利用智能手机传感器建立室内定位指纹库的wifi指纹定位方法

无线电定位系统在室外空间已经取得了巨大成功,GPS等卫星定位系统的已广泛应用,科技界在室内定位技术方面虽然出了很多成果,但都没有取得广泛应用,本文介绍了定位技术的基本原理,无线电定位研究的热门方法.分析了当前几种热门方法的优缺点,并针对wifi信号强度指纹定位方法的缺点提出了一种弥补的方案.     

室内定位系统中位置指纹库滤波算法研究

WiFi指纹定位是目前最受欢迎的室内定位技术之一,离线阶段创建的位置指纹库的精确与否对定位的精准度有很大的影响。传统的指纹库构建一般对采集的数据进行均值滤波,误差较大,并且在范围较大的场合进行定位时,由于位置指纹数据过多,使得定位时效性不好,结果不理想。为了提高指纹库的可靠性,通过给采集的源指纹数据赋予权值并根据权值的大小划分有效数据进行滤波处理,建立高精度指纹库,并利用基于临近域加权最近邻算法进行验证。实验结果表明,与传统的构建指纹库和定位算法相比,该方法显著提高了定位精度,缩短了定位时间。     

改进指纹强度下的WiFi室内定位算法

目前的室内定位算法利用信号传播模型求出信号强度后直接进行求解定位,使得定位误差较大.为提高定位精度,提出利用信号能量的欧氏距离方法进行加权,然后对改进后的信号强度进行阈值滤波加均值滤波双重处理.定位阶段,在K最近邻算法基础上利用距离的倒数作为加权函数的算法进行定位.经仿真结果表明,改进后的算法相比于一些典型的定位算法,定位精度有较大提高.     

一种基于位置指纹的室内WLAN定位方法

针对室内信号时变性导致定位不准的问题,提出了一种改进的3阶段位置指纹定位法。采样阶段,将采集信号的坐标、方位、接收信号强度的高斯分布及其对应的无线接入点等信息存储在数据库中生成位置指纹;在校正阶段中,利用参考点间信号强度的关联性信息,使用局部加权线性回归法,计算出一些虚拟点的信号强度;最后是线上实时定位阶段。通过与传统的加权K最邻近算法、直方图和联合聚类等3种定位方法相比较,该算法在同样的场景下可以取得更好的定位精度。     

基于RSS相关性的位置指纹室内定位方法

解决设备差异性造成的Wi-Fi信号强度不确定问题是位置指纹室内定位应用与推广的关键.一种基于设备间接收信号强度(Received Signal Strength,RSS)相关性的位置指纹室内定位方法被提出.以智能手机为用户终端,离线阶段,通过智能手机扫描的Wi-Fi信号强度信息,经过数据处理,筛选稳定的接入点(Access Point,AP),构建离线指纹数据库;在线定位阶段,对于实时获取的Wi-Fi信号强度信息,进行筛选处理后,挑选与离线指纹共同拥有的AP,并根据该AP集合,形成新的离线指纹和在线指纹.对离线指纹按RSS的大小降序排序;在线指纹,则以同一次序对RSS排序,然后利用皮尔逊相关系数和杰卡德相似系数,计算指纹相似度并排序,通过K最近邻(K-Nearest Neighbor,KNN)算法实现用户定位.实验表明该方法可有效解决设备差异性问题,并实现精确定位,平均定位误差达到1.7 m.     

室内位置指纹定位方法中的小波去噪应用

采集的位置指纹包含的大量随机噪声严重影响着位置指纹定位方法的精确度,为了提高位置指纹定位方法的精确度,文中提出了一种基于卡尔曼滤波和小波去噪相结合的方法来去除采集获得的位置指纹中的随机噪声的方法。实验结果表明,与常规的去噪方法相比,基于此方法的位置指纹定位算法精度有一定程度的提高。     

An adaptive location estimator using tracking algorithms for indoor WLANs

This paper presents adaptive algorithms for estimating the location of a mobile terminal (MT) based on radio propagation modeling (RPM), Kalman filtering (KF), and radio-frequency identification (RFID) assisting for indoor wireless local area networks (WLANs). The location of the MT of the extended KF positioning algorithm is extracted from the constant-speed trajectory and the radio propagation model. The observation information of the KF tracker is extracted from the empirical and RPM positioning methods. Specifically, a sensor-assisted method employs an RFID system to adapt the sequential selection cluster algorithm. As compared with the empirical method, not only can the RPM algorithm reduce the number of training data points and perform on-line calibration in the signal space, but the RPM and KF algorithms can alleviate the problem of aliasing. In addition, the KF tracker with the RFID-assisted scheme can calibrate the location estimation and improve the corner effect. Experimental results demonstrate that the proposed location-tracking algorithm using KF with the RFID-assisted scheme can achieve a high degree of location accuracy (i.e., more than 90% of the estimated positions have error distances of less than 2.1 m).     

Extreme learning machine for indoor location fingerprinting

With the rapid growing market of wireless devices, positioning systems that make use of the signal strength of wireless devices are gaining more interest nowadays. Being able to track the location of a Wi-Fi or Radio Frequency Identification device could improve the quality of services in various sectors, including security, warehouse, logistic management, and healthcare. As compared with outdoor environment, positioning systems face a greater challenge in indoor environment because wireless signal is significantly influenced by building layout and surrounding objects, for which a location fingerprinting approach is needed. Moreover, the signal strength of a wireless device may also change over time, which is known as temporal variation, and therefore a reliable location estimation system must have the ability to learn and adapt with temporal changes. However, if the learning process is highly complex and requires long processing time, deploying the system into a larger scale would not be feasible. In recent years, Extreme Learning Machine (ELM) has surfaced as a viable alternative that challenged the norm of iterative and progressive learning. ELM has also been considered as a solution for indoor location fingerprinting. However, there has not been a comprehensive review on how the ELM-based approaches are linked with existing location fingerprinting techniques. Here we discuss some major location fingerprinting techniques, which are nearest-neighbor, LANDMARC, and LEMT, and formulate a new framework for systematically translating the techniques into ELM-based methods.     

Broadband ultrasonic location systems for improved indoor positioning

Ultrasonic location systems are a popular solution for the provision of fine-grained indoor positioning data. Applications include enhanced routing for wireless networks, computer-aided navigation, and location-sensitive device behavior. However, current ultrasonic location systems suffer from limitations due to their use of narrowband transducers, This paper investigates the use of broadband ultrasound for indoor positioning systems. Broadband ultrasonic transmitter and receiver units have been developed and characterized. The utilization of these units to construct two positioning systems with different architectures serves to highlight and affirm the concrete, practical benefits of broadband ultrasound for locating people and devices indoors.     

Methods for optimizing the location of base stations for indoor wireless communications

When designing wireless communication systems, it is very important to know the optimum locations for the base station antennas. In this paper, a model has been developed to set up an optimization problem, the solution of which provides the information for the optimum location of the base station antennas particularly for an indoor environment. Several methods for the optimization of the cost function are presented and the final results are compared with each other. This methodology can be applied for the design and planning of the location of base station antennas for indoor wireless communication systems. Two numerical examples have been presented to illustrate the application of this methodology.     

A survey of indoor positioning systems for wireless personal networks

Recently, indoor positioning systems (IPSs) have been designed to provide location information of persons and devices. The position information enables location-based protocols for user applications. Personal networks (PNs) are designed to meet the users' needs and interconnect users' devices equipped with different communications technologies in various places to form one network. Location-aware services need to be developed in PNs to offer flexible and adaptive personal services and improve the quality of lives. This paper gives a comprehensive survey of numerous IPSs, which include both commercial products and research-oriented solutions. Evaluation criteria are proposed for assessing these systems, namely security and privacy, cost, performance, robustness, complexity, user preferences, commercial availability, and limitations.We compare the existing IPSs and outline the trade-offs among these systems from the viewpoint of a user in a PN.     

Software tool for optimising indoor/outdoor coverage in aconstruction site

A system architecture, an empirical propagation model, and a software combined with a CAD tool, have been designed to offer mobile communication services to construction sites. Results have been validated by measurements     

Multitrellis Viterbi algorithm for indoor systems using narrowbeamantennas

In earlier work, the performance (in terms of data eye closure) of a threshold detector in 2- and 4-PSK modulation schemes has been analyzed for wireless indoor systems using narrowbeam antennas. Here, assuming the channel is known, a very efficient implementation of the Viterbi algorithm (VA) is included in the receiver, and a bit-error rate (BER) criterion is used to evaluate the receiver robustness to channel conditions. In contrast to the earlier work, it is seen that 4-PSK signals with VA detectors are indeed more robust than 2-PSK signals to channel conditions     

Channel precoding for indoor radio communications using dimensionpartitioning

A new phase precoding technique is developed to combat the intersymbol interference (ISI) resulting from a frequency-selective slowly fading channel in a personal communication system using quadrature phase-shift keying (QPSK). Based on a new dimension partitioning technique, the precoder predistorts only the phase of the transmitted signal to keep a constant transmitted signal amplitude and, therefore, to ensure the stability of the precoder even in equalizing a nonminimum-phase channel. Under the constraint of the constant amplitude, the dimension partitioning method is developed to guarantee the possibility of correct detection for all transmitted information symbols and to further improve the transmission accuracy by increasing the size of the decision regions. Analytical and simulation results demonstrate that over frequency selective Rayleigh and Rician fading channels, the system using the proposed channel precoder can achieve a bit error rate (BER) comparable with that using a conventional decision feedback equalizer (DFE). The precoder can outperform the DFE in an indoor environment where there is a strong direct propagation path. The main advantage of using the precoder is that the impairment of ISI due to multipath propagation on the transmission performance can be mitigated without increasing the complexity of the portable unit receiver. The proposed technique is especially useful for personal communications, where ISI due to multipath fading channels can severely deteriorate the BER transmission performance and where the simplicity of portable units is a vital characteristic of the system     

Reducing overhead in movement based dynamic location management scheme for cellular networks

One of the key issues in cellular mobile communication is to find the current location of mobile terminal (MT) to deliver the services, which is called location management (LM). Much research has been done on dynamic LM that reduced the LM cost up to a large extent. In movement based dynamic LM scheme, the location area is defined in the form of ring of cells for individual user. Whenever an MT visits a cell outside of its current location area (LA), it triggers location update (LU). For this purpose, network must inform the mobile terminal about ID of all the cells present in its current location area. In this paper, a simple way of cell-ID assignment is proposed under which, network sends only the ID of center cell of LA ring to MT and then MT can compute IDs of all other cells in its location area. This saves a significant amount of wireless bandwidth by minimizing the signaling traffic at VLR level and thus reduces the mobility management overhead.     

Reducing location map in prediction-based difference expansion for reversible image data embedding

In this paper, we present a reversible data embedding scheme based on an adaptive edge-directed prediction for images. It is known that the difference expansion is an efficient data embedding method. Since the expansion on a large difference will cause a significant embedding distortion, a location map is usually employed to select small differences for expansion and to avoid overflow/underflow problems caused by expansion. However, location map bits lower payload capacity for data embedding. To reduce the location map, our proposed scheme aims to predict small prediction errors for expansion by using an edge detector. Moreover, to generate a small prediction error for each pixel, an adaptive edge-directed prediction is employed which adapts reasonably well between smooth regions and edge areas. Experimental results show that our proposed data embedding scheme for natural images can achieve a high embedding capacity while keeping the embedding distortion low.     

Smart-antenna operation for indoor wireless local-area networks using OFDM

This paper reports link-level Monte Carlo simulations for a system that is compatible with the physical layer of the 5-GHz IEEE 802.11a wireless-local-area network and utilizes an adaptive antenna array at the access point for single-user smart-antenna operation, as well as for space-division multiple access (SDMA). For the spatial indoor radio propagation channel, complex impulse-response recordings are used. These are obtained in wideband channel-sounder measurements in three different buildings at 5.3 GHz. Thus, no unrealistic assumptions about channel conditions are involved. The paper studies how the packet-error-rate performance for the downlink (DL) is affected by time evolution of the radio channel that takes place after the uplink operation in which channel estimation is performed, and before DL operation in which the estimated channel information is utilized. Based on simulations two-user SDMA is possible with four-antenna elements under indoor propagation conditions and with six antennas three users can simultaneously be served. Delay spreads, coherence bandwidths, and correlation properties (in space, frequency, and polarization) of the radio channels obtained in the measurements are also discussed. The results suggest that indoor time-division-duplex systems with access-point-controlled scheduling are desirable communication systems which can benefit from SDMA.     

Empirical pathloss model for indoor geolocation using UWB measurements

A novel empirical approach is presented for modelling the path loss behaviour of the direct path (DP) between the transmitter and receiver, which is important for time-of-arrival-based indoor geolocation coverage characterisation. Using ultra wideband (UWB) measurements in four sites and three ranging scenarios, pathloss models at 500 MHz and 3 GHz system bandwidths are provided, centred on 4.5 GHz for DP and total signal power. In addition, ranging coverage analysis is provided using the DP models     

A new method for fingerprint matching using phase-only auto- and cross-bispectrum

Fingerprints are widely used in biometric techniques for automatic personal identification. In this work, we present a new correlation-based approach which uses the phase-only auto- and cross-bispectrum. This paper deals with the problem of aligning two fingerprints images under translation and rotation. The method described utilizes the shift invariance property of the auto-bispectrum to eliminate the effect of the translation component. Only the phase information is preserved from the auto-bispectrum in order to achieve better resilience against non-uniform illumination changes. The input fingerprint image that gives the highest correlation peak is selected as the rotation-normalized image. The theoretical basis for fingerprint matching by auto- and cross-bispectrum analysis is presented. To prove the feasibility of the proposed method, we compared it to a the method proposed by Ito et al. (IEICE Trans Fundam E87-A(3):682–691, 2004) implemented in a similar manner as our approach. The experiments executed on FVC 2004 have shown that the suggested algorithm is successful on the bad or poor quality fingerprint images. The algorithm is robust providing accurate results in most of the time.