文献翻译-基于自适应滤波器的组合导航信息融合
英文翻译
系别
专业名称
班级
学生姓名
学号
指导教师
Information Fusion of Integrated Navigation Based on
Self-adaptive Filter
Abstract- In order to realize high accuracy and excellent reliability of navigation system, information fusion technology of integrated navigation based on self-adaptive filter is researched in this paper. Inertial navigation system (INS), global navigation satellite system (GNSS),synthetic aperture radar (SAR) and barometric altimeter (BA) are taken to construct INS/GNSS/SARIBA integrated system.INS is regarded as the primary navigation equipment, and other systems are aided navigation equipments. Firstly, errors of INS, GNSS, SAR and BA are modeled and chosen as system states of integrated navigation. Based on self-adaptive filter algorithm, output information of INS and GNSS are fused in INS/GNSS integrated navigation filter, and output information of INS, SAR and BA are fused in INS/SARIBA integrated navigation filter. Then the federated filter frame is designed, and estimations of system states from INS/GNSS and INS/SARIBA local filters are fused once more in the master filter independently.Consequently global optimal estimations of system states are given by the master filter, which are used to correct errors of INS. Simulation results show that,position accuracy of INS/GNSS/SARIBA integrated navigation reaches±1l.6m,attitude accuracy reaches ±0.52,velocity accuracy reaches ±0.14m/s, and its reliability is very excellent when noise statistics characteristics of some navigation equipment are variational in the navigation process.
Keywords-information fusion; integrated navigation; self-adaptive filter; inertial navigation system; global navigation satellite system; synthetic aperture radar; barometric altimeter
I.INTRODUCTION
The accuracy and reliability of navigation system are more and more important for the modern flight task.Integrated navigation technology based on information fusion is an available approach to improve the accuracy and reliability of the navigation system . By fusing navigation information from all sorts of navigation equipments, integrated navigation can take full advantage of each non-similar navigation sub-systems. Based on Wiener filtering, Kalman filtering,self-adaptive filtering and other information fusion technologies, the optimal estimates of navigation parameters can be obtained.
At present, inertial navigation system (INS) is widely used in spaceflight, aviation and other fields. It has strong anti-interference capability, and can provide position,attitude, velocity and other parameters. But its errors accumulate with navigation time. Global navigation satellite system (GNSS) is the most precise navigation system in the world, but satellite signals of GNSS are subject to be interfered or shielded [2]. Similarly, other modern navigation systems also have several disadvantages. However, accuracy, reliability and anti-interference capability of navigation system become more and more important for the modern aircraft. In order to realize higher accuracy and more excellent performance, it is necessary to take full advantage of each navigation system by information fusion technology.INS, GNSS, synthetic aperture radar (SAR) and barometrical time ter(BA)are taken to construct INS/GNSS/SARIBA integrated navigation system by information fusion technology in this paper. INS is regarded as the primary navigation equipment, and other systems are aided navigation equipments. Noise statistics characteristics of these aided navigation equipments are probably uncertain or variational during the navigation process, which will lower the accuracy of Kalman filter [3], so self-adaptive filter is adopted to design local filters of integrated navigation. In order to obtain global optimal estimations of system states, the federated filter frame and
global optimal information fusion algorithm are designed. Thus high accuracy, strong reliability and good anti-interference capability are realized in INS/GNSS/SARIBA integrated navigation system.
In this integrated navigation system, East-North-Up geography coordinate is chosen as navigation coordinate. INS, GNSS, SAR and BA are all mounted on the aircraft. INS outputs the position, velocity and attitude of the aircraft, GNSS output the position and velocity, SAR outputs the latitude and longitude of the position, and BA outputs the altitude. Errors of INS, GNSS, SAR and BA are chosen as system states of integrated navigation. The difference between position outputs of INS and GNSS, and the difference between velocity outputs of INS and GNSS are taken as the measurement of INS/GNSS integrated navigation. At the same time, the difference between position outputs of INS and SAR, and the difference between altitude outputs of INS and BA are taken as the measurement of INS/SARIBA integrated navigation. Then two measurements are sent to corresponding local filters, and two local estimations of system states are obtained by information fusion algorithm. Two local estimations are sent to the master filer, and then global optimal estimations of system states are given in the master filter by the global Optimal Fusion Algorithm. Finally, global optimal estimations are used to correct errors of INS, and outputs of corrected INS are regarded as outputs of INS/GNSS/SARIBA integrated navigation system. So the above information fusion scheme in integrated navigation is described as follows:
In the design of integrated navigation, errors of navigation equipments are taken as system states, so errors of INS, GNSS, SAR and BA must be analyzed and modeled firstly. Errors of inertial instrument are the main error sources of INS. After calibration and compensation, random drifts are reserved in inertial instrument errors, which including constant drifts of gyro white noises of gyros constant biases of accelerometers and white noises ofaccelerometers where i = x, y, Z denote the X, Y and Z axes of the aircraft. And thus inertial instrument errors generate other errors of INS, including analytic platform attitude error, velocity error and position error. Model equations of above errors are provided in many references, so unnecessary details are not given in this paper. GNSS is the most precise navigation system in the world, and its positioning accuracy reaches several dozens meters. So errors of GNSS are usually considered as white noise processes, and not chosen as system states of integrated navigation So system states of INS/GNSS integrated navigation include inertial instrument errors, analytic platform attitude errors of INS,velocity errors.According to error model of INS, state equation of INS/GNSS integrated navigation can be written as Based on (2) and (5), the information fusion of INS/GNSS integrated navigation can be accomplished by Kalman filter usually. However, satellite signals of GNSS are subject to be influenced during the navigation process, and noise statistics characteristics of GNSS are probably uncertain or variational, which will lower the accuracy of Kalman filter obviously [5]. So the following simplified Sage-Husa self-adaptive filtering algorithm is taken as the information fusion algorithm in INS/GNSS integrated navigation.
SAR is a sort of imaging radar with high resolution.Among its wide-range applications, SAR mounted on the aircraft can realize navigation function by image processing and matching technology. At present, SAR can output the latitude and longitude of the position of the aircraft, and its accuracy reaches several dozens meters.
In matching navigation of SAR, antenna attitude errors of SAR are the main error sources. Thus antenna attitude errors of SAR must be considered and modeled. Once SAR is mounted on the aircraft, its antenna attitude errors usually can be
considered as random constant. So antenna attitude errors If/i can be modeled as follows.
Barometric altimeter (BA) is a sort of precise equipment for measuring the altitude. It can calculate the altitude of the carrier by measuring the barometric value. By analyzing work principle and actual output data of BA, it is found that altitude error of BA is subject to be influenced by environment temperature and wind power [6], and it can be described as the combination of random walk and white noise. So altitude error of BA can be modeled as follow.
As the traditional navigation system can’t satisfy the requirements of the navigating position of the Autonomous Underwater Vehicles(AUV),especially in the long time and long range travel. Based on the practical thing and the developments of navigation technique,we design the Integrated Navigation System of the AUV in this paper. Using timing introducing GPS navigation information,we solve the question of the positional error accumulated with the time due to strapdown inertial navigation system(SINS) and doppler Navigation System.And by means of simulation study,the result indicates that the design method in this paper is proper,which can increase the positioning accuracy of UA V in the long time and long range travel.
The main research work is done as follows:
Design the strapdown inertial navigation system of AUV. The basic navigation algorithm of SINS is inferenced detailedly.We make the formula derivation of the basic position, speed and attitude of the strapdown inertial navigation,and analysis the error characteristics of SINS systematically.And at the same time we establish its error model equation. Research the composition of GPS,the basic principle of navigation position一setting,and the analysis of data error.Aimed at the different error source,this paper establish the variant basic error model.This paper detailedly Introduce the Doppler velometer, electric gyrocompass and strapdown flux一gate azimuth finder,and so on,which compose the Doppler navigation system.Research the operating principle and error source of the subsystem. Deduce the error formula,and establish its error model.
Design of the Integrated Navigation system of AUV. Based on the various
navigation system error,aimed at the navigation characteristic in the long time and long range travel,by means of the vehicle receiving the GPS Navigation information by timing rise,we design the Integrated Navigation System.The simulation result shows that after timing introducing GPS Navigation information this navigation system can increase the positioning accuracy evidently,and overcome the question of the positional error accumulated with the of time in SINS/DVL Integrated Navigation.
Simulation result figures show that, INS/GNSS/SARIBA integrated navigation method based on self-adaptive filter realizes high accuracy and excellent reliability. Figure 2 shows that, position accuracy of INS/GNSS/SARIBA integrated navigation reaches ±11.6m. Figure 3 shows that, the heading, pitch and roll accuracy of integrated navigation all reach ±0.52'. Figures 4 shows that, velocity accuracy of integrated navigation reaches ±0.14m/s. According to the above simulation result figures, it can also be found that, although noise statistics characteristics of navigation equipments are variational obviously in the navigation process, INS/GNSS/SARIBA integrated navigation based on self-adaptive filter still achieves high and stable accuracy. So it can be concluded that, INS/GNSS/SARIB integrated navigation based on self-adaptive filter not only has high accuracy, but also has excellent reliability and anti-interference capability.
基于自适应滤波器的组合导航信息融合
摘要——本文讲述的是为了实现精度高和优秀的导航系统的可靠性，信息融合技术基于自适应滤波器的组合导航研究。惯性导航系统(INS),全球导航卫星系统(GPS)，合成孔径雷达(SAR)和气压测高计(BA)是采取来构造INS / GNNS / SARIBA集成航系统。INS被视为主要的导航设备,和其他系统辅助导航设备。首先，INS的误差，GNNS，SAR和英航建模和系统状态的选择组合导航。基于自适应滤波器算法输出信息的INS和GNSS融合在INS / GNNS/INS组合导航滤波器和输出信息，特别行政区和英航融合在INS / SARIBA组合导航滤波器然后联邦滤波器框架设计，估计系统状态的INS / GPS和INS / SAR/IBA当地的过滤器融合一次更多的在独立性的主过滤器。因此全球系统状态的最优估计，由主过滤器，用来纠正错误Ins。模拟结果显示那位置精度的INS / GPS / SAR/IBA集成导航到达±1 l.6m，态度精度达到±0.52.速度精度达到±0.14 m / s，其可靠性是非常优秀的，当噪声统计数据一些设备变分的特征导航过程。
关键字——信息融合，组合导航，自我自适应滤波器、惯性导航系统、全球导航卫星系统、合成孔径雷达、气压测高计。
一绪论
导航系统的精度和可靠性是越来越重要的现代飞行任务。基于信息集成导航技术融合是提高准确性和一个可用的方法导航系统的可靠性。通过融合导航信息从各种导航设备，组合导航可以充分利用每个非类似的导航子系统。基于维纳滤波，卡尔曼过滤，自适应过滤和其他信息融合技术，最优的估计导航参数可以获得。目前，惯性导航系统(INS)是广泛应用于航天、航空等领域。它有很强的抗干扰能力，可以提供位置，态度、速度和其他的参数。但它的错误积累与导航。全球导航卫星系统(GPS)，最精确的导航系统世界，但GPS卫星信号的主题干扰或屏蔽。同样，其他现代导航系统也有几个缺点。然而,准确性，可靠性和抗干扰能力的导航对现代系统变得越来越重要飞机。为了实现更高的准确性和更优秀的性能，有必要充分利用每个导航系统的信息融合技术。GPS /INS，合成孔径雷达(SAR)和气压测高计(BA)是采取来构造INS / GPS / SAR/IBA集成导航系统通过信息融合技术。INS被认为作为主要的导航设备，和其他系统辅助导航设备。噪声统计特性这些辅助导航设备可能是不确定的或在导航过程中变分，卡尔曼滤波的精度低，因此自适应过滤器采用集成设计当地过滤器导航。为了获得全局最优估计系统状态,联邦过滤器框架和全局最优信息融合算法设计。因此,高准确性，可靠性强，抗干扰好功能实现在INS / GPS / SAR/IBA集成导航系统。
在这个组合导航系统，East-North-Up地理坐标是选为导航坐标。INS /GPS/ SAR和英航都安装在飞机。INS输出位置、速度和态度的飞机，GPS输出位置和速度，特别行政区输出位置的纬度和经度,英航输出的高度。错误的INS/GPS /SAR和英航选择作为组合导航的系统状态。的不同位置输出INS和GPS，速度输出INS和GPS的区别被测量的INS / GPS集成导航。同时，之间的区别位置输的INS和特别行政区,区别之间高度INS和英航作为输出测量的INS / SAR/IBA 组合导航。然后两个测量被发送到相应的地方过滤器，和两个地方得到系统状态的估计信息融合算法。两个地方估计发送到主编档人员，然后全局最优估计系统状态的主过滤器由全球最优融合算法。最后,全球最优INS的估计是用来纠正错
图像处理中值滤波器中英文对照外文翻译文献
中英文资料对照外文翻译 一、英文原文 A NEW CONTENT BASED MEDIAN FILTER ABSTRACT In this paper the hardware implementation of a contentbased median filter suitabl e for real-time impulse noise suppression is presented. The function of the proposed ci rcuitry is adaptive; it detects the existence of impulse noise in an image neighborhood and applies the median filter operator only when necessary. In this way, the blurring o f the imagein process is avoided and the integrity of edge and detail information is pre served. The proposed digital hardware structure is capable of processing gray-scale im ages of 8-bit resolution and is fully pipelined, whereas parallel processing is used to m inimize computational time. The architecturepresented was implemented in FPGA an d it can be used in industrial imaging applications, where fast processing is of the utm ost importance. The typical system clock frequency is 55 MHz. 1. INTRODUCTION Two applications of great importance in the area of image processing are noise filtering and image enhancement [1].These tasks are an essential part of any image pro cessor,whether the final image is utilized for visual interpretation or for automatic an alysis. The aim of noise filtering is to eliminate noise and its effects on the original im age, while corrupting the image as little as possible. To this end, nonlinear techniques (like the median and, in general, order statistics filters) have been found to provide mo re satisfactory results in comparison to linear methods. Impulse noise exists in many p ractical applications and can be generated by various sources, including a number of man made phenomena, such as unprotected switches, industrial machines and car ign ition systems. Images are often corrupted by impulse noise due to a noisy sensor or ch annel transmission errors. The most common method used for impulse noise suppressi on n forgray-scale and color images is the median filter (MF) [2].The basic drawback o f the application of the MF is the blurringof the image in process. In the general case,t he filter is applied uniformly across an image, modifying pixels that arenot contamina ted by noise. In this way, the effective elimination of impulse noise is often at the exp ense of an overalldegradation of the image and blurred or distorted features[3].In this paper an intelligent hardware structure of a content based median filter (CBMF) suita ble for impulse noise suppression is presented. The function of the proposed circuit is to detect the existence of noise in the image window and apply the corresponding MF
毕业论文外文文献翻译-数据库管理系统的介绍
数据库管理系统的介绍 Raghu Ramakrishnan1 数据库（database,有时拼作data base）又称为电子数据库，是专门组织起来的一组数据或信息，其目的是为了便于计算机快速查询及检索。数据库的结构是专门设计的，在各种数据处理操作命令的支持下，可以简化数据的存储，检索，修改和删除。数据库可以存储在磁盘，磁带，光盘或其他辅助存储设备上。 数据库由一个或一套文件组成，其中的信息可以分解为记录，每一记录又包含一个或多个字段（或称为域）。字段是数据存取的基本单位。数据库用于描述实体，其中的一个字段通常表示与实体的某一属性相关的信息。通过关键字以及各种分类（排序）命令，用户可以对多条记录的字段进行查询，重新整理，分组或选择，以实体对某一类数据的检索，也可以生成报表。 所有数据库（最简单的除外）中都有复杂的数据关系及其链接。处理与创建，访问以及维护数据库记录有关的复杂任务的系统软件包叫做数据库管理系统（DBMS）。DBMS软件包中的程序在数据库与其用户间建立接口。（这些用户可以是应用程序员，管理员及其他需要信息的人员和各种操作系统程序）。 DBMS可组织，处理和表示从数据库中选出的数据元。该功能使决策者能搜索，探查和查询数据库的内容，从而对在正规报告中没有的，不再出现的且无法预料的问题做出回答。这些问题最初可能是模糊的并且（或者）是定义不恰当的，但是人们可以浏览数据库直到获得所需的信息。简言之，DBMS将“管理”存储的数据项，并从公共数据库中汇集所需的数据项以回答非程序员的询问。 DBMS由3个主要部分组成：（1）存储子系统，用来存储和检索文件中的数据；（2）建模和操作子系统，提供组织数据以及添加，删除，维护，更新数据的方法；（3）用户和DBMS之间的接口。在提高数据库管理系统的价值和有效性方面正在展现以下一些重要发展趋势； 1.管理人员需要最新的信息以做出有效的决策。 2.客户需要越来越复杂的信息服务以及更多的有关其订单，发票和账号的当前信息。 3.用户发现他们可以使用传统的程序设计语言，在很短的一段时间内用数据1Database Management Systems( 3th Edition ),Wiley ,2004, 5-12
IIR数字滤波器的设计外文文献以与翻译
IIR Digita Filter Design An important step in the development of a digital filter is the determination of a realizable transfer function G(z) approximating the given frequency response specifications. If an IIR filter is desired,it is also necessary to ensure that G(z) is stable. The process of deriving the transfer function G(z) is called digital filter design. After G(z) has been obtained, the next step is to realize it in the form of a suitable filter structure. In chapter 8,we outlined a variety of basic structures for the realization of FIR and IIR transfer functions. In this chapter,we consider the IIR digital filter design problem. The design of FIR digital filters is treated in chapter 10. First we review some of the issues associated with the filter design problem. A widely used approach to IIR filter design based on the conversion of a prototype analog transfer function to a digital transfer function is discussed next. Typical design examples are included to illustrate this approach. We then consider the transformation of one type of IIR filter transfer function into another type, which is achieved by replacing the complex variable z by a function of z. Four commonly used transformations are summarized. Finally we consider the computer-aided design of IIR digital filter. To this end, we restrict our discussion to the use of matlab in determining the transfer functions. 9.1 preliminary considerations There are two major issues that need to be answered before one can develop the digital transfer function G(z). The first and foremost issue is the development of a reasonable filter frequency response specification from the requirements of the overall system in which the digital filter is to be employed. The second issue is to determine whether an FIR or IIR digital filter is to be designed. In the section ,we examine these two issues first .
现代通信技术作业翻译
自干扰消除在5G和超5G中的应用 Steven Hong, Joel Brand, Jung Il Choi, Mayank Jain, Jeff Mehlman, Kumu Networks Sachin Katti, and Philip Levis, Kumu Networks and Stanford University 摘要：自干扰消除使得一个在无线网络设计中的长期的基本假设变得无效，这 个假设是无线电设备只能工作在同一频道的半双工模式下。实现真正的同频全双工，有效的加倍了频谱效率，SIC大大简化了频谱管理。它不但放弃了像TD-LTE 一样的过时的整个系统，而且使得未来的网络能够利用零散的频谱，这是一个将继续使5G网络恶化的紧迫的全球问题。自干扰消除提供了能够去补偿和维持5G 技术向密集的异构网络演化的潜力，并且能够被用在无线通信系统的多个方面，包括增加链路容量、频谱虚拟化、任意分割双工（ADD）、新的中继方案和增强的干扰协调。由于它的基本特点的价值，自干扰消除将会对5G网络和超5G有很大的影响。 引言 由于干扰的原因，无线电收发机在同样的频带下去接收和发射一般是并不可能的。(Andrea Goldsmith,无线通信【1】) 以上的引用获得了一个在无线系统设计中的长期的假设：无线电收发器不得不在同一频道下工作在半双工模式（例如，发送或者接收的，但不是同时发生）。最近的工作一直在试图否定这个假设。斯坦福【2-5】和莱斯【6】大学的研究者和几个其他在业界【7】和学术界【8,9】的组织都曾经提出多种多样的设计去建立同频全双工的无线电传播模式。如果可能，全双工会对网络部署有巨大的影响；例如，它能够使得蜂窝网的频谱效率加倍。今天LTE频分双工用了两个分离的信道，一个是上行信道和一个是下行信道，能够使得无线电传播实现全双工。在一个同频全双工系统情况下，一个单一的信道能够获得同样的性能，立即就会使值数十亿美元的频谱财产的价值加倍。 为什么全双工很难去实现呢？当一个无线电设备发射一个信号，这信号能量中的一些能够被它自己的接收器接收到。因为它是自己产生的，这些无用的自干扰能量比那些预期的接收信号强数十亿倍（100dB+）。试着在同一时间同一信道去发射和接收信号就相当于当扯着嗓子大喊时试着去听一个耳语。这是一个知名的并且未解决的问题；每一个无线电设备都曾经被设计成以一个给予的频率或者发射或者接受信号，绝不会同时都发生，来去避免自干扰。 考虑到自干扰使得半双工运作成为必要，如果无线电传播能够完全消除自干扰，未来的5G无线网络将会怎样变化？随着几个组织在真实环境下演示的生动的自干扰消除结果，业界和学术界都已经在自干扰消除(SIC) 方面取得巨大的进步。再加上对这个主题的知识体系的不断的扩展，一些人认为这是一个SIC性能什么时候将使得全双工变成事实的问题，而不是是否SIC性能将使得全双工变成事实的问题。虽然我们简短的回顾了SIC架构和性能上的最先进的技术，但这篇文章的目的不是去探讨自干扰的复杂的模型，也不是去评估不同消除技术的有效性，因为关于这两方面有很多写得好的文章。相反，我们的目的是去探索SIC的长期的和短期的影响，SIC在5G和超5G的有限的频谱资源内能够去支持未来的
生物信息学试题整理
UTR的含义是（B ） A.编码区 B. 非编码区 C. motif的含义是（D ）。 A.基序 B. 跨叠克隆群 C. algorithm 的含义是（B ）。 A.登录号 B. 算法 C. RGR^ （D ）。 A.在线人类孟德尔遗传数据 D.水稻基因组计划 下列Fasta格式正确的是（B） 低复杂度区域 D. 幵放阅读框 碱基对 D. 结构域 比对 D. 类推 B. 国家核酸数据库 C. 人类基因组计划 A. seql: agcggatccagacgctgcgtttgctggctttgatgaaaactctaactaaacactccctta B. >seq1 agcggatccagacgctgcgtttgctggctttgatgaaaactctaactaaacactccctta C. seq1:agcggatccagacgctgcgtttgctggctttgatgaaaactctaactaaacactccctta D. >seq1agcggatccagacgctgcgtttgctggctttgatgaaaactctaactaaacactccctta 如果我们试图做蛋白质亚细胞定位分析，应使用（D） A. NDB 数据库 B. PDB 数据库 C. GenBank 数据库 D. SWISS-PROT 数
据库 Bioinformatics 的含义是（A ）。 A. 生物信息学 B. 基因组学 C. 蛋白质组学 D. 表观遗传学 Gen Bank中分类码PLN表示是（D ）。 A.哺乳类序列 B. 细菌序列 C.噬菌体序列 D. 植物、真菌和藻类序列 ortholog 的含义是（A）0 A.直系同源 B.旁系同源 C.直接进化 D.间接进化 从cDNA文库中获得的短序列是（D ）o A. STS B. UTR C. CDS D. EST con tig的含义是（B ）o A.基序 B. 跨叠克隆群 C. 碱基对 D. 结构域 TAIR （AtDB）数据库是（C）o A.线虫基因组 B. 果蝇基因组 C. 拟南芥数据库 D. 大肠杆菌基因组ORF的含义是（D ）o A.调控区 B. 非编码区 C.低复杂度区域 D. 幵放阅读框
管理信息系统外文翻译
管理信息系统外文翻译-标准化文件发布号：（9456-EUATWK-MWUB-WUNN-INNUL-DDQTY-KII
英文文献翻译 二〇年月日
科技文章摘译 Definition of a Management Information System There is no consensus of the definition of the term "management information system". Some writers prefer alternative terminology such as "information processing system", "information and decision system", "organizational information system", or simply "information system" to refer to the computer-based information processing system which supports the operations, management, and decision-making functions of an organization. This text uses “MIS” because it is descriptive and generally understood; it also frequently uses “information system” instead of “MIS” to refer to an organizational information system. A definition of a management information system, as the term is generally understood, is an integrated, user-machine system for providing information to support operations, management, and decision-making functions in an organization. The system utilizes computer hardware and software; manual procedures; models for analysis planning, control and decision making; and a database. The fact that it is an integrated system does not mean that it is a single, monolithic structure; rather, it means that the parts fit into an overall design. The elements of the definition are highlighted below. 1 Computer-based user-machine system Conceptually, management information can exist without computer, but it is the power of the computer which makes MIS feasible. The question is not whether computers should be used in management information system, but the extent to which information use should be computerized. The concept of a user-machine system implies that some tasks are best performed by humans, while others are best done by machine. The user of an MIS is any person responsible for entering input data, instructing the system, or utilizing the information output of the system. For many problems, the user and the computer form a combined system with results obtained through a set of interactions between the computer and the user. User-machine interaction is facilitated by operation in which the user’s input-output device (usually a visual display terminal) is connected to the computer. The computer can be a personal computer serving only one user or a large computer that
自适应滤波器MATLAB仿真
自适应滤波器MATLAB仿真 摘要:本文介绍了自适应滤波器的工作原理，以及推导了著名的LMS（Least mean squares）算法。以一个例子演示了自适应滤波器的滤波效果。实验结果表明，该滤波器滤波效果较好。 关键词:自适应滤波器 MATLAB7.0 LMS算法 Simulate of adaptive filter based on MATLAB7.0 Abstract:This article described the working principle of adaptive filter and deduced the well-known LMS algorithm. Take an example to demonstrate the adaptive filters filtering effects. The results show that the filter has an effective way to filter single. Key words:LMS algorithm Adaptive Filter Matlab7.0 1 引言 由Widrow B等提出的自适应滤波理论，是在维纳滤波、卡尔曼滤波等线性滤波基础上发展起来的一种最佳滤波方法。由于它具有更强的适应性和更优的滤波性能，从而广泛应用于通信、系统辨识、回波消除、自适应谱线增强、自适应信道均衡、语音线性预测和自适应天线阵等诸多领域[1]。自适应滤波器最大的优点在于不需要知道信号和噪声的统计特性的先验知识就可以实现信号的最佳滤波处理。本文通过一个具体例子和结果论证了自适应滤波器的滤波效果。 2 自适应滤波原理及LMS算法 2.1 自适应滤波原理 自适应滤波原理图[2]，如图1所示。 图1自适应滤波原理图 在自适应滤波器中，参数可调的数字滤波器一般为FIR数字滤波器，IIR数字滤波器或格型数字滤波器。自适应滤波分2个过程。第一，输入信号想x(n)通过参数可调的数字滤波器后得输出信号y(n)，y(n)与参考信号d(n)进行比较得误差信号e(n)；第二，通过一种自适应算法和x(n)和e(n)的值来调节参数可调的数字滤波器的参数，即加权系数，使之达到最佳滤波效果。
数字滤波器的外文翻译
FIR 数字滤波器的有限字长系数优化的比较研究 拜彻尔，泰勒，罗兰 威尔士大学纽波特学院运算工程学校 摘要：实时数字滤波器频率响应的精度受实现时系数约束条件即有限字长(FWL)的影响。该文仅考虑FIR 数字滤波器有关的FWL 问题。准确和近似响应之间的最大误差限的约束条件所对应的理论问题和统计误差值都进行了详细的研究。利用实数值遗传算法作为优化工具，并由若干设计案例的FWL 效应获得其最大误差限和误差值。由此，完成了简单凑整逼近、遗传算法优化、整数规划法，以及简单希尔登山者方法之间的比较。 关键词：实时数字滤波器； 有限字长；遗传算法；整数规划 1. 前言 FIR 数字滤波器广泛用于图像处理、移动通信、医疗电子，以及很多其他的信号处理应用。为降低能耗和提高运算量，截断系数到最短长度是有优势的。然而，该截断会引起滤波嚣设计参数的变化，在某些情况下这是不可接收的。此即优化问题，即尽可能地选择近似系数值的微小变化量，以便最好的服从设计规范标准。针对有限脉冲响应(FIR)滤波器形式结构的线性相位已被证明是鲁棒的，因而FWL 系数的自我实现的研究是极具有吸引力的[1]。FWL FIR 对称数字滤波器的研究涉及到一组系数的选择，从而这个新频率响应可以作为无限准确系数截断的一个结果，可以最大的接近所给定的规范频率响应。 已知的为解决该问题所使用的算法均基于两种方法：局部搜索法[2]和整数规划分支界限法[3,4]。局部搜索法需要选择一组可行的FWL 系数(称为四舍五入值)，用以给出一个频率响应并用以检验H 的领域。同时要选定滤波器的传递函数，以便得到更好的滤波器H'，即具有低误差函数的滤波器。如果找到了这样的一个滤波器H'，那么便可用H'来代替H ，而算法即可进入下一步或者终止。分支界限算法涉及对一组可能解所构成的树的系统性修正，这些解依赖于由枚举总数所确定的下界值。这两种算法本质上计算密集，且不能保证全局优化。其问题即是在于进一步复合，使其更加灵敏以便增加滤波器长度。 2. FWL 系数及误差目标函数 用以导出FWL 系数的最常用定点算法是直接量化法。使用标准滤波器设计技术导出的高精度系数在该方法中首次被利用，以得出FWL 的量化系数。如下量化系数的起始解给出。 h ri =round[h ei 2B-1] i=0,1,2,...,N-1 (1) 这里，h ri 为四舍五入系数，hei 为高精度系数，B 为用以描述系数的位数，N 为滤波器长度。 优化过程的主要目的在于极小化目标函数，其明确目标为获得一个与期望的响应尽可能接近的滤波器频率响应。目标函数被用于500个等距频率的格点。 目标函数通过以下式来评价： }H max ,H 110max{max }H H 1{ObjV s p s s p p i i L s i 2 i P i 2 i -++-=∑∑== (2) H ip =遗传算法优化滤波器在通带中对应频率的幅值响应 H is =遗传算法优化滤波器在阻带中对应频率的幅值响应 L=频率格点的数目（500）
外文文献及其翻译电子政务信息
外文文献及其翻译电子政务信息 1.政府信息化的含义？ 政府信息化是指：政府有效利用现代信息和通信技术，通过不同的信息服务设施，对政府的业务流程、组织结构、人员素质等诸方面进行优化、改造的过程。 2.广义和狭义的电子政务的定义？ 广义的电子政务是指：运用信息技术和通信技术实现党委、人大、政协、政府、司法机关、军队系统和企事业单位的行政管理活动。（电子党务、电子人大、电子政协） 狭义的电子政务是指：政府在其管理和服务职能中运用现代信息和通信技术，实现政府组织结构和工作流程的重组优化，超越时间、空间和部门分隔的制约，全方位的向社会提供优质规范、透明的服务，是政府管理手段的变革。 3.电子政务的组成部分？ ①：政府部门内部办公职能的电子化和网络化； ②：政府职能部门之间通过计算机网络实现有权限的实时互通的信息共享； ③：政府部门通过网络与公众和企业间开展双向的信息交流与策； 4．理解电子政务的发展动力？ ①：信息技术的快速发展； ②：政府自身改革与发展的需要； ③：信息化、民主化的社会需求的推动； 5.电子政务的应用模式？
模式有：1.政府对公务员的电子政务（G2E）； 2.政府间的电子政务（G2G）； 3.政府对企业的电子政务（G2B）； 4.政府对公众的电子政务（G2C）； 6.电子政务的功能？ ①：提高工作效率，降低办公成本； ②：加快部门整合，堵塞监管漏洞； ③：提高服务水平，便于公众的监督； ④：带动社会信息化发展； 7.我国电子政务发展存在的主要问题？ ①：政府公务员与社会公众对电子政务的认识不足； ②：电子政务发展缺乏整体规划和统一性标准； ③：电子政务管理体制改革远未到位； ④：电子政务整体应用水平还较低； ⑤：政府公务员的素质有待提高； ⑥：电子政务立法滞后； ⑦：对电子政务安全问题缺乏正确认识； 8.政府创新的含义和内容？ 含义：是指各级政府为适应公共管理与行政环境的需要，与时俱进的转变观念与职能，探索新的行政方法与途径，形成新的组织结
基于LMS算法的自适应组合滤波器中英文翻译
Combined Adaptive Filter with LMS-Based Algorithms ′ Abstract: A combined adaptive ?lter is proposed. It consists of parallel LMS-based adaptive FIR ?lters and an algorithm for choosing the better among them. As a criterion for comparison of the considere d algorithms in the proposed ?lter, we take the ratio between bias and variance of the weighting coef?cients. Simulations results con?rm the advantages of the proposed adaptive ?lter. Keywords: Adaptive ?lter, LMS algorithm, Combined algorithm,Bias and var iance trade-off 1．Introduction Adaptive ?lters have been applied in signal processing and control, as well as in many practical problems, [1, 2]. Performance of an adaptive ?lter depends mainly on the algorithm used for updating the ?lter weighting coef?ci ents. The most commonly used adaptive systems are those based on the Least Mean Square (LMS) adaptive algorithm and its modi?cations (LMS-based algorithms). The LMS is simple for implementation and robust in a number of applications [1–3]. However, since it does not always converge in an acceptable manner, there have been many attempts to improve its performance by the appropriate modi?cations: sign algorithm (SA) [8], geometric mean LMS (GLMS) [5], variable step-size LMS(VS LMS) [6, 7]. Each of the LMS-bas ed algorithms has at least one parameter that should be de?ned prior to the adaptation procedure (step for LMS and SA; step and smoothing coef?cients for GLMS; various parameters affecting the step for VS LMS). These parameters crucially in?uence the ?lter output during two adaptation phases:transient and steady state. Choice of these parameters is mostly based on some kind of trade-off between the quality of algorithm performance in the mentioned adaptation phases. We propose a possible approach for the LMS-based adaptive ?lter performance improvement. Namely, we make a combination of several LMS-based FIR ?lters with different parameters, and provide the criterion for choosing the most suitable algorithm for different adaptation phases. This method may be applied to all the
外文翻译-----学生信息管理系统的设计与发展
英文译文 学生信息管理系统的设计与发展 随着信息技术的日新月异,各种管理系统的相继出现,让日常生活变的更加具有条理化, 尽可能的合理的运用网络资源可以大大的减少人工管理上带来的不 便及时间的浪费. 二十一世纪现代化程度的不断加速,科学文化水平的不断提高,学生数量的急剧增长，势必增加了管理学生信息带来的压力，人工检索的低效完全不符合整个社会的需要.学生信息管理系统是信息管理系统中的一种，目前信息技术不断的发展，网络技术已经广泛的应用于我们身边的各行各业，有了网络技术的发展，各高校都利用计算机来管理办学，以前学校靠手工操作的一切繁琐事情都得到了快速且高效率的解决，特别是学生成绩管理系统在学校中起到了很大的作用，对于学生和教师来说都能够更方便、快捷、准确地了解和管理各方面信息。 采用人工管理庞大的数据库是一项繁重枯燥的工作，无论是数据录入，查询还是修改都存在着工作量大，效率低下，周期长的缺点。而计算机管理系统的引进将给人工管理数据库的工作带来一次彻底的变革。学校由于学生众多，学生数据信息库庞大，使信息的管理成为了一个复杂繁琐的工作。本系统针对学校,经过实际的需求分析，采用功能强大的VB6.0作为开发工具来开发学生信息管理系统。整个系统从符合操作简便，界面美观、灵活、实用的要求出发，完成学生信息管理的全过程，包括系统管理、基本信息管理、学习管理、奖惩管理和打印报表等功能。经过使用证明，本文所设计的学生信息管理系统可以满足学校对学生信息管理方面的需要。论文主要介绍了本课题的开发背景，所要完成的功能和开发的过程。重点的说明了系统设计的重点、开发设计思想、难点技术和解决方案。学生管理系统的产生大大减少了人力上的不便，让整个学生数据管理更加科学合理。本系统最有特色的地方就是后台数据库对学生信息的统一管理。该系统主要分为系统管理，学生专业管理，学生档案管理，学费管理，课程管理，成绩管理和打印报表。系统的界面是运用vb软件制作的，以上几个模块都是运用vb 控件绑定的方法来实现对后台数据库的连接，后台数据库大概分为以下几个表：专业信息表，收费类别表，学生职务表，学生信息表，学生政治面貌表，用户登入表。采用Client/Server结构进行设计，本系统是在由一台数据服务器和若干台
数字信号处理英文文献及翻译
数字信号处理 一、导论 数字信号处理（DSP）是由一系列的数字或符号来表示这些信号的处理的过程的。数字信号处理与模拟信号处理属于信号处理领域。DSP包括子域的音频和语音信号处理，雷达和声纳信号处理，传感器阵列处理，谱估计，统计信号处理，数字图像处理，通信信号处理，生物医学信号处理，地震数据处理等。 由于DSP的目标通常是对连续的真实世界的模拟信号进行测量或滤波，第一步通常是通过使用一个模拟到数字的转换器将信号从模拟信号转化到数字信号。通常，所需的输出信号却是一个模拟输出信号，因此这就需要一个数字到模拟的转换器。即使这个过程比模拟处理更复杂的和而且具有离散值，由于数字信号处理的错误检测和校正不易受噪声影响，它的稳定性使得它优于许多模拟信号处理的应用（虽然不是全部）。 DSP算法一直是运行在标准的计算机，被称为数字信号处理器（DSP）的专用处理器或在专用硬件如特殊应用集成电路（ASIC）。目前有用于数字信号处理的附加技术包括更强大的通用微处理器，现场可编程门阵列（FPGA），数字信号控制器（大多为工业应用，如电机控制）和流处理器和其他相关技术。 在数字信号处理过程中，工程师通常研究数字信号的以下领域：时间域（一维信号），空间域（多维信号），频率域，域和小波域的自相关。他们选择在哪个领域过程中的一个信号，做一个明智的猜测（或通过尝试不同的可能性）作为该域的最佳代表的信号的本质特征。从测量装置对样品序列产生一个时间或空间域表示，而离散傅立叶变换产生的频谱的频率域信息。自相关的定义是互相关的信号本身在不同时间间隔的时间或空间的相关情况。 二、信号采样 随着计算机的应用越来越多地使用，数字信号处理的需要也增加了。为了在计算机上使用一个模拟信号的计算机，它上面必须使用模拟到数字的转换器（ADC）使其数字化。采样通常分两阶段进行，离散化和量化。在离散化阶段，信号的空间被划分成等价类和量化是通过一组有限的具有代表性的信号值来代替信号近似值。 奈奎斯特-香农采样定理指出，如果样本的取样频率大于两倍的信号的最高频率，一个信号可以准确地重建它的样本。在实践中，采样频率往往大大超过所需的带宽的两倍。 数字模拟转换器（DAC）用于将数字信号转化到模拟信号。数字计算机的使用是数字控制系统中的一个关键因素。 三、时间域和空间域 在时间或空间域中最常见的处理方法是对输入信号进行一种称为滤波的操作。滤波通常包括对一些周边样本的输入或输出信号电流采样进行一些改造。现在有各种不同的方法来表征的滤波器，例如： 一个线性滤波器的输入样本的线性变换；其他的过滤器都是“非线性”。线性滤波器满足叠加条件，即如果一个输入不同的信号的加权线性组合，输出的是一个同样加权线性组合所对应的输出信号。
RLS算法的自适应滤波器MATLAB仿真作业
RLS 自适应滤波器仿真作业 工程1班220150820 王子豪 1. 步骤 1)令h M(-1)=0，计算滤波器的输出d(n)=X M T=h M(n-1)； 2)计算误差值e M(n)=d(n)-d(n,n-1)； 3)计算Kalman增益向量K M(n)； 4)更新矩阵的逆R M-1(N)=P M(N)； 5)计算h M(n)=h M(n-1)+K M(n)e M(n)； 2. 仿真 RLS 中取T (-1)=10，λ=1及λ= 0.98； 信号源x(n)与之前LMS算法仿真不变，对自适应滤波器采用RLS算法。通过对比不同遗忘因子λ的情况下RLS的误差收敛情况。取λ=0.98和λ=1两种情况下的性能曲线如图1所示。 其系数收敛情况如图2所示。
图1 不同λ值下的RLS算法性能曲线（100次实验平均） 图2 不同λ值下的RLS算法系数收敛情况（100次实验平均）
3. 结果分析 RLS算法在算法的稳态阶段、即算法的后期收敛阶段其性能和LMS算法相差不明显。但在算法的前期收敛段，RLS算法的收敛速度要明显高于LMS算法。但是RLS算法复杂度高，计算量比较大。 遗忘因子λ越小，系统的跟踪能力越强，同时对噪声越敏感；其值越大，系统跟踪能力减弱，但对噪声不敏感，收敛时估计误差也越小。 4. Matlab程序 clear; clc; N=2048; %信号的取样点数 M=2;%滤波器抽头的个数 iter=500;%迭代次数 %初始化 X_A=zeros(M,1); %X数据向量 y=zeros(1,N); %预测输出 err=zeros(1,iter); %误差向量 errp=zeros(1,iter); %平均误差 wR=zeros(M,iter); %每一行代表一次迭代滤波器的M个抽头参数 T=eye(M,M)*10; %RLS算法下T参数的初始化，T初始值为10 X=zeros(1,M); lamuta=0.98 ; %遗忘因子 for j=1:100 ex=randn(1,N); %噪声信号e(n) x=filter(1,[1,-1.6,0.8],ex);%经过系统H(Z)之后输出x d=x; %参考信号 for k=(M+1):iter-1