Extended Kalman Filter-based localization algorithm by edge computing in Wireless Sensor Networks

The Extended Kalman Filter (EKF) has received abundant attention with the growing demands for robotic localization. The EKF algorithm is more realistic in non-linear systems, which has an autonomous white noise in both the system and the estimation model. Also, in the field of engineering, most systems are non-linear. Therefore, the EKF attracts more attention than the Kalman Filter (KF). In this paper, we propose an EKF-based localization algorithm by edge computing, and a mobile robot is used to update its location concerning the landmark. This localization algorithm aims to achieve a high level of accuracy and wider coverage. The proposed algorithm is helpful for the research related to the use of EKF localization algorithms. Simulation results demonstrate that, under the situations presented in the paper, the proposed localization algorithm is more accurate compared with the current state-of-the-art localization algorithms.     

Land mobile GNSS availability and multipath evaluation tool

Applications of global navigation satellite system (GNSS) in land transportation systems are already extensively deployed and will certainly continue to grow especially in the framework of intelligent transport systems. However, one of the best-known drawbacks of such a system is the lack of satellite visibility in dense urban areas as well as in some specific embedded railway environments. This restricts considerably GNSS use for extended safety related applications. In this paper, a new tool is proposed to predict the availability of a satellite constellation from the point of view of the land transportation user. Knowing the trajectory of a land vehicle, the tool predicts the number of satellites that will be received and produces a safety criterion able to qualify the GNSS localization result. A first version of the tool, already in operation, merges an image processing approach providing the knowledge of the land environment, and the output of a satellite tracking program predicting satellite positions in the sky. This allows us to determine, using a simple optical approach, the number of satellites received in line-of-sight or blocked, with regard to the nearby environment of the receiving antenna. Results obtained in railway as well as in road environments show that satellite signals received by multipath are often used by GNSS receivers in the localization process. Thus, propagation characteristics of the satellite signals in an urban canyon configuration were characterized to determine when a signal received by reflected ray is used by the receiver or not. A criterion related to the satellite elevation is defined to improve the overall performance of the predictive tool. Comparisons with real measurements are commented on. Both simulations and measurements are very similar.     

Localization systems for wireless sensor networks

Monitoring applications define an important class of applications used in wireless sensor networks. In these applications the network perceives the environment and searches for event occurrences (phenomena) by sensing different physical properties, such as temperature, humidity, pressure, ambient light, movement, and presence (for target tracking). In such cases the location information of both phenomena and nodes is usually required for tracking and correlation purposes. In this work we summarize most of the concepts related to localization systems for WSNs as well as how to localize the nodes in these networks (which allows the localization of phenomena). By dividing the localization systems into three distinct components -distance/angle estimation, position computation, and localization algorithm - besides providing a didactic viewpoint, we show that these components can be seen as subareas of the localization problem that need to be analyzed and studied separately.     

GUIDE: Smartphone sensors‐based pedestrian indoor localization with heterogeneous devices

A plethora of indoor localization systems based on Wi‐Fi, radio frequency chips, ultra‐wide‐band, and bluetooth have been proposed, yet these systems do not work when the infrastructure is absent. On the other hand, infrastructure less systems benefit mostly from off‐the‐shelf smartphone sensors and do not need additional hardware. This study shows a similar indoor localization approach which turns smartphone built‐in sensors to good account. We take advantage of magnetic field strength fingerprinting approach to localize a pedestrian indoor. In addition, accelerometer and gyroscope sensors are utilized to find the pedestrian's traveled distance and heading estimation, respectively. Our aim is to solve the problem of device dependence by devising an approach that can perform localization using various smartphones in a similar fashion. We make the use of patterns of magnetic field strength to formulate the fingerprint database to achieve this goal. This approach solves two problems: need to update the database periodically and device dependence. We conduct experiments using Samsung Galaxy S8 and LG G6 for five different buildings with different dimensions in Yeungnam University, Republic of Korea. The evaluation is performed by following three different path geometries inside the buildings. The results show that the proposed localization approach can potentially be used for indoor localization with heterogeneous devices. The errors for path 1 and path 2 are very similar, however, localization error for path 3 is comparatively higher because of the complexity of the path 3. The mean and median errors for Galaxy S8 are 1.37 and 0.88 m while for LG G6, these are 1.84 and 1.21 m, respectively, while considering all buildings and all paths followed during the experiment. Overall, the proposed approach can potentially localize a pedestrian within 1.21 m at 50% and within 1.93 m at 75%, irrespective of the device used for localization. The performance of the proposed approach is compared with the K nearest neighbor (KNN) for evaluation. The proposed approach outperforms the KNN     

"Seeing" in the dark: neuromorphic VLSI modeling of bat echolocation

While modern sonar and radar processing systems are constructed using large sensor arrays that have incredible imaging and localization capabilities, the question of what bats experience and how they process echo data with only two ears and a pea-sized brain remains a major mystery. The exploration of this question and the attempt to construct a functional model of the bat's neural signal processing using neuromorphic very large scale integration (VLSI) techniques and robotics have provided an interesting framework for our laboratory's research program.     

Energy-accuracy trade-offs for hybrid localization using RSS and inertial measurements in wireless sensor networks

This paper presents a framework for optimizing the trade-off between energy consumption and localization accuracy in hybrid localization systems combining Received Signal Strength (RSS) measurements with inertial ones. The proposed framework aims at finding the optimal operation point that minimizes the radio energy consumption for a desired target accuracy, or equivalently, the one that maximizes the localization accuracy for a given energy budget. To this end, the proposed approach considers the joint optimization of the localization frequency and number of RSS measurements used at each localization round and leverages practical models to predict the energy consumption and the localization accuracy for combined RSS-inertial localization systems. Simulations and real-field experiments are used to demonstrate that, for a given target accuracy, the proposed strategy entails a lower energy consumption than state-of-the-art methods available in the literature.     

Facing the defect characterization and localization challenges of bridge defects on a submicronic technology (45 nm and below)

For very deep submicron technologies, 45 nm and less, bridge defects are getting more and more complex and critical. In order to find the exact root cause, accurate defect localization, precise understanding on the nature of the defect and its impact on the fine electrical behaviour of the device are mandatory. At these ultimate technologic nodes, failure analysis techniques show a real lack of efficiency on bridge defect localization while this precise location is one of the keys to find the defect root cause that allows correct implementation of corrective actions to improve yield and reliability.To face this challenge we have built a complete set of signatures related to advance Eldo simulations, performed measurement with ultimate failure analysis tools, fully characterized a microelectronic structure in advanced technology presenting a bridge defect and established a complete link between all these data and the failure location.     

多异构阵列归一化数据融合被动定位方法

在水下分布式定位系统中,多个阵列节点往往是异构的,即各节点在阵列构型、幅度归一化参数、工作频带、采样数据量等参数方面存在差异。现有数据融合被动定位方法通常忽略上述差异对定位性能的影响,存在定位精度低、分辨能力差的问题。针对这一问题,该文首先建立了基于多个异构阵列的接收信号模型,特别是将幅度归一化参数纳入接收信号模型中,并且考虑了各节点阵列参数的不同;其次,推导目标坐标的最大似然估计方法,并对该方法的融合方式进行了理论分析;最后,为了提高分布式定位系统对多目标的分辨能力,该文进一步将最小方差无失真响应空间谱纳入上述融合方式之中,提出基于多异构阵列的最小方差无失真响应定位方法。仿真结果与实测数据验证了所提的两种方法相对于已有方法在定位精度和分辨能力方面的优势。     

SAM LOST smart antennas-based movable localization system

Nowadays, wireless position location of multiple sources attracts considerable interest, not only for military, law-enforcement, and public safety applications, but also in the field of intelligent transportation systems and location-specific commercial services. In this paper, we present a complete, autonomous, and movable-on-demand localization system. It is based on the estimation of the direction of arrival of signals emitted by mobile sources, impinging on an array of sensors placed on board a mobile localization station, represented by any aerial or terrestrial vehicle. The system is especially tailored for wireless users unable to perform self-localization, and its most attractive characteristic is its inherent mobility, which allows a quick employment "on demand", in emergency situations, where other localization infrastructures are not present or are unable to properly operate. Procedures of autolocalization and autoorientation of the localization station, based on a set of emitting sources in known location, are considered as well. The user to be located should only be equipped with a very simple radio transmitter, whose signal can be received and identified by the localization station. Alternatively, in more sophisticated scenarios, the user's equipment can be a personal mobile phone, seamlessly connected with the localization station acting as a temporary base station. The performance of the overall system has been evaluated for a case of code division multiple access (CDMA)-based transceiver via computer simulations, showing that the achievable accuracy for locating the user position can fulfil the Federal Communications Commission (FCC) E-911 standard requirements for emergency calls over reasonably wide coverage areas.     

Range-free localization algorithm based on connectivity and motion

Information about the position of entities is very valuable in many fields. People, animals, robots and sensors are some examples of entities that have been targeted as nodes of interest for localization purposes. Technical advances in ubiquitous computing and wireless communications properties are very valuable means to obtain localization information. This paper presents a novel range-free localization algorithm based on connectivity and motion (LACM). The core of the algorithm is an error function that measures the error of the obtained trajectories with respect to the localization solution space, a multi-dimensional space that encompasses all solutions that satisfy completely the constraints of a range-free localization problem. LACM is a centralized method that can be used standalone or as a refinement phase for other localization methods. Limited-memory Broyden–Fletcher–Goldfarb–Shanno, an unconstrained optimization algorithm, is the numerical method used to minimize the error function. The performance of LACM is validated both through extensive simulations with excellent results in scenarios with irregular communications and by transforming real Bluetooth connectivity traces into localization information.     

Aubry模型和Soukoulis－Economou模型电子态局域性质的区别

Ａｕｂｒｙ模型和Ｓｏｕｋｏｕｌｉｓ－Ｅｃｏｎｏｍｏｕ模型是一维无公度系统的两个重要模型，它们都存在扩展态和局域态两种本征态。本文用数值结果表明，两种模型的局域态局域方式不同，前者局域态的波函数局域在系统的一个小范围内，后者局域态的波函数呈梳状分散地局域在系统的许多小区域。这一结果对于进一步研究Ａｕｂｒｙ模型和Ｓｏｕｋｏｕｌｉｓ－Ｅｃｏｎｏｍｏｕ模型有重要意义。     

Decentralized Consensus Based Target Localization in Wireless Sensor Networks

Target localization is an attractive subject for modern systems that utilize different types of distributed sensors for location based services such as navigation, public transport, retail services and so on. Target localization could be performed in both centralized and decentralized manner. Due to drawbacks of centralized systems such as security and reliability issues, decentralized systems are become more desirable. In this paper, we introduce a new decentralized and cooperative target localization algorithm for wireless sensor networks. In cooperative consensus based localization, each sensor knows its own location and estimates the targets position using the ranging techniques such as received signal strength. Then, all nodes cooperate with their neighbours and share their information to reach a consensus on targets location. In our proposed algorithm, we weight the received information of neighbour nodes according to their estimated distance toward the target node. Simulation results confirm that our proposed algorithm is faster, less sensitive to targets location and improves the localization accuracy by 85% in comparison with distributed Gauss–Newton algorithm.     

Aubry模型和Soukoulis－Economou模型电子态局域性质的区别

Ａｕｂｒｙ模型和Ｓｏｕｋｏｕｌｉｓ－Ｅｃｏｎｏｍｏｕ模型是一维无公度系统的两个重要模型，它们都存在扩展态和局域态两种本征态。本文用数值结果表明，两种模型的局域态局域方式不同，前者局域态的波函数局域在系统的一个小范围内，后者局域态的波函数呈梳状分散地局域在系统的许多小区域。这一结果对于进一步研究Ａｕｂｒｙ模型和Ｓｏｕｋｏｕｌｉｓ－Ｅｃｏｎｏｍｏｕ模型有重要意义。     

无线传感器网络定位算法综述

无线传感器网络(WSN)是一个多学科的研究领域,具有很广泛的应用前景,其中,WSN的定位是非常重要的研究方向。介绍了国内外研究机构在WSN定位方面的研究进展,并对这些工作进行了归纳和总结。将每种定位算法按照需不需要测距分为两大类,而且在具体算法中讨论了其以下几个特征,包括:需要/不需要锚节点、集中式/分布式、固定/移动等。     

基于频控阵的无源定位对抗技术

无源定位技术是现代电子战领域中重要的组成部分,然而现有的对抗无源定位系统采用的射频隐身、电子干扰等传统方法仍存在着很大的局限性。该文提出将频控阵技术应用到无源定位对抗领域,频控阵独特的波束扫描特性使得主波束在同一方位角度位置处的波束驻留时间缩短,无源定位系统无法长时间截获频控阵信号。另一方面,频控阵信号的时变特性使得无源定位系统接收信号信噪比大大降低,因此能有效地增加无源定位系统的定位误差,降低其定位效能。搭载有频控阵辐射源的电子系统在利用自身辐射信号对外部环境进行感知的同时,又能阻止敌方的无源定位系统对其实施定位侦察。理论分析和仿真验证均证实了频控阵辐射源针对干涉仪测向与时频差定位两种无源定位方法具备优良的对抗性能,该文的仿真实例显示采用频控阵辐射源时其探测精度明显降低,从而为研究同时具备主动探测和无源定位对抗能力的新一代电子系统提供了新的技术思路。      

A RSS-based localization method using HMM-based error correction

ABSTRACT

Indoor localization and tracking systems are harvesting more attention from the researchers. Recently, several approaches for localization systems have been proposed that use the sensors which are available on smartphones. In this paper, a new filtering approach based on Hidden Markov Model (HMM) techniques to enhance the accuracy of the localization system is presented. The proposed approach filtered out the undesirable Received Signal Strength (RSS) values which affect the accuracy of the system using the hidden states. The proposed approach helps in the direction and the distance estimation. The results of the proposed approach show a significant improvement in terms of distance estimation and the filtering of the RSS values.     

室内定位技术及应用综述

室内定位技术作为当前的研究热点,对军事、经济以及人们的日常生活产生了深远的影响。文中首先介绍了室内定位技术的应用背景以及发展方向,以及室内环境进行定位面临的主要难点。然后介绍了目前主要的定位算法,包括邻近信息、场景分析和几何定位算法,以及各种算法衍生出来的各种定位技术。最后指出了室内定位技术亟待解决的问题,以及下一步进行相关研究的突破口。     

An analysis of error inducing parameters in multihop sensor node localization

Ad hoc localization of wireless sensor nodes is a fundamental problem in wireless sensor networks. Despite the recent proposals for the development of ad hoc localization algorithms, the fundamental behavior in systems using measurements has not been characterized. In this paper, we take a first step toward such a characterization by examining the behavior of error inducing parameters in multihop localization systems in an algorithm independent manner. We first derive the Crame Rao Bound for Gaussian measurement error for multihop localization systems using distance and angular measurements. Later on, we use these bounds on a carefully controlled set of scenarios to study the trends in the error induced by the measurement technology accuracy, network density, beacon node concentration, and beacon uncertainty. By exposing these trends, the goal of this paper is to develop a fundamental understanding of the error behavior that can provide a set of guidelines to be considered during the design and deployment of multihop localization systems.     

无线传感器网络节点定位算法研究

作为一种全新的信息获取和处理技术,拥有十分广泛的应用前景,其中,节点定位是重要的核心技术之一,同时也是无线传感器网络技术及应用的最核心的技术基础。目前已有的定位方法主要是按照基于测距和非基于测距进行分类总结。在研究大量相关文献的基础上,用一种全新的视角对目前现有的定位方法进行重新分类,介绍了WSN无线信号衰减模型,提出一种基于RSSI校验的加权质心节点定位算法,且与相关定位算法进行了比较分析和仿真实验得出结论。     

Geometrical Localization Algorithm for Three Dimensional Wireless Sensor Networks

The issue of localization has been addressed in many research areas such as vehicle navigation systems, virtual reality systems, user localization in wireless sensor networks (WSNs). In this paper, we have proposed an efficient range-free localization algorithm: Geometrical Localization Algorithm (GLA) for large scale three dimensional WSNs. GLA uses moving anchors to localize static sensors. GLA consists of beacon message selection, circular cross section selection. Three beacon messages are used to compute the center of circular cross section using vector method and perpendicular bisector method. The static sensors are localized with help of the center of circular cross section and geometrical rules for sphere. GLA is simulated in SINALGO software and results have been compared with existing methods namely chord selection and point localization. GLA outperforms both the compared methods in terms of average localization time and beacon overhead.