基于简化模型与自适应滤波的车载SINS静基座快速对准

为了实现捷联惯性导航系统(Strap-down Inertial Navigation System,SINS)快速初始对准,根据已有可观测性分析结果,通过理论分析和计算得到了扩展观测量时初始对准系统最优可观测状态量组合,在此基础上简化了对准模型,建立了新的系统方程。针对载车发动机启动或其他情况导致系统噪声无法精确统计,提出了运用基于强跟踪滤波原理的自适应卡尔曼滤波(Kalman Filter,KF)算法抑制滤波发散,加快收敛速度。仿真结果表明运用简化模型和自适应滤波在系统噪声不匹配时具有更快的收敛速度和更高的对准精度,车载实验结果也表明运用简化模型和自适应滤波可以实现快速对准。     

Robust modeling of acoustic paths using a sparse adaptive algorithm

Acoustic impulse response functions are generally sparse in nature and traditionally these are modeled by adaptive finite impulse response (FIR) filters trained using a least mean square (LMS) algorithm. The conventional LMS algorithm is not effective in modeling sparse systems and sparse LMS algorithms have been recently developed to improve the modeling in such scenarios. However, the traditional sparse LMS algorithms are not robust to disturbances at the error sensor and may diverge in some scenarios. With an objective to overcome this limitation of conventional sparse adaptive algorithm, this paper presents a robust sparse adaptive algorithm. The new algorithm has been shown to effectively model sparse systems in a robust manner. In addition, the algorithm has been successfully applied in modeling the acoustic feedback path in a behind the ear digital hearing aid.     

Registration and integration algorithm in structured light three-dimensional scanning based on scale-invariant feature matching of multi-source images

Based on the homography between a multi-source image and three-dimensional (3D) measurement points, this letter proposes a novel 3D registration and integration method based on scale-invariant feature matching. The matching relationships of two-dimensional (2D) texture gray images and two-and-a-half- dimensional (2.5D) range images are constructed using the scale-invariant feature transform algorithms. Then, at least three non-collinear 3D measurement points corresponding to image feature points are used to achieve a registration relationship accurately. According to the index of overlapping images and the local 3D border search method, multi-view registration data are rapidly and accurately integrated. Experimental results on real models demonstrate that the algorithm is robust and effective.     

Real-time application of critical dimension measurement of TFT-LCD pattern using a newly proposed 2D image-processing algorithm

A critical dimension measurement system for TFT-LCD patterns has been implemented in this study. To improve the measurement accuracy, an imaging auto-focus algorithm, fast pattern-matching algorithm, and precise edge detection algorithm with subpixel accuracy have been developed and implemented in the system.The optimum focusing position can be calculated using the image focus estimator. The two-step auto-focusing technique has been newly proposed for various LCD patterns, and various focus estimators have been compared to select a stable and accurate one.Fast pattern matching and subpixel edge detection have been developed for measurement. The new approach, called NEMC, is based on edge detection for the selection of influential points; in this approach, points having a strong edge magnitude are only used in the matching procedure. To accelerate pattern matching, point correlation and an image pyramid structure are combined.Edge detection is the most important technique in a vision inspection system. A two-stage edge detection algorithm has been introduced. In the first stage, a first order derivative operator such as the Sobel operator is used to place the edge points and to find the edge directions using a least-square estimation method with pixel accuracy. In the second stage, an eight-connected neighborhood of the estimated edge points is convolved with the LoG (Laplacian of Gaussian) operator, and the LoG-filtered image can be modeled as a continuous function using the facet model. The measurement results of the various patterns are finally presented.The developed system has been successfully used in the TFT-LCD manufacturing industry, and repeatability of less than 30 nm (3σ) can be obtained with a very fast inspection time.     

非平面图的色数算法

本文对非平面无向简单图的点着色问题进行分析研究后,提出了一个点色数算法.该算法不仅给出了非平面图求点色数的方法,同时也解决了着色方法.并且对算法所涉及的有关性质定理给出了证明.     

基于邻域特征点提取和匹配的点云配准

为解决噪声干扰、数据丢失情况下迭代最近点算法的鲁棒性差、配准精度低等问题,提出一种基于邻域特征点提取和匹配的点云配准方法.首先定义一个由点的k邻域曲率、点与邻近点的法向量内积均值以及邻近点与邻域拟合平面的欧氏距离方差等三部分组成的邻域特征参数,结合在移动最小二乘表面构造的曲率特征参数对点云进行两次特征点提取;其次依据直方图特征定义三个匹配条件,并用双重约束获得正确的匹配点对;最后在配准阶段,采用双向构建k维树的迭代最近点算法实现精确配准.实验结果表明,该算法的配准精度较迭代最近点算法提高了90%以上,并且能够在噪声环境下有效地完成缺失点云的配准,在鲁棒性和精确配准方面有明显优势.     

Measurement Theory in Deutsch’s Algorithm Based on the Truth Values

We propose a new measurement theory, in qubits handling, based on the truth values, i.e., the truth T (1) for true and the falsity F (0) for false. The results of measurement are either 0 or 1. To implement Deutsch’s algorithm, we need both observability and controllability of a quantum state. The new measurement theory can satisfy these two. Especially, we systematically describe our assertion based on more mathematical analysis using raw data in a thoughtful experiment.     

A non-rigid cardiac image registration method based on an optical flow model

According to non-rigid medical image registration, new method of classification registration is proposed. First, Feature points are extracted based on SIFT (Scale Invariant Feature Transform) from reference images and floating images to match feature points. And the coarse registration is performed using the least square method. Then the precise registration is achieved using the optical flow model algorithm. SIFT algorithm is based on local image features that are with good scale, rotation and illumination invariance. Optical flow algorithm does not extract features and use the image gray information directly, and its registration speed is faster. The both algorithms are complementary. SIFT algorithm is used for improving the convergence speed of optical flow algorithm, and optical flow algorithm makes the registration result more accurate. The experimental results prove that the algorithm can improve the accuracy of the non-rigid medical image registration and enhance the convergence speed. Therefore, the algorithm has some advantages in the image registration.     

Evaluation of optimal density weighting for regridding

Density weighting is a necessary component of the regridding algorithm for interpolating nonuniformly sampled data points onto a regular grid. Differing concepts of optimality for the density weighting have been proposed previously. The present study reviews some of these concepts and evaluates the accuracy of different techniques by comparison with the image obtained by a computationally intensive least squares minimization. A variant on one of the techniques is proposed that yields the highest accuracy of those studied.     

An approach of DVL-aided SDINS alignment for in-motion vessel

An in-motion alignment algorithm of strapdown inertial navigation system (SDINS) aided by Doppler velocity log (DVL) is described. As the bias and scale factor errors of DVL cannot be estimated by using conventional algorithm, error model of DVL along axes on local level navigation frame is developed while the ship is sailing at a constant speed. Analysis shows that by using this error model in Kalman filter, the observability of state variable can be improved by the angular motion of the ship. Simulation results show that the DVL measurement error can be estimated precisely and the accuracy of the DVL-aided in-sail alignment can be enhanced greatly by using the proposed approach.     

Companding to improve cochlear-implant speech recognition in speech-shaped noise

Nonlinear sensory and neural processing mechanisms have been exploited to enhance spectral contrast for improvement of speech understanding in noise. The "companding" algorithm employs both two-tone suppression and adaptive gain mechanisms to achieve spectral enhancement. This study implemented a 50-channel companding strategy and evaluated its efficiency as a front-end noise suppression technique in cochlear implants. The key parameters were identified and evaluated to optimize the companding performance. Both normal-hearing (NH) listeners and cochlear-implant (CI) users performed phoneme and sentence recognition tests in quiet and in steady-state speech-shaped noise. Data from the NH listeners showed that for noise conditions, the implemented strategy improved vowel perception but not consonant and sentence perception. However, the CI users showed significant improvements in both phoneme and sentence perception in noise. Maximum average improvement for vowel recognition was 21.3 percentage points (p<0.05) at 0 dB signal-to-noise ratio (SNR), followed by 17.7 percentage points (p<0.05) at 5 dB SNR for sentence recognition and 12.1 percentage points (p<0.05) at 5 dB SNR for consonant recognition. While the observed results could be attributed to the enhanced spectral contrast, it is likely that the corresponding temporal changes caused by companding also played a significant role and should be addressed by future studies.     

三维空间中的偏振光导航方法

提出了偏振光/GPS/SINS组合导航方法。推导了偏振光辅助测姿原理并进行了仿真验证。提出了多模块改善能观度的方法。采用联邦卡尔曼滤波方法实现了组合导航算法,利用Matlab仿真方式分别对使用单偏振光模块和多偏振光模块的组合导航系统的测姿修正效果和能观度改善效果进行了检验。结果表明偏振光辅助测姿方法的引入能够大大改善导航系统的能观度和精度,非平行观测的多偏振光模块可以进一步提高系统性能。     

基于时频分析的多目标盲波束形成算法

针对现有盲波束形成算法适用范围较窄, 多目标信号分离级联模式结构复杂、并联模式稳定性较差等问题, 提出一种基于时频分析的多目标盲波束形成算法. 该算法首先利用时频分析技术给出信号导向矢量的不确定集, 然后优化求解导向矢量的最优估计, 最后利用Capon方法实现多目标信号的并行输出. 理论分析及仿真结果表明, 该算法对信号特性没有特殊要求, 适用性较广, 性能稳定, 且输出信干噪比高于其他盲波束形成算法, 接近于最优Capon波束形成器.     

基于特征点自动匹配的图像拼接方法

提出了一种基于特征点自动匹配的图像拼接算法,采用改进的Harris算子提取特征点,保证了提取的效率和精度,根据互相关的双向匹配实现对应特征点的自动匹配,从而建立参考图像与当前图像的对应点对,最后采用最小二乘方法得到图像间的全局变换参数,实现图像的拼接。     

利用环境噪声互相关实现散射体无源成像

最近研究表明利用环境噪声的互相关可以恢复两点之间的时域格林函数(声脉冲响应),这一原理在文献中被称为格林函数恢复。基于此原理,通过对多个传声器所接收的环境噪声进行互相关处理,获取与散射体相关联的散射波的到达时延信息,结合最小二乘反演算法和改进克希霍夫移位算法,分别获得道路交通噪声场中石柱以及海浪噪声场中塑料桶的空间位置,且其估计结果与实际测量相一致。实验结果表明将环境噪声作为探测信号进行散射体无源成像是可行的。这为设计室内无源声监测系统以及通过海洋环境噪声实现对水中静默目标成像提供了新思路和有益参考。      

An efficient,robust, domain-decomposition algorithm for particle Monte Carlo

A previously described algorithm [T.A. Brunner, T.J. Urbatsch, T.M. Evans, N.A. Gentile, Comparison of four parallel algorithms for domain decomposed implicit Monte Carlo, Journal of Computational Physics 212 (2) (2006) 527–539] for doing domain decomposed particle Monte Carlo calculations in the context of thermal radiation transport has been improved. It has been extended to support cases where the number of particles in a time step are unknown at the beginning of the time step. This situation arises when various physical processes, such as neutron transport, can generate additional particles during the time step, or when particle splitting is used for variance reduction. Additionally, several race conditions that existed in the previous algorithm and could cause code hangs have been fixed. This new algorithm is believed to be robust against all race conditions. The parallel scalability of the new algorithm remains excellent.     

基于粒子群优化算法的伺服系统测试点优选策略研究

针对某型雷达天线伺服系统测试点多,故障诊断需测试较多测试点而导致的故障诊断时间长,效率低的问题,提出了一种基于粒子群优化的测试点优选方法。该方法首先基于系统所需的故障诊断率和所能容忍的故障虚警率构建目标优化函数,其次利用粒子群算法对目标函数进行优化以选择最少的测试点完成故障定位和诊断。该方法避免了对所有测试点的测试,节省了测试时间,可在最短的时间内完成测试点的优选。仿真实验验证了算法的有效性。     

On a recent attempt to define the interpretation basis in the many worlds interpretation of quantum mechanics

David Deutsch's 1985 algorithm to determine the preferred product structure and basis in the many worlds interpretation is examined. His heuristic argument for the conditions appearing in the algorithm is found wanting. The question of the existence and uniqueness of a final solution to his algorithm is discussed. The algorithm is shown to be inadequate to account for certain types of measurement which are, at least in principle, possible.     

嵌入随机多项式的抛物方程不确定声场快速算法

为了得到准确且高效计算起伏海洋介质中随机声场的算法,本文将随机多项式展开嵌入到宽角抛物方程声场计算模型(简称RAM模型)中,发展了一种不确定声场的快速算法.其计算结果比使用嵌入随机多项式的窄角抛物方程准确,计算时间小于作为参考的蒙特卡洛方法.在仿真算例中,随机多项式展开法对声强均值、方差、概率密度的计算准确;在一定的随...     

基于最小角回归与GA-PLS的NIR光谱变量选择方法

近红外(NIR)光谱一般具有较多的波长变量数,对其直接或间接地进行变量选择是提高模型稳定性能及预测性能的关键。最小角回归(LAR)是一种相对较新和有效的机器学习算法,常用于进行回归分析和变量选择。面向光谱建模应用,提出一种LAR结合遗传偏最小二乘法(GA-PLS)的变量选择方法,可有效筛选出少数特征波长点。首先在全光谱区利用LAR消除变量间的共线性得到初筛波长点,然后用GA-PLS对LAR筛选出的波长点进一步优选从而得到最终建模用的特征波长点。为验证本文方法的有效性,以药片和汽油的近红外光谱回归分析作为应用案例,对原光谱进行预处理后,采用该方法进行变量筛选,然后分别建模其中的活性成分含量和C10含量。结果显示,在这两个应用中,最终优化得到的特征波长点数均只需七个,而两者的预测决定系数R2_p分别达到0.933 9和0.951 9,与全光谱、无信息变量消除法(UVE)和连续投影算法(SPA)等方法相比,特征波长点更少,同时R2_p和预测均方根误差RMSEP值更优。因此,LAR结合GA-PLS,能有效地从近红外光谱中选择出信息变量从而减少建模波数,提高预测精度,拥有较好的模型解释性。该方法可为特定领域的专用光谱仪设计提供有效的波长筛选工具。