马尔可夫分析在系统安全性评估中的应用进行了深入研究．给出了马尔可夫在系统安全性评估中的一般分析方法。运用马尔可夫方法和故障树方法分别对飞行控制系统的同一种失效状态进行了建模分析．并对二者的分析结果进行了比较,得出对并联顺序系统进行安全性分析时马尔可夫分析方法具有更高的定量分析精度,并克服了故障树静态分析特性的缺点。     

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     

用图论方法分析马尔可夫频次阵特性

 简述了飞机机动疲劳载荷谱的各种常用表征方法及其优点与不足, 重点论述疲劳载荷状态转移的马尔可夫频次矩阵法。结合示例说明马尔可夫频次阵的构造形成与计算机编程填充方法。利用图论研究方法说明马尔可夫阵是一幅欧拉图的邻接矩阵, 阐述了其重要特性, 给出了据此构造疲劳载荷历程的要求与做法,并给出了数据处理实例。通过讨论马尔可夫阵与其他疲劳载荷表征方法间的关系, 表明马尔可夫矩阵含有更多信息, 是较适合完整描述疲劳载荷谱的表征方法之一。     

几何规划在飞机总体设计中的应用

系统地讨论了代数多项式的算术－ 几何均值定理,并对原型几何规划理论作出了简明的推导与分析。提出了具有缩并迭代特性的几何规划求解理论和编程步骤。还用２ 个工程设计的优化求解算例来说明这种缩并迭代几何规划优化求解特点和优点。例１ 显示了几何规划的工程实用性和简易性;例２ 通过轻型飞机总体方案参数优化,说明所提出的优化方法,可随设计人员思路的变动而得到及时地相适应。     

防空辅助决策系统中部署方案的评估计算模型

在防空辅助决策系统中,对战斗部署方案进行评估是防空作战中非常关键的一环,评估计算模型的优劣对结论起着重要的影响。防空战斗部署主要包括防空兵器战斗部署和情报预警雷达组网部署两部分。首先分析了防空兵器战斗部署的评估指标体系,用数学规划的方法对其作战能力进行评估。然后运用开马尔可夫排队网络对情报预警能力进行评估。     

面向飞机表面喷涂的多层次控制程序结构

 为实现飞机外表面的机器人自动化喷涂,根据飞机外表面的几何特征,提出了飞机表面喷涂轨迹的规划方案和自动化喷涂作业的定位方法。根据该方法制订了多层次的喷涂控制程序结构,包括主逻辑层、控制程序层、辅助功能层3个层次。主逻辑层负责整个程序体系运行的调度,即调用控制程序层和辅助功能层中的功能模块;控制程序层包含飞机表面的分区及相应的喷涂控制程序模块;辅助功能层包括喷涂工艺参数、运动参数、系统默认参数等内容。为快速生成多层次喷涂程序体系,提出了面向飞机外表面喷涂的离线编程技术方案。以飞机模型表面喷涂为例,验证了方法的有效性和可维护性。     

Optimal Detection of a Signala with Time-Varying Carrier Phase

The problem considered in this paper is the detection of a signal known except for time-varying carrier phase in white Gaussian noise. The method of attacking this problem is to model the time-varying carrier phase as a Markov process. Fourier transform techniques are then applies to yield a simple time-wise adaptive form for the phasetracking detector. Optimal accounting for the time variations in phase is accomplished via a simple algorithm which serves to update the detector memory. Furthermore, it is shown that this memory updating operation is a discrete linear filter whose impulse response is a simple function of the previous memory state and the Markov transitional statistics on the phase. A priori knowledge regarding the phase is summarized in the initial impulse response of the updating filter.     

一种飞-续-飞随机谱的编制方法及软件

本文介绍了一种飞-续-飞随机谱的编制方法和软件。它以空测的重心过载数据为基础,经过数据处理后,建立对应于每个飞行任务的Markov矩阵。并调整统计平均后的Markov矩阵以保证可得到一个不中断的过载序列。然后从矩阵中抽取半循环序列,构成飞-续-飞随机谱。本文中讨论了矩阵中半循环的随机抽取方法,给出了应用实例。     

扰动环境下火星精确着陆自主轨迹规划方法

针对扰动环境下火星精确着陆动力下降段自主轨迹规划问题,在终端时间自由条件下,研究了基于序列凸优化方法的自主轨迹规划方法。首先,在终端自由情况下,建立初始状态无扰动轨迹预规划问题。其次,结合鲁棒Tube-MPC思想,针对线性反馈控制律,建立扰动环境下着陆轨迹重规划问题,分析重规划问题的可行性,给出了预规划问题可行的必要性条件,为控制参数的选取提供参考,提出扰动环境下火星精确着陆自主轨迹规划框架。然后,针对终端自由问题,将飞行时域映射到单位时间,建立序列凸优化子问题,对子问题进行线性近似,使用序列凸优化方法进行求解并分析了收敛解的最优性。最后,进行数值仿真,验证扰动环境下火星精确着陆自主轨迹规划方法的有效性。     

近地小推力转移轨道的加权组合制导策略

 研究了近地小推力转移轨道的制导问题,给出了一种基于局部最优控制律的自主制导算法。推导出了各改进春分点根数对应的局部最优控制律;通过最优推力分配和目标偏差两个策略,对各局部最优控制律进行动态加权组合,从而有效减少了制导律的设计参数。在此基础上,针对燃料最省转移轨道,定义了一种新的发动机开关函数。采用遗传/逐次二次规划混合优化算法计算了最优制导参数。与传统算法相比,该制导算法是一种闭环制导算法,能够实现飞行器的自主制导,并且制导过程中无需对制导参数进行更新。以地球低轨到高轨的小推力转移为例,采用该方法分别求解了时间和燃料最省转移问题,并与传统算法进行了比较分析。数值结果验证了该算法的有效性。     

PLC中顺序控制问题的一种解决方案

本文通过液压系统顺序控制实例，介绍采用字节标志，然后分别映射到输出的编程方法及给编程带来了灵活性。