一种简化特征空间稳健自适应波束形成算法*

在基于特征空间(ESB)的自适应波束形成算法中,针对当指向误差落在波束主瓣的边缘特定角度时,输出信干噪比下降,且信号子空间需要进行费时的特征值分解的问题,提出了改进线性约束最小方差(LCMV)算法。在假定的期望信号方向附近减少一个方向性约束条件,并基于信号特征值大于噪声特征值的这一特性, 利用空间协方差矩阵逆的高阶次幂来逼近信号子空间,无须特征分解,将求得的权矢量向改进的信号子空间投影。该方法能够大大减少计算量,同时还显著提高了自适应波束形成稳健性。通过仿真分析及结果比较验证了算法的正确性和有效性,因此从     

基于子空间拟合波达方向估计方法研究

传统波达方向(DOA)估计方法由于受阵列尺寸的限制,对处于同一波束内的多个信号源无法得到正确的估计.为此提出了基于子空间拟合的信号到达方位角(DOA)估计算法--信号子空间拟合算法和噪声子空间拟合算法.算法通过对接收数据的子空间与实际信号导向矢量组成的子空间的拟合,来构造信号功率谱尖峰,从而估计目标信号的到达方位角.仿真实验对两种算法的性能进行了分析,分析表明基于噪声子空间拟合算法能突破空域瑞利限的限制,具有空间分辨率高、稳定性好的估计性能.信号子空间拟合算法只有在阵元数较大时,才能正确分辨距离较近的信号源,但具有对环境噪声不敏感的特点.     

人体自由运动状态下的视线追踪算法研究*

针对人体在大空间范围内自由运动时视线方向难以追踪的问题,构建了一套基于光学跟踪设备的头戴式视线追踪系统。系统通过被动式光学追踪设备和头戴式眼部摄像机获取使用者的头部运动状态与眼部图像,然后依据初始标定结果来估计使用者自由运动状态下的视线方向;最后对系统进行简化,得到了适用于同类环境、与具体硬件设备无关的视线跟踪三点三面三变换几何模型。对系统进行应用实验和误差分析表明,使用者在3.0 * 3.2 * 2.0 m的大工作空间内自由运动时视线追踪误差为1.69度,频率为20赫兹。     

Transmission of roll and pitch seat vibration to the head

A series of experiments has investigated the transmission of roll and pitch seat vibration to the heads of seated subjects. Head motion was measured in all six axes using a light-weight bite-bar while seated subjects were exposed to random motion at frequencies of up to 5 Hz at 1.0 rad.s ^?2 r.m.s. Subjects sat on a rigid flat seat in two body postures: ‘back-on’ (back in contact with backrest) and ‘back-off’ (no backrest contact). The influence of the position of the centre of rotation was also investigated.

Motion at the head occurred mostly in the lateral, roll and yaw axes during exposure to roll seat vibration and in the fore-and-aft, vertical and pitch axes during exposure to pitch seat vibration. A reduction in the magnitude of head motion occurred when the subjects sat in a 'back-off' posture compared with a 'back-on' posture. Varying the position of the centre of rotation along the lateral axis during roll seat vibration affected vertical and pitch head motion: least head motion occurred when the centre of rotation was in line with the subject's mid-sagittal plane. Varying the position of the centre of rotation along the vertical axis during roll seat vibration affected head motion in the mid-coronal plane: roll head motion decreased as the position of the centre of rotation was raised from below the seat surface to above the seat surface. Varying the centre of rotation (along the fore-and-aft and vertical axes) during pitch seat vibration altered head motion in the mid-sagittal plane. Head motion increased with increasing distance of the centre of rotation in front or behind the subject's ischial tuberosities and increased as the seat was raised from below the centre of rotation to above the centre of rotation.     

Auxiliary Diagnosis for Parkinson's Disease Using Multimodal Feature Analysis

Parkinson''s disease is a widespread neurodegenerative disease that slowly impairs motor and certain cognitive skills. It is insidious and incurable, and it causes a significant burden on sufferers and their families. However, clinical diagnosis of Parkinson''s disease typically relies on subjective rating scales, which can be influenced by the examinee''s recall bias and assessor subjectivity. Numerous studies have used diverse methods to investigate the physiological aspects of Parkinson''s disease and have provided objective, quantifiable tools for auxiliary diagnosis. However, given the diversity of neurodegenerative illnesses and the similarities in their effects, it remains a problem among unimodal methodologies built upon the representations of Parkinson''s disease to identify the disease uniquely. To this end, we develop a multimodal diagnostic tool comprising the paradigms that evoke potential Parkinson''s aberrant behaviors. First, parametric tests of the identifying features are performed based on the results of the normal distribution test, and statistically significant feature sets are constructed ($p <$ 0.05). Second, multimodal data are collected from 38 cases in a clinical setting using the MDS-UPDRS scale. Finally, the significance of different feature combinations for the assessment of Parkinson''s disease is analyzed based on gait and eye movement modalities; the high immersion triggered task paradigm and the multimodal Parkinson''s disease diagnostic tool are validated in virtual reality scenarios. It is worth noting that it only take 2--4 tasks for the combination of gait and eye movement modalities to obtain an average AUC of 0.97 and accuracy of 0.92.     

基于双旋Lyapunov矢量场的无人机避障算法

提出一种基于双旋Lyapunov矢量场的无人机避障算法.首先,建立无人机和障碍物的模型,并根据无人机有限时间是否会侵犯障碍物安全圆设计避障判定规则;然后,基于最小侧向偏移量原则选定避障机动中无人机速度旋转方向为最优避障方向,选定其反方向为矢量场旋转方向,定义成功避障的标准并进行证明;最后,通过建立的障碍物合并规则提升避障效率,使得上述方法适用于未知环境下的无人机在线避障.仿真结果表明,在无人机性能约束下,所提出的算法对动态和静态障碍都能有效避障,算法性能优于Dubins路径和人工势场法.     

一类改进混沌Lur′e系统的滞后同步判据

本文研究了混沌Lur′e系统的滞后同步问题.通过合理构造增广Lyapunov-Krasovskii泛函,使得增广向量不仅包括单积分项以及双积分项,而且加入了增广的三重积分项.在估计Lyapunov-Krasovskii泛函导数表达式的基础上,通过零等式引入自由矩阵,同时利用积分不等式,求得以线性矩阵不等式形式表达下的混沌Lur′e系统滞后同步的判据,即充分条件.最后,通过数值计算表明本文理论研究的有效性.     

使用人眼几何特征的视线追踪方法

目的 视线追踪是人机交互的辅助系统,针对传统的虹膜定位方法误判率高且耗时较长的问题,本文提出了一种基于人眼几何特征的视线追踪方法,以提高在2维环境下视线追踪的准确率。方法 首先通过人脸定位算法定位人脸位置,使用人脸特征点检测的特征点定位眼角点位置,通过眼角点计算出人眼的位置。直接使用虹膜中心定位算法的耗时较长,为了使虹膜中心定位的速度加快,先利用虹膜图片建立虹膜模板,然后利用虹膜模板检测出虹膜区域的位置,通过虹膜中心精定位算法定位虹膜中心的位置,最后提取出眼角点、虹膜中心点等信息,对点中包含的角度信息、距离信息进行提取,组合成眼动向量特征。使用神经网络模型进行分类,建立注视点映射关系,实现视线的追踪。通过图像的预处理对图像进行增强,之后提取到了相对的虹膜中心。提取到需要的特征点,建立相对稳定的几何特征代表眼动特征。结果 在普通的实验光照环境中,头部姿态固定的情况下,识别率最高达到98.9%,平均识别率达到95.74%。而当头部姿态在限制区域内发生变化时,仍能保持较高的识别率,平均识别率达到了90%以上。通过实验分析发现,在头部变化的限制区域内,本文方法具有良好的鲁棒性。结论 本文提出使用模板匹配与虹膜精定位相结合的方法来快速定位虹膜中心,利用神经网络来对视线落点进行映射,计算视线落点区域,实验证明本文方法具有较高的精度。     

Unknown input reconstruction for LPV systems

Detection and invariant subspaces of unknown inputs' signals for linear parameter‐varying systems are examined in the paper. For a class of nonlinear system like this, the effect of unmeasured signals in parameter‐varying measurement equation at the plant output is investigated. The main contributions of the paper are the parameter‐varying extension of the pseudo‐actuation of the possible and generic unknown sensor signal and the proposition of parameter‐dependent similarity transformation. The general parameter‐varying measurement equation is casted into a parameter‐independent form by the similarity transformation, if any. Moreover, it showed that the nonlinear state transformation does not modify the output subspace spanned by the equivalent pseudo‐actuator directions. The proposed methods are illustrated by a numerical example. Copyright © 2009 John Wiley & Sons, Ltd.     

基于多频稀疏噪声的流场运动方向可视化算法

针对现有流场可视化算法存在的矢量场运动指向二义性以及缺乏对矢量场速率区分等问题进行了研究,提出了一种基于多频稀疏噪声纹理的改进线积分卷积算法,用来提高流场可视化后的信息表达效果。该方法首先根据矢量场速率量级的大小划分频率不同的噪声群,并合成适用于该向量场的特定多频噪声纹理;然后使用斜坡卷积核根据向量场流线对噪声纹理进行卷积;最后生成一幅同时具有矢量场运动方向和运动速率信息的彩色图像。实验结果表明,该方法可以增强用户对流场流量大小和矢量场方向的感知效果,在大规模风场数据可视化的验证实验上取得了良好的可视化效果。     

用于疲劳驾驶检测的人眼快速跟踪方法

针对疲劳驾驶检测中头部运动多变情况下的人眼跟踪问题,提出一种改进的Mean-shift算法,通过对像素值分布特征及目标梯度方向的密度分布特征的迭代公式进行交替迭代运算,实现对运动目标的平移跟踪和旋转跟踪,以改善头部深度旋转运动下的人眼跟踪性能。实验结果表明,该方法在驾驶员头部运动姿态多变的情况下,能快速有效地对人眼进行跟踪和定位。     

Movement of loads with trunk rotation

Movements with participants standing at a bench and moving loads up to 6 kg were studied, with participants using two hands to hold the load and trunk rotation in order to move the loads to specified locations. Tasks were performed with rapid ballistic movements and also with ongoing visual control. Data for ballistic movements were modelled in terms of a modified form of the (Gan, K.-C. and Hoffmann, E.R. 1988. “Geometrical conditions for ballistic and visually controlled movements.” Ergonomics 5 (31): 829–839) model for ballistic movements, taking into account the inertial properties of trunk rotation. Visually-controlled movements were modelled in terms of Fitts' law and a term that allowed for the ballistic form of the first submovement of the visually-controlled movement.

Practitioner Summary: Movement times to move masses up to 6 kg, for workers at a bench using trunk rotation, are given. Theoretical models fit the experimental data very well and allow prediction of movement times.     

Haptic discrimination of virtual surface slope

We report the difference thresholds of the slope of a virtual surface rendered via a force–feedback haptic interface with the body frontal plane as a reference. The factors varied in experiments were the stiffness of a virtual plane, the lateral velocity with which the haptic probe scanned the plane, the length of a scanning interval, the movement direction of the probe to the body frontal plane (toward or away from the body), and lateral scanning direction (left-to-right or right-to-left). Measured slope thresholds ranged from 8.33° to 12.74° and were generally higher than or similar to previously published thresholds for haptic orientation or angle discrimination. The results suggested that haptic slope discriminability was independent of surface stiffness and lateral scanning velocity. Slope discrimination was largely affected by the lateral scan distance, indicating that the terminal difference of probe normal position can be an important sensory cue. In terms of scan direction, inward or rightward scans resulted in better slope discrimination than outward or leftward scans, respectively. These thresholds and findings have implications for haptics applications that involve geometric model modification or simplification of virtual objects while preserving their perceptual properties.     

Effect of target shape on movement time in a Fitts task

Experiments on the effect of target shape in a Fitts movement task are reported. Two experiments investigated the movement time vs. index of difficulty relationship for targets that were square, circular, diamond and triangular in shape. The ratio of standard deviation of hits in the vertical and horizontal directions was constant for all target shapes and thus the movement time could be expressed in terms of the constraint in the direction of motion. Correlation of movement time in terms of an Index of Difficulty based on the standard deviation of hits in the direction of motion showed all data fitting on a single line. Thus the constraint effects of the various shapes occurred from the way in which the hits were distributed within each shape. Various models were tried to account for the effect of the target shape. It was found that the experimental data were best accounted for by a 'cookie-cutter' model in which the target shape was cut into a bivariate normal distribution of hits on the target to obtain a ‘shape factor’ that defined the difficulty of the task relative to the usual rectangular target used in Fitts task experiments.     

High-resolution DOA estimation based on independent noise component for correlated signal sources

In this article, a modified complex-valued FastICA algorithm is utilized to extract the specific feature of the Gaussian noise component from mixtures so that the estimated component is as independent as possible to the other non-Gaussian signal components. Once the noise basis vector is obtained, we can estimate direction of arrival by searching the array manifold for direction vectors, which are as orthogonal as possible to the estimated noise basis vector especially for highly correlated signals with closely spaced direction. Superior resolution capabilities achieved with the proposed method in comparison with the conventional multiple signal classification (MUSIC) method, the spatial smoothing MUSIC method, and the signal subspace scaled MUSIC method are shown by simulation results.     

An effective head pose estimation approach using Lie Algebrized Gaussians based face representation

The accuracy of head pose estimation is significant for many computer vision applications such as face recognition, driver attention detection and human-computer interaction. Most appearance-based head pose estimation works typically extract the low-dimensional face appearance features in some statistic subspaces, where the subspaces represent the underlying geometry structure of the pose space. However, there is an open problem, namely, how to effectively represent appearance-based subspace face for the head pose estimation problem. To address the problem, this paper proposes a head pose estimation approach based on the Lie Algebrized Gaussians (LAG) feature to model the pose characteristic. LAG is built on Gaussian Mixture Models (GMM), which actually not only models the distribution of local appearance features, but also captures the Lie group manifold structure of the feature space. Moreover, to keep multi-resolution structure information, LAG is operated on many subregions of the image. As a result, these properties of LAG enable it to effectively model the structure of subspace face which can lead to powerful discriminative ability for head pose estimation. After representing subspace face using the LAG, we treat the head pose estimation as a classification problem. The within-class covariance normalization (WCCN) based Support Vector Machine (SVM) classifier is employed to achieve robust performance as WCCN could reduce the within-class variabilities of the same pose. Extensive experimental analysis and comparison with both traditional and state-of-the-art algorithms on two challenging benchmarks demonstrate the effectiveness of our approach.     

A Krylov‐subspace technique for the simulation of integrated RF/microwave subsystems driven by digitally modulated carriers

This article introduces a new approach to the analysis of nonlinear RF/microwave systems or subsystems described at the circuit level and excited by sinusoidal carriers modulated by arbitrary baseband signals. The circuit is simulated by a sequence of harmonic‐balance analyses based on a Krylov‐subspace method driven by an inexact Newton loop, and suitably modified to account for coupling with a finite number of preceding time instants. The Jacobian matrix of the nonlinear solving system is computed by an exact algorithm, and its structure is shown to be very well suited for the application of Krylov‐subspace techniques such as the GMRES method. In this way, problems with many millions of nodal unknowns may be efficiently tackled at the workstation level. ©1999 John Wiley & Sons, Inc. Int J RF and Microwave CAE 9: 490–505, 1999.     

Sensor-based motion planning in three dimensions for a highly redundant snake robot

A strategy is described for real-time motion planning for a highly redundant snake-like robot manipulator operating in a three-dimensional (3D) environment filled with unknown obstacles of arbitrary shape. The robot consists of many (say 30 or 50) links serially connected by universal joints (such a joint allows a 3D rotation of one link relative to the other). The robot's sensors allow it to sense objects in the vicinity of any points of its body. The task is to move the robot's tip point (its head) from its starting position to a specified target position, collision-free for the whole robot's body. To achieve the efficiency necessary for real-time computation, an iterative procedure is proposed which makes use of a unit motion for a single link based on the tractrix curve. This choice also results in automatically achieving a motion that is 'natural' (in that the joint displacements tend to 'die out' in the direction from head to tail) as well as locally optimal.     

Understanding intention of movement from electroencephalograms

Abstract: In this paper, we propose a new framework for understanding intention of movement that can be used in developing non-invasive brain–computer interfaces. The proposed method is based on extracting salient features from brain signals recorded whilst the subject is actually (or imagining) performing a wrist movement in different directions. Our method focuses on analysing the brain signals at the time preceding wrist movement, i.e. while the subject is preparing (or intending) to perform the movement. Feature selection and classification of the direction is done using a wrapper method based on support vector machines (SVMs). The classification results show that we are able to discriminate the directions using features extracted from brain signals prior to movement. We then extract rules from the SVM classifiers to compare the features extracted for real and imaginary movements in an attempt to understand the mechanisms of intention of movement. Our new approach could be potentially useful in building brain–computer interfaces where a paralysed person could communicate with a wheelchair and steer it to the desired direction using a rule-based knowledge system based on understanding of the subject's intention to move through his/her brain signals.