基于小波分析和鲁棒最小二乘的信息融合估计算法

对于农田土壤的多传感器检测系统来说,其测量的信息具有非线性和时空变异等特性,因此对信息融合方法的基本要求是具有鲁棒性和并行处理能力.应用小波分析理论,对原始测量数据进行了降噪处理,使降噪后的数据更能反映土壤的本质及变化规律:应用鲁棒最小二乘估计技术可以对不同传感器数据进行综合处理,去除冗余,克服歧义,得到比任何单个传感器更全面、更准确、更可靠的信息.针对农业中的自然环境具有很强的不确定性和经验性,运用基于小波分析的降噪和现代信息融合思想,提出了一种基于小波降噪和鲁棒最小二乘的信息融合估计方法.通过实验分析,其结果表明该方法是可行和值得研究的.     

基于线性规划的不确定系统参数及其边界的辨识方法

一般的辨识方法都是求系统参数的点估计。但是在鲁棒控制、鲁棒自适应控制中,不但要知道系统的标称模型,而且要求得到系统参数的不确定性区间估计＾（１）。本文提出了一种用线性规划法求得系统参数不确定性间隔的方法。这种方法可以用于ＵＢＢＥ（Ｕｎｋｎｏｗｎ Ｂｕｔ Ｂｏｕｎｄｅｄ Ｅｒｒｏｒ）系统中。该算法不但可以提高估计的精度,而且还可以给出参数的不确定性边界,从而方便了鲁棒控制系统的设计。     

基于改进鲁棒DEA模型的电力系统评价研究

针对传统DEA模型在不确定环境下评价结果不稳定的缺陷,提出了一种改进的鲁棒DEA评价方法,为电网建设和投资规划提供有效的经济指导。该方法采用鲁棒模糊核主成分分析,确定电力系统评价的投入产出指标;考虑投入产出不确定性,利用不确定信息一般化思想和对偶理论构建鲁棒DEA模型。为验证模型效果,采用我国部分省级电力系统的投入产出数据,研究不确定环境下电力系统评价的稳定性,实验表明,鲁棒DEA模型会在效率最优性和求解可靠性之间权衡,当投入产出数据同时面临不确定扰动时,模型仍能保证评价的准确稳定性。     

合成孔径声纳姿态及运动估计--鲁棒Kalman估计算法

合成孔径声纳姿态及运动估计系统一般由惯性测量单元(IMU),差分DGPS,声多普勒计程仪DVL,深度传感器,磁罗经等多种测量传感器组成.通常情况下,惯性测量单元(IMU)必须与DVL或DGPS进行数据融合,才能获得更好的测量性能;同时,由于姿态及运动监测系统的传感器较多,系统受外界扰动影响比较严重,即观测野值比较严重.因此,将M-估计原理应用到Kalman滤波算法中,利用鲁棒Kalman滤波算法来处理合这类估计问题.计算机仿真结果表明,该方法将惯性测量单元(IMU)测量结果与差分DGPS或DVL测量结果进行数据融合,较好地解决了合成孔径声纳姿态、运动估计问题.     

基于非线性系统描述的超声马达鲁棒跟踪控制

针对行波型超声马达,在非线性系统描述的数学模型基础上,采用了一种新的鲁棒控制方案．该控制器由标称控制器和鲁棒补偿器两部分构成。首先,针对标称系统设计标称控制器得到期望的输出跟踪特性,然后加上鲁棒补偿器,实现鲁棒特性。可以证明,鲁棒稳定性、鲁棒静态特性、鲁棒瞬态特性以及鲁棒跟踪特性可同时得到．仿真和实验结果都表明了控制方案的有效性,而且该控制器结构简单、参数可在线调整.     

大型相控阵雷达可靠性评估方法

大型相控阵雷达整机外场可靠性试验可分为联调联试和验证试验两个阶段。针对现有的整机可靠性评估仅利用验证试验阶段较少的试验数据,导致整机可靠性评估结果置信度低的问题,提出一种基于改进序化关系模型的整机可靠性评估方法。该方法通过构建新的联合似然函数对传统序化关系模型进行改进,并融合联调联试数据和验证试验数据来评估整机的可靠性水平。实例表明:该方法能提高整机平均故障间隔时间在同一置信水平下的估计下限,缩短平均故障间隔时间的估计区间。     

多尺度时空上下文目标跟踪

相关滤波器在视觉目标跟踪中得到了广泛应用,针对复杂场景下目标跟踪容易出现跟踪漂移的问题,以及现有多尺度跟踪算法计算量大的问题,本文提出一种实时的多尺度目标跟踪方法。首先由时空上下文模型输出目标位置置信图完成目标定位,再在尺度空间上训练相关滤波器完成目标尺度估计,最后基于目标位置和尺度提出了一种新的时空上下文模型更新机制,避免了模型更新错误。实验表明:该方法在尺度变化、局部遮挡、目标姿态变化等情况下均能完成鲁棒跟踪,跟踪正确率较原始时空上下文跟踪算法提高了38.4%。     

DI/QFT控制器在四旋翼无人直升机飞行控制中的应用

首先建立了四旋翼无人机的非线性数学模型.然后针对该无人机数学模型的不确定性和非线性,采用动态逆(DI)和定量反馈理论(QFT)相结合的方法设计了该无人机姿态回路的鲁棒控制器.应用动态逆方法处理对象的非线性,将系统等效为一个解耦但存在不确定性的线性对象.鉴于动态逆控制在气动参数摄动的情况下不能满足控制要求的事实,设计了QFT控制器,QFT控制器能克服对象的参数不确定性,保障系统的鲁棒性.仿真结果表明,在气动数据变化±20%的范围内,DI/QFT控制器实现了对姿态角的精确控制.     

单目视觉拼图导航中的单应矩阵估计

在单目视觉拼图导航与水下自主机器人的准确定位中,针对单一的单应矩阵代数估计方法和鲁棒估计方法导致估计结果较大的偏差性,研究了利用图像对之间的匹配点估计单应矩阵的原理。分析了测量数据点对可能存在的误匹配及测量误差,会导致测量矩阵的非线性、病态性,从而影响单应矩阵的准确估计。融合几种单应矩阵估计方法,提出了因子归一化鲁棒估计方法对单应矩阵进行估计。利用该方法既能优化测量矩阵,又能剔除误匹配点。实验结果表明,该方法较准确地估计了单应矩阵。     

鲁棒最小二乘在测位探测器建模中的应用

本文主要讨论了鲁棒最小二乘方法在测位控制器建模中的应用。首先简单介绍了鲁棒最小二乘方法的原理及几何解释;对测位控制器的输入误差的结构进行了估计,然后利用这种误差结构所确定的鲁棒最小二乘方法进行测位控制器建模,生成了模型参数,并对所生成的模型参数进行数字仿真验证和误差适应性测试,分析了各种测试结果,从而证明了在有不确定性扰动因素的情况下,利用鲁棒最小二乘方法建模对提高测位控制器的控制精度是有效而可行     

宽带子阵域特征空间稳健对角减载波束形成

针对宽带子阵域自适应波束形成器在实际使用中稳健性下降、对弱信号的检测能力受信噪比限制的问题,提出了一种宽带子阵域特征空间稳健对角减载自适应波束形成方法.首先提出利用子阵域特征空间投影法修正导引向量并得到球形不确定集的估计,再利用RCB（Robust Capon Beamformer）算法得到约束条件下的最优权值.另一方面,利用子阵域互谱密度矩阵的最小特征值作为子阵域非相关噪声功率的估计并进行对角减载,以最优权值对减载矩阵波束形成得到子带波束输出,对每个窄子带重复上述处理,再将结果非相干叠加即可得到本文方法的最终结果.理论及实验分析表明方法能提高自适应波束形成器的稳健性及输出信噪比.     

基于激光雷达距离像的目标3D姿态估计

在激光雷达目标识别中,目标姿态的精确估计可以有效地简化识别过程.现有的PDVA算法主要是针对地面结构化目标而提出的一种3D目标姿态估计方法.该方法利用模型坐标系(MCS)各个坐标轴的正方向向量来确定目标的三维姿态角,其有效性通过实验得到了验证.但该方法在确定MCS各坐标轴的正方向向量时,所消耗的时间比较多,影响了算法的执行效率.文中提出了一种改进的PDVA算法,利用聚类中心邻域判别CCND法来加速MCS各坐标轴的正方向向量的确定过程.采用四种地面军用车模型目标进行了仿真实验,实验结果显示,改进的PDVA算法的平均运行时间约占PDVA算法的66%,极大地提高了目标3D姿态估计的执行效率.     

An improved MMUSIC algorithm of direction of arrival estimation

An improved algorithm is presented for a signal's direction of arrival estimation to reduce the computational complexity of the existing modified multiple signal classification (MMUSIC) algorithm. In this paper, FFT algorithm is introduced to narrow the searching range of the direction angle. Afterwards, a compromise approach‐based SVD and orthogonal–triangular decomposition takes the place of traditional double SVDs. Then, during matrix calculation, the noise subspace is achieved for the signal's direction of arrival. Finally, the system simulation demonstrates the efficiency and reliability of this novel MMUSIC algorithm. Compared with the existing algorithm, MMUSIC effectively saves the computational complexity with the approximation estimation performance. Copyright © 2011 John Wiley & Sons, Ltd.     

基于测量误差不确定性加权的快速相机位姿估计算法

在相机位姿估计任务中,参考点位置的测量容易受测量仪器或者所处环境影响,出现一定程度的测量误差,其中误差较大的点对最终求解精度的影响很大,被称为野值点。文章针对现有算法抗野值点能力较弱的问题,提出一种基于测量误差不确定性加权的快速相机位姿估计算法。该算法以经典的正交迭代算法为基础,引入M估计方法,对目标函数根据参考点的测量误差赋予相应大小的权值,最大程度地将野值点的影响排除,并引入Kronecker积对计算过程进行优化,减少了迭代过程中的冗余计算,提高运算速度。仿真实验结果表明,改进后的算法提升了原算法的抗野值点能力,且计算速度更快。     

Robust and Accurate Frequency and Timing Synchronization Using Chirp Signals

We propose a new robust and accurate synchronization procedure using a training sequence composed of chirp signals. We use a new integer frequency estimation algorithm and propose a new combination of a known fractional frequency offset estimation algorithm and timing synchronization algorithm. The training sequence is composed of one up and two down chirp symbols, also known as Newman phases. The integer frequency offset estimation algorithm uses the effect of timing and frequency offsets on the matched filter outputs of the chirp signals. Autocorrelation and reversed autocorrelation are used to acquire the timing instant and the fractional frequency offset. We present the complete timing and frequency synchronization procedure and study the output signals of the autocorrelation and reversed autocorrelation algorithms. Finally, we check the performance of the synchronization procedure via Monte Carlo simulation in several multipath channels. Our algorithms are accurate and more robust compared to previously published state-of-the art algorithms.      

数字稳像中的快速和鲁棒运动估计研究

 提出了一种用于数字图像稳定的快速和鲁棒运动估计方法.在图像的运动估计中,首先采用一种预判局部宏块的算法：在计算运动矢量前对宏块的梯度信息进行分析以避免误匹配,通过减少参与计算的宏块数目提高处理速度;其次,提出快速估计宏块运动矢量的方法,用改进的序贯相似性算法(SSDA)进行块匹配,以提高运动矢量的计算速度;然后采用LMedS估计法去除不精确的宏块运动向量,用最小二乘法求解出最优的模型参数.实验结果表明了该方法的精确性、快速性和鲁棒性.     

Efficient De-Jitter Control for Voice Applications over Wireless Ad Hoc Networks

Voice over IP applications require a playout buffer at the receiver side to smooth network delay variations. Unfortunately, existing algorithms for dynamic playout adjustment designed for wireline networks do not operate correctly in wireless ad hoc networks. These algorithms estimate the end-to-end delay on the set of previous received audio packets. Indeed, such a delay estimation based on past history is not appropriate due to mobility which leads to random changes of the network topology. In this paper, we highlight this delay estimation problem. We show that route request AODV control messages provide more accurate delay estimation. Then, we propose a new algorithm for playout delay adjustment based on these control messages. The performance evaluation is performed by simulation using ns-2. We show that this algorithm outperforms existing playout delay adjustment algorithms. Performance criteria are loss late percentage (reliability criterion), averaged playout delay (interactivity criterion) and playout delay variation (stability criterion).     

System optimization with component reliability estimation uncertainty: a multi-criteria approach

Summary & Conclusions-This paper addresses system reliability optimization when component reliability estimates are treated as random variables with estimation uncertainty. System reliability optimization algorithms generally assume that component reliability values are known exactly, i.e., they are deterministic. In practice, that is rarely the case. For risk-averse system design, the estimation uncertainty, propagated from the component estimates, may result in unacceptable estimation uncertainty at the system-level. The system design problem is thus formulated with multiple objectives: (1) to maximize the system reliability estimate, and (2) to minimize its associated variance. This formulation of the reliability optimization is new, and the resulting solutions offer a unique perspective on system design. Once formulated in this manner, standard multiple objective concepts, including Pareto optimality, were used to determine solutions. Pareto optimality is an attractive alternative for this type of problem. It provides decision-makers the flexibility to choose the best-compromise solution. Pareto optimal solutions were found by solving a series of weighted objective problems with incrementally varied weights. Several sample systems are solved to demonstrate the approach presented in this paper. The first example is a hypothetical series-parallel system, and the second example is the fault tolerant distributed system architecture for a voice recognition system. The results indicate that significantly different designs are obtained when the formulation incorporates estimation uncertainty. If decision-makers are risk averse, and wish to consider estimation uncertainty, previously available methodologies are likely to be inadequate.     

相关竞争失效场合雷达功率放大系统可靠性评估

针对相关竞争失效场合难以获取高可靠部件的性能分布信息,无法对系统可靠性进行准确估计的问题.提出了相关竞争失效场合下考虑认知不确定性的多态系统可靠性评估方法.该方法首先通过假定部件突发失效阈值为递减型随机过程来表征累积退化与突发失效的相关性,同时为降低对部件认知不确定性的影响,假定冲击引起的部件性能损伤分布参数和突发失效参数均为区间变量,建立基于区间变量的部件性能分布模型;而后对传统的通用生成函数方法进行改进,给出了区间通用生成函数的定义及其运算法则;最后对某型雷达功率放大系统的可靠性进行分析.该方法不仅克服了部件的失效模式复杂、状态信息少的不足,且方法简单、思路清晰,具有很强的通用性和工程应用价值.     

Fast Random‐Forest‐Based Human Pose Estimation Using a Multi‐scale and Cascade Approach

Since the recent launch of Microsoft Xbox Kinect, research on 3D human pose estimation has attracted a lot of attention in the computer vision community. Kinect shows impressive estimation accuracy and real‐time performance on massive graphics processing unit hardware. In this paper, we focus on further reducing the computation complexity of the existing state‐of‐the‐art method to make the real‐time 3D human pose estimation functionality applicable to devices with lower computing power. As a result, we propose two simple approaches to speed up the random‐forest‐based human pose estimation method. In the original algorithm, the random forest classifier is applied to all pixels of the segmented human depth image. We first use a multi‐scale approach to reduce the number of such calculations. Second, the complexity of the random forest classification itself is decreased by the proposed cascade approach. Experiment results for real data show that our method is effective and works in real time (30 fps) without any parallelization efforts.