An Indoor Positioning Scheme for Visible Light Using Fingerprint Database with Multi.Parameters

This paper proposes a novel indoor positioning scheme based on visible light communication(VLC).A new indoor VLC positioning scheme using fingerprint database with multi-parameters have been raised.We conduct simulation and experimental research on the illumination intensity distribution of several direction parameters.In the experiment,four LED matrixes are identified by LED-ID with room dimensions of 3.75×4.00×2.7 m^3.The results show that the mean of the location error is 0.22 m in the receiving plane,verifying the correctness and feasibility of the positioning scheme.

Construction of Gliadin Fingerprints Database for the Main Wheat Cultivars Grown in North China

The standard gliadin fingerprints and their database of 68 major cultivars and a part of backbone parents, which have ever been extensively grown in North China since the 1950' s, were constructed by using CAWGES software and an improved method of pH 3.2 A-PAGE. In the meantime, investigations were made on the utilization of the database in the area of gliadin fingerprints analysis, variety identification and genetic relationship study. The results showed that it provided an effective method for building core collections and variety identification.

Fusing Fixed and Hint Landmarks on Crowd Paths for Automatically Constructing Wi-Fi Fingerprint Database

In typical Wi-Fi based indoor positioning systems employing fingerprint model,plentiful fingerprints need to be trained by trained experts or technician,which extends labor costs and restricts their promotion.In this paper,a novel approach based on crowd paths to solve this problem is presented,which collects and constructs automatically fingerprints database for anonymous buildings through common crowd customers.However,the accuracy degradation problem may be introduced as crowd customers are not professional trained and equipped.Therefore,we define two concepts:fixed landmark and hint landmark,to rectify the fingerprint database in the practical system,in which common corridor crossing points serve as fixed landmark and cross point among different crowd paths serve as hint landmark.Machinelearning techniques are utilized for short range approximation around fixed landmarks and fuzzy logic decision technology is applied for searching hint landmarks in crowd traces space.Besides,the particle filter algorithm is also introduced to smooth the sample points in crowd paths.We implemented the approach on off-the-shelf smartphones and evaluate the performance.Experimental results indicate that the approach can availably construct WiFi fingerprint database without reduce the localization accuracy.

Fingerprint Database Updating Using Crowdsourcing in Indoor Bluetooth Positioning System

Fingerprint⁃based Bluetooth positioning is a popular indoor positioning technology.However,the change of indoor environment and Bluetooth anchor locations has significant impact on signal distribution,which will result in the decline of positioning accuracy.The widespread extension of Bluetooth positioning is limited by the need of manual effort to collect the fingerprints with position labels for fingerprint database construction and updating.To address this problem,this paper presents an adaptive fingerprint database updating approach.First,the crowdsourced data including the Bluetooth Received Signal Strength(RSS)sequences and the speed and heading of the pedestrian were recorded.Second,the recorded crowdsourced data were fused by the Kalman Filtering(KF),and then fed into the trajectory validity analysis model with the purpose of assigning the unlabeled RSS data with position labels to generate candidate fingerprints.Third,after enough candidate fingerprints were obtained at each Reference Point(RP),the Density⁃based Spatial Clustering of Applications with Noise(DBSCAN)approach was conducted on both the original and the candidate fingerprints to filter out the fingerprints which had been identified as the noise,and then the mean of fingerprints in the cluster with the largest data volume was selected as the updated fingerprint of the corresponding RP.Finally,the extensive experimental results show that with the increase of the number of candidate fingerprints and update iterations,the fingerprint⁃based Bluetooth positioning accuracy can be effectively improved.

Establish a Three-dimensional Fluorescent Fingerprint Database of Traditional Chinese Medicines

Objective:To set up a database of three-dimensional fluorescence spectra of traditional Chinese medicines,Screening of medicinal materials by three-dimensional fluorescence spectroscopy,Methods:The paper Summarizes the three-dimensional fluorescence fingerprints,screens medicinal materials on basis of verifying the three-dimensional fluorescence spectra of the reference crude herbs of the national standard Chinese medicines,and combines with visual basic6.0 and microsoft access 2003 technology system to construct a three-dimensional fluorescence fingerprint database of TCMs.Results:the identification and quality control of traditional Chinese medicines(TCMs)was accuately and swiftly achieved.Conclusion:The relevant analysis on the operating system of database and the three-dimensional fluorescence spectrum database of TCMs indicates that this operating system can provide convenient channels for the inspection,verification and quality control of TCMs.

基于多层编码的数据库指纹溯源方法

为了实现针对数据库数据的泄密追踪,提出一套基于多层编码的数据库指纹溯源方法。在通过OFFO多层编码预防用户合谋的基础上在数据库中嵌入数据指纹,详细介绍指纹嵌入的基本原理与实现流程,通过提取码元的方式实现数据库指纹的溯源。最后通过数据库指纹匹配率对比实验的方式对溯源算法的有效性加以验证,实验结果表明,研究所提出的数据库指纹溯源方案在溯源准确率方面应用效果较为理想。

中国棉花审定品种SSR指纹库的构建与综合评价

[目的]棉花是一种异源四倍体作物,基因组结构复杂,常异花授粉的繁殖方式也导致棉花品种难以实现高度纯合;棉种市场缺乏有效的监管技术手段,品种多乱杂现象长期存在,严重影响纤维品质一致性。构建中国近20年棉花审定品种标准样品的DNA指纹库,探索棉花品种高通量SSR身份鉴定模式,为棉花品种真实性鉴定和新品种特异性鉴定提供依据;分析审定品种的遗传多样性和群体分化,为棉花不同生态区的适应性鉴定和培育适应新环境的品种提供理论基础。[方法]基于多重PCR技术和毛细管电泳检测方法,使用筛选得到的60个SSR标记构建1 015份棉花审定品种标准样品的DNA指纹库,通过植物品种DNA指纹库管理系统对审定品种SSR指纹进行两两比对,分析审定品种的遗传差异,筛选用于品种鉴定的核心SSR位点。利用聚类分析法和群体结构分析法分析1 015份棉花审定品种的遗传多样性,并计算群体间遗传分化指数。[结果]60个SSR标记在1 015个审定品种中共扩增出216种等位变异,平均等位变异数为3.6,平均PIC值为0.37。1 015个审定品种的SSR指纹进行两两比较,共产生513 591组结果,样品间最大差异位点数为58个。差异位点百分比主要集中在41%-70%,涉及428 115组,占83.36%;其中,差异位点百分比在51%-60%时,涉及组数最多,为197 829组,占38.52%。品种间差异位点百分比大于20%时,占所有品种两两比对组数的99%以上,差异位点百分比低于20%的比对结果只占0.58%。基于组合鉴定法,筛选一套包含10个SSR位点的核心位点组合,在1 015个品种中鉴别能力达到99%。聚类结果和群体结构分析表明,1 015个品种被清晰地划分为5个亚群,G1(n=240)为早熟棉亚群,主要分布于中国北部和西北内陆地区,该亚群品种遗传多样性最丰富,品种间平均遗传距离为0.419。G2(n=277)亚群为中熟棉亚群,分布于长江流域,该亚群杂交种较多,亚群内平均遗传距离为0.309。G3(n=109)亚群属于早熟、中熟棉亚群,分布于河北黑龙港地区,该亚群品种遗传组分相对单一,亚群内平均遗传距离在陆地棉群体中最小,仅为0.150。G4(n=254)亚群属于中早熟棉亚群,主要分布于黄河流域,群体内平均遗传距离为0.307。G5(n=37)亚群由37份海岛棉组成,群体内平均遗传距离最小,为0.149。海岛棉与陆地棉之间遗传分化水平最高,平均FST值为0.503;陆地棉群体内,G3亚群与其他亚群之间遗传分化水平最高,FST值为0.193-0.242。长江流域与黄河流域相比,遗传分化水平最低,FST值为0.112。[结论]构建了1 015个中国近20年审定品种标准样品DNA指纹库,筛选了一套包含10个SSR位点的核心标记组合,可以清晰地鉴别99%以上的品种,创建了“核心位点+扩展位点”的高通量棉花鉴定模式;1 015个品种被划分为5个亚群,其中,陆地棉具有明显的地理分布特征。

煤矿井下HBi-LSTM地磁定位算法研究

针对井下环境对地磁数据影响较大的问题,提出HBi-LSTM神经网络地磁定位模型。基于分层LSTM处理不同长短时间序列以及Bi-LSTM充分学习每条序列信息的特点,构建出HBi-LSTM模型,利用矿用手机内置磁力计采集井下地磁数据,建立面向井下环境的地磁指纹数据库,通过HBi-LSTM学习实现地磁序列可以更好地对应位置标签,之后矿工手持矿用手机随机运动采集地磁序列通过训练好的模型精确匹配指纹库实现在线定位。实验结果显示:所提出的模型比基本LSTM模型的定位性能更好,能够有效提升复杂环境下定位精度。

指纹库容量对指纹检索结果的影响

近年来,指纹库容量的快速增长导致指纹比对难度加大,尤其体现在检索结果中相似异源指纹对比中同源指纹的干扰上。为了探究不同指纹库容量对同源指纹与相似异源指纹出现情况的影响,本实验建立600万人级、1000万人级和1亿人级数据库,对箕型纹三角区域各部分发起查询并讨论检索结果。结果显示:指纹库容量增长幅度越大,同源指纹出现率降低越明显,同时其排位显著降低,而相似异源指纹数量显著增加,当相似异源指纹排在同源指纹之前时,会对指纹鉴定人员造成干扰。此外,还发现特征点密度可以影响相似异源指纹的出现数量,特征点密度越大,特征组合的特定性越小,越容易产生相似异源指纹。本研究旨在增强大数据条件下指纹鉴定人员的风险意识。

基于众值滤波的室内定位指纹库建立方法

基于接收信号强度(Received Signal Strength Indicator, RSSI)位置指纹定位算法可避免RSSI测距问题,通过滤波处理可构建高质量指纹数据库。针对高斯滤波运算时间长而均值滤波定位误差大等问题,通过分析RSSI分布规律,基于部分RSSI重复出现的特性,提出一种众值滤波方法,通过逐次选取当前数据中众数,直到所选众数的频数累积和与数据总量之比大于95%时取平均提取特征RSSI。实验表明,基于众值滤波构建的指纹数据库在73%的情况下与高斯滤波定位精度相近,但运算效率优于高斯滤波。同时,相对于均值滤波,众值滤波将定位精度提升约0.15 m,在95%的情况下将最大定位误差限制在2 m以内,可有效提高指纹数据库质量。

基于改进Fast-DTW的多维地磁序列匹配算法研究

传统单点的地磁匹配定位算法运算量大,且定位时效性及定位精度较差。针对该问题,采用基于序列的快速动态时间规整算法Fast-DTW实现多维的地磁序列匹配,并利用最长公共子序列LCS的有序聚类进行优化。离线阶段通过坐标转换法构建四维地磁指纹库,在线阶段进行实时地磁序列匹配,获得定位结果。实验结果表明,该算法的定位时效性及精度均有提升。

一种面向MR数据定位场景的脏指纹剔除算法

【目的】随着通信技术发展与移动设备的普及,MR(测量报告,Measurement Report)数据被广泛应用到无线网络定位中,其中基于MR指纹库匹配的定位方法是精度较高、应用较广泛的方法。然而,位置的计算精度依赖于MR指纹库数据记录的质量,亟需在积累位置指纹库时对数据进行清洗、过滤、位置纠偏等工作,以保证指纹库的数据质量。【方法】因此,本文提出了一种面向MR数据定位场景的脏指纹剔除算法,通过DBSCAN聚类算法识别异常指纹,并纠偏基站位置,建立高质量的指纹数据库,以提升MR数据定位精准性。【结果】本文在农村、市区、郊区3个场景下,分别使用模拟数据进行仿真试验,对本文方法进行分析与评估。【结论】试验结果显示,随着异常指纹剔除及指纹数据库更新,MR数据定位精准度得到有效提升,且所提算法在指纹聚类场景下相比其他算法均存在优势。

基于多模态特征的新型电力系统终端无线指纹提取与识别

随着新型电力系统的不断发展,设备在开放环境中存在被假冒攻击的可能。常见的应对方式是基于无线信号指纹的识别技术,在物理层面保证设备的安全性。然而,由于无线信号的不稳定性,导致对终端设备的识别准确率较低。针对上述问题,文章提出了一种基于多模态特征的新型电力系统终端无线指纹提取与识别方法。通过融合无线信号的时域特征和频域特征构建动态指纹数据库,形成一种基于多模态特征的新型电力系统无线终端设备识别认证的方法,实现了稳定的无线终端指纹提取,可以有效在无线设备接入时和无线设备持续通信期间对无线设备进行识别认证,保证无线设备的安全可靠运行。通过不同场景下的实验结果表明,使用帧响应时间间隔作为时域特征和信道状态信息作为频域特征的多域融合方法进行无线设备识别,可以显著提高计算的准确性和稳定性,识别率达到95%以上。

基于指纹库更新补偿的波束跟踪算法研究

针对拒止、复杂电磁环境下,高动态无人节点定向通信面临的坐标信息不精确、飞行姿态和轨迹变化剧烈等问题,为保持可靠的波束对准与跟踪,提出了一种基于卡尔曼滤波的指纹库更新补偿算法;利用卡尔曼滤波算法对自身姿态进行预测更新,建立载体坐标系;采用改进的算法对波束指向进行预测更新,并利用指纹库对状态向量进行更新补偿,调节采样比例,并将新的数据存入指纹库对数据更新,进行二次状态信息预测,完成最终波束指向;整体设计的波束跟踪算法流程更加符合实际应用场景,满足通信需求;仿真结果表明,在半波束宽度为3°,100个通信时隙中,维持正常通信的成功率有92%以上,相比传统跟踪算法提高了8%,具有更加稳定的通信质量。

RSSI室内定位在线匹配算法的研究与性能比较

针对在基于WiFi信号强度RSSI进行室内定位的指纹库算法的在线匹配环节中存在的不足,该文利用基于阈值R_(0)动态筛选匹配的指纹点数,提出了一种增强加权k近邻算法(EWKNN).因为阈值R_(0)可以动态筛选指纹库中的样本点,所以能够提高增强加权k近邻算法的适用度和高精度.仿真结果表明:在R_(0)设置恰当的情况下,增强加权k近邻算法的计算量与加权k近邻算法(WKNN)相当,但定位精度更高.

Robust Fingerprint Localization Based on Massive MIMO Systems

Location-based services have become an important part of the daily life.Fingerprint localization has been put forward to overcome the shortcomings of the traditional positioning algorithms in indoor scenario and rich scattering environment.In this paper,a single-site multiple-input multiple-output(MIMO)orthogonal frequency division multiplexing(OFDM)system is modeled,from which an angle delay channel power matrix(ADCPM)is extracted.Considering the changing environment,auto encoders are used to generate new fingerprints based on ADCPM fingerprints to improve the robustness of the fingerprints.When the scattering environment has changed beyond a certain extent,the robustness will not be able to make up for the positioning error.Under this circumstance,an updating of the fingerprint database is imperative.A new fingerprint database updating algorithm which combines a new clustering method and an updating rule based on probability is proposed.Simulation results show the desirable performance of the proposed methods.

Online Fingerprint Verification Algorithm and Distributed System

In this paper, a novel online fingerprint verification algorithm and distribution system is proposed. In the beginning, fingerprint acquisition, image preprocessing, and feature extraction are conducted on workstations. Then, the extracted feature is transmitted over the internet. Finally, fingerprint verification is processed on a server through web-based database query. For the fingerprint feature extraction, a template is imposed on the fingerprint image to calculate the type and direction of minutiae. A data structure of the feature set is designed in order to accurately match minutiae features between the testing fingerprint and the references in the database. An elastic structural feature matching algorithm is employed for feature verification. The proposed fingerprint matching algorithm is insensitive to fingerprint image distortion, scale, and rotation. Experimental results demonstrated that the matching algorithm is robust even on poor quality fingerprint images. Clients can remotely use ADO.NET on their workstations to verify the testing fingerprint and manipulate fingerprint feature database on the server through the internet. The proposed system performed well on benchmark fingerprint dataset.

A Study on Automatic Latent Fingerprint Identification System

Latent fingerprints are the unintentional impressions found at the crime scenes and are considered crucial evidence in criminal identification.Law enforcement and forensic agencies have been using latent fingerprints as testimony in courts.However,since the latent fingerprints are accidentally leftover on different surfaces,the lifted prints look inferior.Therefore,a tremendous amount of research is being carried out in automatic latent fingerprint identification to improve the overall fingerprint recognition performance.As a result,there is an ever-growing demand to develop reliable and robust systems.In this regard,we present a comprehensive literature review of the existing methods utilized in latent fingerprint acquisition,segmentation,quality assessment,enhancement,feature extraction,and matching steps.Later,we provide insight into different benchmark latent datasets available to perform research in this area.Our study highlights various research challenges and gaps by performing detailed analysis on the existing state-of-the-art segmentation,enhancement,extraction,and matching approaches to strengthen the research.

基于特征降维的在线序列学习机算法在室内动态定位中的应用

随着室内定位需求的不断增加,基于指纹的定位方法由于低成本、易于实现、精度较高等优势被广泛使用。但指纹定位算法在离线阶段训练成本高,接收信号强度值易受环境和噪声的影响,对环境的动态变化缺乏灵活性。提出了一种基于特征降维的在线序列学习机算法(PCA-OS-ELM),PCA算法可以对原始的RSSI数据进降维,去除干扰信息,构造新的特征。OSELM的快速学习能力可以降低离线阶段的训练成本,适应环境的动态变化。在2种不同的环境下进行了对比实验,结果表明所提出的算法能适应环境的动态变化,提高定位精度。

云南省优质稻标准样品数据采集方法及应用研究

【目的】探索采集优质稻标准样品数据的方法,构建云南省优质稻品种的标准样品数据库,为优质稻品种真实性鉴定及提纯复壮提供技术支撑。【方法】以云恢290、滇屯502的原种及生产用种为研究材料,采用品种农艺性状调查、SSR分子标记构建指纹图谱、稻米品质检测等技术全面系统地描述优质稻品种的特征特性。【结果】利用12对分布在水稻12条染色体上的核心标记采集原种及生产用种的指纹图谱,结果云恢290和滇屯502的生产用种和原种的扩增产物均无差异,可用于云恢290和滇屯502的指纹图谱描述。采用12个核心标记对原种及生产用种随机抽取48个单株进行基因型一致性鉴定,云恢290原种、生产用种在12个标记中扩增产物大小一致,无异型株;滇屯502原种扩增产物整齐一致,无异型株,其生产用种有2个标记出现异带,有2个异型株。采用DUS测试方法采集17个DUS测试性状、4张植株部位图片,根据国家优质稻标准采集11个品质性状。【结论】以品种指纹图谱、DUS测试性状、植株部位图片、品质性状及商品信息5个要素作为数据库基础数据,借助计算机编程软件构建优质稻标准样品数据库。优质稻标准样品数据库的建立可以从基因水平、品种特征特性及外观对品种进行系统描述。