一种音频测距信号到达时刻估计方法

对音频测距信号到达时刻的精确估计是利用音频信号实现远距离无线传感器网络节点定位的关键。研究比较了几种常用的音频测距信号到达时刻估计方法,并提出了一种基于数字整流处理的到达时刻估计方法。它包括信噪比增强、去除直流分量、全波整流、低通滤波、到达时刻估计等过程。该方法在以dsPIC6014A单片机为控制器的节点进行了实验验证,测试结果表明:处理4 096点(12位量化)数据的计算时间约为1.5 s(10MHz时钟),30m距离处的时间值估计误差小于3.5%。     

基于并行相关的实时时差估计器设计与实现

从相关时差估计的基本原理出发,提出了一种并行时域相关结构,基于这种并行结构设计实现了一种简单高效的时差估计器.与传统频域相关时差估计器相比,这种时差估计器的主要优点是提高了运算效率,运算周期大为缩短,可以满足实时高精度时差估计的需求,同时结构简单,硬件资源开销小,易于设计实现.实际测试结果验证了上述结论.     

Retrial queuing system with Markovian arrival flow and phase-type service time distribution

We consider a multi-server queuing system with retrial customers to model a call center. The flow of customers is described by a Markovian arrival process (MAP). The servers are identical and independent of each other. A customer’s service time has a phase-type distribution (PH). If all servers are busy during the customer arrival epoch, the customer moves to the buffer with a probability that depends on the number of customers in the system, leaves the system forever, or goes into an orbit of infinite size. A customer in the orbit tries his (her) luck in an exponentially distributed arbitrary time. During a waiting period in the buffer, customers can be impatient and may leave the system forever or go into orbit. A special method for reducing the dimension of the system state space is used. The ergodicity condition is derived in an analytically tractable form. The stationary distribution of the system states and the main performance measures are calculated. The problem of optimal design is solved numerically. The numerical results show the importance of considering the MAP arrival process and PH service process in the performance evaluation and capacity planning of call centers.     

基于前车与经验数据的车辆到站时间预测模型

公交车辆运行经验数据体现了到站时间的一般性规律,前车数据反映了到站时间的实时性。提出一种基于前车与经验数据的公交车辆到站时间预测模型。在该模型中对站点间路段行驶时间及站点停留时间区分了高峰期和非高峰期,站点间的延时时间考虑了不同方向红灯等待时间的区别以及斑马线的影响。用杭州公交104路公交车的数据对预测模型进行了验证,结果表明,该预测模型具有较高的预测精度,能够较为准确地预测公交车辆到站时间。     

基于Spark与粒子滤波算法的公交到站时间预测系统

针对公交车到站时间预测准确性不高的问题，选用具有流式计算特点的粒子滤波（PF）算法，建立了一个公交到站时间预测模型。为更好地解决使用PF算法过程中存在的预测误差及粒子优化选择问题，通过引入上一趟公交车的行驶速度和构造观测值的方法对预测模型进行改进，使之具有更贴近实际路况的公交到站时间预测精度，并且能同时预测多个公交到达时间。基于该模型和Spark平台实现了一套公交到站时间实时预测软件系统，所有到站时间预测结果与实际相比，平峰的最大绝对误差为207 s，平均绝对误差为71.67 s；高峰的最大绝对误差为270 s，平均绝对误差为87.61 s，而预测结果的平均绝对误差在2 min以内是公认的理想结果。实验结果表明，所提模型及实现系统能准确预测公交到站时间，满足乘客实际需求。     

基于DBSCAN算法和多源数据的缺失公交到站数据修补

针对缺失公交到站信息修补方法考虑因素较少、准确度低、鲁棒性差的现状,提出了基于DBSCAN算法和多源数据的缺失公交到站数据修补方法。该方法使用公交全球定位系统（GPS）、公交集成电路卡（IC）等多源数据进行缺失到站信息的修补。对于缺失的到站名称、到站经纬度数据,用已有完整到站数据和静态线路信息关联分析进行修补。对于缺失的到站时刻数据,则按以下步骤进行修补：首先,对每一个缺失数据站点与其最近的未缺失数据站点,将这两站点间历史完整到站数据的行程时间和班次时序进行基于DBSCAN算法的聚类;其次,判断研究班次的两个相邻的数据完整的班次所属簇是否为同一个簇,若为同一个簇则不作改变,否则将两个簇合并;最后,将簇中点对应最大行程时间作为缺失行程时间判断是否有乘客在该站点上车刷卡,若有则由乘客开始刷卡时刻推算到站时刻,若无则将簇中点对应最大、最小行程时间的均值作为缺失行程时间推算到站时刻。以厦门市公交到站数据为例,在缺失到站名称、经纬度修补中,基于GPS数据聚类的方法、基于极大概率估计的方法和所提方法皆可进行100%的修补;在缺失到站时刻修补中,所提方法的平均相对误差比两种对比方法分别低0.0301%和0.0004%,相关系数比对比方法分别高0.005和0.0075。实验结果表明,所提算法在缺失公交到站数据修补中能有效提高修补的准确度,降低缺失站点个数变化对于准确度的影响。     

A minimal representation of Markov arrival processes and a moments matching method

The paper investigates the problem of minimal representation of Markov arrival processes of order n (MAP(n)). The minimal representation of MAPs is crucial for developing effective fitting methods. It seems that all existing MAP fitting methods are based on the , representation which is known to be redundant. We present the minimal number of parameters to define a MAP(n) and provide a numerical moments-matching method based on a minimal representation.

The discussion starts with a characterization of phase type (PH) distributions and then the analysis of MAPs follows a similar pattern. This characterization contains essential results on the identity of stationary behaviour of MAPs and on the number of parameters required to describe the stationary behaviour.

The proposed moments matching method is also applicable for PH distributions. In this case it is a unique method that fits a general PH distribution of order n based on 2n−1 parameters.     

Joint estimation of time delays and directions of arrival using proper set of antenna elements of a high-order antenna array

In this work, we investigate the accuracy and complexity deviation between using all or selected antenna elements of a massive MIMO array for source localization. In addition, we address the problem of highly resolving the propagation time delay, and the angles of arrival (azimuth and elevation) associated with signals in multipath communication channels for many location-based services and three-dimensional (3D) beamforming. The 3D unitary matrix pencil (3D UMP) algorithm is enhanced and applied in a new way to evaluate these parameters simultaneously from the estimated space channel frequency response (S-CFR) using wideband orthogonal multicarrier signals and uniform rectangular array (URA). Furthermore, the 2D UMP is enhanced to estimate the unknown parameters of wideband signals impinging on 8 different array configurations that are structured as combinations of uniform linear arrays (ULAs). It is not necessary to use all antenna elements of a high-order antenna array for source localization. Due to the dependency on mobile unit location, the phase uncertainties and the deviation of received signal strength between array elements, using the proper set of antenna elements can provide a comparable accuracy and a considerable reduction in the computational complexity of the localization algorithm. The computational complexity is further reduced by exploiting real computation and similar eigen-structure property, and using a priori information of wireless positioning. The IEEE 802.11ac system parameters are used in our experiments.     

Automatic detection and picking of P-wave arrival in locally stationary noise using cross-correlation

Accurate picking of seismic wave arrivals plays a central role in many seismic studies. Nowadays, automatic-picking schemes are indispensable due to the large amount of digital data recorded by wide seismic networks and the need for rapid analysis. The increase of computer power allows the development of more sophisticated algorithms. Many of these algorithms are based on finding change in power, envelope, or statistical properties of the seismic signal in time or frequency domain. But, they have often ignored kind and characteristics of seismic background noise at each recording site. Such information may improve the detector and picker performance if it is taken into account. The aim of this study is to propose a method for picking the arrival of the P-wave in locally stationary seismic background noise. In fact, through analysis of background noise, we have found that it shows local regularity at seismically quiet sites. Therefore, if the background noise satisfies local stationarity, it is evident that occurrence of a seismic event will violate this stationarity. The transition from stationarity to non-stationarity is exploited to pick the P-arrival. To quantify the degree of signal stationarity, we use the normalized cross-correlation function. This method can detect and pick changes both in frequency and amplitude. Thus, it provides robust detection and picking of P-phase onsets even when the signal-to-noise ratio is low. Experimental results on real seismic data, consisting of local seismic events of different signal-to-noise ratios, and comparison with commonly used methods in practice demonstrate the reliable performance of the proposed method.     

Error associated with the direction of arrival estimation in the presence of material bodies

In many adaptive processing it is assumed that the direction of arrival of (DOA) of the signals is known. For a radar problem this is true as we know along which direction we transmitted the beam and therefore we expect the radar return to be arriving from that direction. However, this assumption is questionable when there are material bodies near or along its path. Here, we address the question as to what happens to the direction of propagation when the electromagnetic wave encounters a material body near or along its path for the noise free case. Thus the objective is to calculate the error associated with the prediction of DOA when the free space is not empty. We illustrate the error associated with the estimation of the DOA when there is a perfect electric conducting (PEC) sphere and a dielectric sphere along/near the path of propagation. A PEC and dielectric will diffract the incident electromagnetic energy. We evaluate the scattered far fields at a few points away from the obstacle. From the measured field points we predict the DOA of the signal of interest. The simulations have been carried out using an electromagnetic simulator and a DOA estimation algorithm using the Matrix Pencil Method. The examples deal with the case of both one- and two-dimensional antenna arrays and how they interpret the diffracted signals.     

Genetic algorithm for minimizing the total weighted completion time scheduling problem with learning and release times

This paper considers a single-machine problem with the sum-of-processing time based learning effect and release times. The objective is to minimize the total weighted completion times. First, a branch-and-bound algorithm incorporating with several dominance properties and two lower bounds are developed for the optimal solution. Then a genetic heuristic-based algorithm is proposed for a near-optimal solution. Finally, a computational experiment is conducted to evaluate the performances of the proposed algorithms. The results show that the branch-and-bound algorithm can solve instances up to 15 jobs, and the average error percentage of the genetic heuristic algorithm is less than 0.105%.     

Pointwise stabilisation of a string with time delay in the observation

Pointwise stabilisation is proposed in this paper for a string equation where the observation signal is subject to a time delay. Different from the boundary control, the feedback stabiliser is acting at the middle joint of the string. Well-posedness of the open-loop system and solvability of the observer are shown first. An observer system is then designed to estimate the state at the time interval when the observation is available, and a predictor system is designed to predict the state at the time interval when the observation is not available. Pointwise output feedback controller is introduced to make the closed-loop system asymptotically stable for the non-smooth initial values and exponentially stable for the smooth initial values, respectively. Simulation results demonstrate that the output feedback based on the observer and predictor effectively stabilises the pointwise control system with time delay.     

基于灰色关联度和SVM舰船设备维修费用预测

维修费用是舰船装备费用的重要组成部分,维修费用和影响费用的驱动因子之间直接的关系式很难确定,运用支持向量机回归可以很好的做到对维修费用的建模预测。为了解决支持向量机计算速度慢,效率低的问题,提出灰色关联度理论对费用相关费用驱动因子进行预处理,测试结果表明提高了SVM的效率,对SVM的泛化能力也有所提高。     

Matrix pencil method for simultaneously estimating azimuth and elevation angles of arrival along with the frequency of the incoming signals

In this paper we describe a method for simultaneously estimating the direction of arrival (DOA) of the signal along with its unknown frequency. In a typical DOA estimation problem it is often assumed that all the signals are arriving at the antenna array at the same frequency which is assumed to be known. The antenna elements in the array are then placed half wavelength apart at the frequency of operation. However, in practice seldom all the signals arrive at the antenna array at a single pre-specified frequency, but at different frequencies. The question then is what to do when there are signals at multiple frequencies, which are unknown. This paper presents an extension of the matrix pencil method to simultaneously estimate the DOA along with the operating frequency of each of the signals. This novel approach involves approximating the voltages that are induced in a three-dimensional antenna array, by a sum of complex exponentials by jointly estimating the direction of arrival (both azimuth and elevation angles) along with the carrier frequencies of multiple far-field sources impinging on the array by using the three-dimensional matrix pencil method. The matrix pencil method is a direct data domain method for approximating a function by a sum of complex exponentials in the presence of noise. The variances of the estimates computed by the matrix pencil method are quite close to the Cramer–Rao bound. Finally, we illustrate how to carry out the broadband DOA estimation procedure using realistic antenna elements located in a conformal array. Some numerical examples are presented to illustrate the applicability of this methodology in the presence of noise. It is shown that the variance decreases as the SNR increases. The Cramer–Rao bound for the estimators are also provided to illustrate the accuracy and the computational efficiency of this new methodology.     

Joint direction of arrival estimation and array calibration for coprime MIMO radar

Compared to large-scale MIMO radar, coprime MIMO radar can achieve approximate estimation performance with reduced antenna number. In this paper, joint direction of arrival (DOA) estimation and array calibration for coprime multiple-input multiple-output (MIMO) radar is considered, and an iterative method for the estimations of DOA and array gain-phase errors is proposed. Based on the received data structure of coprime MIMO radar, trilinear decomposition is firstly adopted to obtain the estimations of transmit and receive direction matrices, which are perturbated by the gain-phase errors. Through equation transformation, the un-perturbated direction matrices and gain-phase errors can be iteratively updated based on Least squares (LS). Finally, the unique DOA estimation is determined from the intersection of transmit and receive direction matrices. The proposed algorithm achieves better DOA estimation and array calibration performance than other methods including estimation of signal parameters via rotational invariance techniques (ESPRIT)-like algorithm, multiple signal classification (MUSIC)-like algorithm and joint angle and array gain-phase error estimation (JAAGE) method, and it performs close to the method with ideal arrays. Multiple simulation results verify the algorithmic effectiveness of the proposed method.     

改进遗传算法准确估计cdma2000-1X 网络中的信号到达方位

针对cdma2000-1X网络中无线信号的特点和无源定位的需要,通过将N阶多项式平滑拟合及加权修正的思想融合到遗传算法中,提出了一种改进的遗传算法来消除NLOS误差和多径传播误差对载干比的影响。不仅避免了遗传算法"早熟"的发生,而且还可以根据实际情况灵活改变搜索精度,使算法搜索达到全局最优,从而实现精确估计信号到达方位的目的。经过场外试验和MATLAB仿真验证该算法可以达到比较好的效果。     

基于单次反射的井下单基站DOA和TOA定位方法

针对井下巷道单基站定位系统中无线信号受多径效应、非视距传播影响导致定位误差较大的问题,提出了一种基于单次反射的到达方向(DOA)和到达时间(TOA)的联合估计定位方法。该方法利用视距路径和多条单次反射路径的TOA估计值构建以基站原点和单次反射点为焦点的双曲线,利用DOA估计值构建直线,从而建立含有连续位置信息的二元多次估计方程组,通过计算直线与双曲线的交点得到移动目标的精确位置。仿真结果表明,该方法较视距直接定位方法的定位精度有较大提高,且当单次反射路径为3条时即可达到较高的定位精度。     

蜂窝网无线定位技术在铁路场景下的应用

针对蜂窝网络定位技术定位精度不高和在铁路实际中难以应用的缺点,提出一种新的列车定位方法.方法的核心是将速度传感器和蜂窝网的定位参数处理为若干列车可能的位置区域,并计算区域中列车位置出现的概率,以所有位置中出现概率最大为优化目标,建立列车定位的误差优化模型.在此基础上进一步引入遗传粒子群优化算法对模型进行求解,并用Matlab仿真.仿真结果表明:在复杂的铁路环境中,该定位方法对不同来源的误差有很好的吸收作用,是一种有效的定位方法.     

Estimators of sensitivity and specificity in the presence of verification bias: A Bayesian approach

Verification bias can occur if some of the patients with test results are not selected to receive the gold standard procedure. Unverified cases frequently are not suggestive to be positives. Consequently, the set of verified cases overestimates the number of true positives and underestimates the number of true negatives. The sensitivity and specificity estimates based only on the patients with verified disease are often biased. In this article we derive estimators for sensitivity and specificity not subject to verification bias using a Bayesian approach. Marginal posterior densities of all parameters are estimated using the Gibbs sampler algorithm. An application to the study of accuracy of Hybrid Capture II in the diagnosis of cervical intraepithelial neoplasia grades 2 and 3 illustrates the proposed methodology.