Hybrid Positioning Research Articles

Empirical Analysis of TOA and AOA in Hybrid Location Positioning Techniques

We explored the role of TOA and AOA in hybrid positioning algorithms in the LOS environment, as well as the effects of weight parameters. We built a model to simulate the experimental process. The simulation environment is an environment of a multi-base station single mobile terminal built on a cellular network. We observed the change of the positioning error by changing the weight of the base station TOA and AOA, so as to analyze the influence of the weight parameter on the accuracy. The final simulation results show that AOA has little effect on the positioning algorithm in LOS communication, and the positioning algorithm mainly depends on TOA. The results of others do not indicate the role of weight parameters in the positioning algorithm, and our research makes up for this vacancy.

Methodology for Simulating 5G and GNSS High-Accuracy Positioning.

This paper focuses on the exploitation of fifth generation (5G) centimetre-wave (cmWave) and millimetre-wave (mmWave) transmissions for high-accuracy positioning, in order to complement the availability of Global Navigation Satellite Systems (GNSS) in harsh environments, such as urban canyons. Our goal is to present a representative methodology to simulate and assess their hybrid positioning capabilities over outdoor urban, suburban and rural scenarios. A novel scenario definition is proposed to integrate the network density of 5G deployments with the visibility masks of GNSS satellites, which helps to generate correlated scenarios of both technologies. Then, a generic and representative modeling of the 5G and GNSS observables is presented for snapshot positioning, which is suitable for standard protocols. The simulations results indicate that GNSS drives the achievable accuracy of its hybridisation with 5G cmWave, because non-line-of-sight (NLoS) conditions can limit the cmWave localization accuracy to around 20 m. The 5G performance is significantly improved with the use of mmWave positioning with dominant line-of-sight (LoS) conditions, which can even achieve sub-meter localization with one or more base stations. Therefore, these results show that NLoS conditions need to be weighted in 5G localization, in order to complement and outperform GNSS positioning over urban environments.

A Survey of Positioning Systems Using Visible LED Lights

As Global Positioning System (GPS) cannot provide satisfying performance in indoor environments, indoor positioning technology, which utilizes indoor wireless signals instead of GPS signals, has grown rapidly in recent years. Meanwhile, visible light communication (VLC) using light devices such as light emitting diodes (LEDs) has been deemed to be a promising candidate in the heterogeneous wireless networks that may collaborate with radio frequencies (RF) wireless networks. In particular, light-fidelity has a great potential for deployment in future indoor environments because of its high throughput and security advantages. This paper provides a comprehensive study of a novel positioning technology based on visible white LED lights, which has attracted much attention from both academia and industry. The essential characteristics and principles of this system are deeply discussed, and relevant positioning algorithms and designs are classified and elaborated. This paper undertakes a thorough investigation into current LED-based indoor positioning systems and compares their performance through many aspects, such as test environment, accuracy, and cost. It presents indoor hybrid positioning systems among VLC and other systems (e.g., inertial sensors and RF systems). We also review and classify outdoor VLC positioning applications for the first time. Finally, this paper surveys major advances as well as open issues, challenges, and future research directions in VLC positioning systems.

Offloading Positioning onto Network Edge

While satellite or cellular positioning implies dedicated hardware or network infrastructure functions, indoor navigation or novel IoT positioning techniques include flexible storage and computation requirements that can be fulfilled by both end‐devices or cloud back‐ends. Hybrid positioning systems support the integration of several algorithms and technologies; however, the common trend of delegating position calculation and storage of local geoinformation to mobile devices or centralized servers causes performance degradation in terms of delay, battery usage, and waste of network resources. The strategy followed in this work is offloading this computation effort onto the network edge, following a Mobile Edge Computing (MEC) approach. MEC nodes in the access network of the mobile device are in charge of receiving navigation data coming from both the smart infrastructure and mobile devices, in order to compute the final position following a hybrid approach. With the aim of supporting mobility and the access to multiple networks, an Information Centric Networking (ICN) solution is used to access generic position information resources. The presented system currently supports WiFi, Bluetooth LE, GPS, cellular and NFC technologies, involving both indoor and outdoor positioning, using fingerprinting and proximity for indoor navigation, and the integration of smart infrastructure data sources such as the door opening system within real smart campus deployment. Evaluations carried out reveal latency improvements of 50%, as compared with a regular configuration where position fixes are computed by mobile devices; at the same time the MEC solution offers extra flexibility features to manage positioning databases and algorithms and move extensive computation from constrained devices to the edge.

Towards an efficient indoor navigation system: a near field communication approach

PurposeThis research aims to focus on providing interventions to alleviate usability challenges to strengthen the overall accuracy and the navigation effectiveness in indoor and stringent environments through the experiential manipulation of technical attributes of the positioning and navigation system.Design/methodology/approachThe study followed a quantitative and experimental method of empirical enquiry and software engineering and synthesis research methods. The study further entails three implementation processes, namely, map generation, positioning framework and navigation service using a prototype mobile navigation application that uses the near field communication (NFC) technology.FindingsThe approach and findings revealed that the capability of NFC in leveraging its low-cost infrastructure of passive tags, its availability in mobile devices and the ubiquity of the mobile device provided a cost-effective solution with impressive accuracy and usability. The positioning accuracy achieved was less than 9 cm. The usability improved from 44 to 96 per cent based on feedbacks given by respondents who tested the application in an indoor environment. These showed that NFC is a viable alternative to resolve the challenges identified in previous solutions and technologies.Research limitations/implicationsThe major limitation of the navigation application was that there is no real-time update of user position. This can be investigated and extended further by using NFC in a hybrid make-up with WLAN, radio-frequency identification (RFID) or Bluetooth as a cost-effective solution for real-time indoor positioning because of their coverage and existing infrastructures. The hybrid positioning model, which merges two or more techniques or technologies, is becoming more popular and will improve its accuracy, robustness and usability. In addition, it will balance complexity, compensate for the limitations in the technologies and achieve real-time mobile indoor navigation. Although the presence of WLAN, RFID and Bluetooth technologies are likely to result in system complexity and high cost, NFC will reduce the system’s complexity and balance the trade-off.Practical implicationsWhilst limitations in existing indoor navigation technologies meant putting up with poor signal and poor communication capabilities, outcomes of the NFC framework will offer valuable insight. It presents new possibilities on how to overcome signal quality limitations at improved turn-around time in constrained indoor spaces.Social implicationsThe innovations have a direct positive social impact in that it will offer new solutions to mobile communications in the previously impossible terrains such as underground platforms and densely covered spaces. With the ability to operate mobile applications without signal inhibitions, the quality of communication – and ultimately, life opportunities – are enhanced.Originality/valueWhile navigating, users face several challenges, such as infrastructure complexity, high-cost solution, inaccuracy and usability. Hence, as a contribution, this paper presents a symbolic map and path architecture of a floor of the test-bed building that was uploaded to OpenStreetMap. Furthermore, the implementation of the RFID and the NFC architectures produced new insight on how to redress the limitations in challenged spaces. In addition, a prototype mobile indoor navigation application was developed and implemented, offering novel solution to the practical problems inhibiting navigation in indoor challenged spaces – a practical contribution to the community of practice.

The influence of global and local iconic brand positioning on advertising persuasion in an emerging market setting

This study explores how positioning a brand as global and/or local iconic can moderate the impact of advertising frequency (AF) on brand attitudes in an emerging market context. We argue that brands may be seen as the source of an advertisement and that the positioning of a brand can thus enhance source attractiveness, and/or source credibility, which in turn facilitate the impact of AF on brand attitudes. Our results support that both a global and a local iconic positioning enhance the AF–brand image relationship, but they do not have an effect on the AF–brand quality relationship. Additionally, we examine whether source attractiveness and source credibility mediate these moderation effects and find that only source attractiveness is a significant mediator. Additionally, we investigate whether a hybrid positioning strategy (i.e., positioning as both global and local iconic) is beneficial. Results indicate that a separate positioning (i.e., global or local iconic) is a better strategy to increase the attractiveness of the advertising source and in turn facilitate the effect of advertising frequency to create brand image.

Ubiquitous and Seamless Localization: Fusing GNSS Pseudoranges and WLAN Signal Strengths

Ubiquitous global positioning is not feasible by GNSS alone, as it lacks accurate position fixes in dense urban centres and indoors. Hybrid positioning methods have been developed to aid GNSS in those environments. Fingerprinting localization in wireless local area networks (WLANs) is a promising aiding system because of its availability, accuracy, and error mechanisms opposed to that of GNSS. This article presents a low-cost approach to ubiquitous, seamless positioning based on a particle filter integrating GNSS pseudoranges and WLAN received signal strength indicators (RSSIs). To achieve accurate location estimates indoors/outdoors and in the transition zones, appropriate likelihood functions are essential as they determine the influence of each sensor information on the position estimate. We model the spatial RSSI distributions with Gaussian processes and use these models to predict RSSIs at the particle’s positions to obtain point estimates of the RSSI likelihood function. The particle filter’s performance is assessed with real data of two test trajectories in an environment challenging for GNSS and WLAN fingerprinting localization. Outcomes of an extended Kalman filter using pseudoranges and a WLAN position as observation is included as benchmark. The proposed algorithm achieves accurate and robust seamless localization with a median accuracy of five meters.

Methods of Controlling a Hybrid Positioning System Using LabVIEW

The paper presents the design of positioning unit acting in a different way with respect to the known methods of controlling the positioning devices. The prototype positioning unit consists of a double-acting cylinder and electromagnetic brake. The proposed hybrid positioning unit allows to free programming of the displacement of the actuator. In the illustrated solution significant disadvantages which often occur in the positioning pneumatic drives were eliminated. The proposed hybrid positioning system provides to maintain the desired position, shorter positioning times, a higher average speed of the piston and a higher positioning accuracy. The fulfilment of such parameters provide a construction of accordingly developed unit which consist of pneumatic drive and control system. Element of control system is the measuring card NI PCI-6221 for data acquisition and control system positioning. LabVIEW allow to control the object, carrying out the visualization of the process control and analysis of measurement data.

Advanced Pedestrian Positioning System to Smartphones and Smartwatches.

In recent years, there has been an increasing interest in the development of pedestrian navigation systems for satellite-denied scenarios. The popularization of smartphones and smartwatches is an interesting opportunity for reducing the infrastructure cost of the positioning systems. Nowadays, smartphones include inertial sensors that can be used in pedestrian dead-reckoning (PDR) algorithms for the estimation of the user’s position. Both smartphones and smartwatches include WiFi capabilities allowing the computation of the received signal strength (RSS). We develop a new method for the combination of RSS measurements from two different receivers using a Gaussian mixture model. We also analyze the implication of using a WiFi network designed for communication purposes in an indoor positioning system when the designer cannot control the network configuration. In this work, we design a hybrid positioning system that combines inertial measurements, from low-cost inertial sensors embedded in a smartphone, with RSS measurements through an extended Kalman filter. The system has been validated in a real scenario, and results show that our system improves the positioning accuracy of the PDR system thanks to the use of two WiFi receivers. The designed system obtains an accuracy up to 1.4 in a scenario of 6000 .

A hybrid positioning approach based on mechanical calculus model and grid simulation for drifting debris

This paper proposes an approach to position the drifting aircraft debris after a crash accident based on a hybrid model, which includes a mechanical calculus part and an advanced ocean model part. The most probable crash area is firstly established via mechanical calculus analysis on the normal forced landing process and the abnormal crashing process. Then the numerical simulation is taken to calculate the drifting process of the debris. A simulation approach based on the grid-measurement and the improved ocean model is used to predict the most possible domain of the drifting debris in the several following days. The impact of using the advanced ocean model on positioning the drifting debris is studied, on which the idealized current flow is used but the effect of winds is ignored. The case study of MH370 and the sensitivity analysis indicate the validity of the model. The proposed work enables further research on quick positioning of drifting debris after an aircraft crash.

A Reliable Hybrid Positioning Methodology for Land Vehicles Using Low-Cost Sensors

In this paper, we propose a reliable hybrid positioning methodology by combining the advantages of $\mbox{H}\infty$ filter and extreme learning machine (ELM), which addresses GPS outages and uncertain nonlinear drift of MEMS INS simultaneously. A novel parallel-dual- $\mbox{H}\infty$ filtering (PDHF) mechanism is proposed to prevent the $\mbox{H}\infty$ filter from diverging during GPS outages and to make full use of supplementary observations. The PDHF is composed of an enhanced $\mbox{H}\infty$ filter and an auxiliary $\mbox{H}\infty$ filter. The enhanced $\mbox{H}\infty$ filter is developed by fusing not only GPS information but also supplementary observations, which include yaw angle provided by electronic compass, longitudinal velocity derived from wheel speed sensor, and lateral velocity constrained by assumptions, whereas the auxiliary $\mbox{H}\infty$ filter only fuses the supplementary observations. Furthermore, an ELM module with good generalization ability is designed and augmented with the auxiliary $\mbox{H}\infty$ filter to constitute a “virtual enhanced $\mbox{H}\infty$ filter.” In the case of GPS outages, the “virtual enhanced $\mbox{H}\infty$ filter” provides accurate corrections for stand-alone INS. Due to the characteristics of the $\mbox{H}\infty$ filter, the proposed methodology is immune to uncertain nonlinear drift of MEMS INS in nature. To verify the effectiveness of the proposed methodology, road-test experiments with various scenarios were performed. The experimental results indicate that the proposed methodology outperform all the compared counterparts.

TemG : 시한적 속성을 갖고 있는 지오펜스 플랫폼

Geofence is a generic concept for describing geographic aspects of PoI(Point of Interest) enabling users to proactively induce context-based actions. However there is no need to maintain continuity when you reflect geofence in case of temporary events, accidents and isolation. Therefore we propose a geofence platform so-called TemG by adding time-limited information to support PoI. The proposed geofence platform TemG ensures the persistency and continuity of geofence. Furthermore, the proposed TemG can not only provide to automatically activate or deactivate the specified geofence during a period of timestamp but also support to the basic context-aware service knowing in/out in the zone. In the near future, the proposed TemG will be need to extend HPS(Hybrid Positioning System) for IoT(Internet of Things).

Hybrid Positioning Aided Amorphous-Cell Assisted User-Centric Visible Light Downlink Techniques

Visible light communications (VLCs) have attracted significant attention in recent years, where the novel concept of user-centric (UC) VLC based on amorphous cells (A-Cells) exhibits extra benefits compared with conventional circular cells. The construction of A-Cells relies on the knowledge of the users' positions; hence, the intrinsic amalgamation of VLC and positioning becomes important. Therefore, we propose a novel hybrid positioning technique by beneficially combining the low-complexity of triangulation-based positioning and the high accuracy of fingerprinting, in order to support A-Cell-assisted UC VLC under practical light-emitting diode linearity constraints with clipping distortion and noise. Our simulation results demonstrate that the proposed technique is capable of achieving a much higher positioning accuracy than triangulation at a lower complexity than fingerprinting, where the resultant system throughput is similar to that of perfect positioning.

Hybrid Indoor-Based WLAN-WSN Localization Scheme for Improving Accuracy Based on Artificial Neural Network

In indoor environments, WiFi (RSS) based localization is sensitive to various indoor fading effects and noise during transmission, which are the main causes of localization errors that affect its accuracy. Keeping in view those fading effects, positioning systems based on a single technology are ineffective in performing accurate localization. For this reason, the trend is toward the use of hybrid positioning systems (combination of two or more wireless technologies) in indoor/outdoor localization scenarios for getting better position accuracy. This paper presents a hybrid technique to implement indoor localization that adopts fingerprinting approaches in both WiFi and Wireless Sensor Networks (WSNs). This model exploits machine learning, in particular Artificial Natural Network (ANN) techniques, for position calculation. The experimental results show that the proposed hybrid system improved the accuracy, reducing the average distance error to 1.05 m by using ANN. Applying Genetic Algorithm (GA) based optimization technique did not incur any further improvement to the accuracy. Compared to the performance of GA optimization, the nonoptimized ANN performed better in terms of accuracy, precision, stability, and computational time. The above results show that the proposed hybrid technique is promising for achieving better accuracy in real-world positioning applications.

A Hybrid Positioning Scheme Exploiting Sensors and RSS of Wi-Fi Signals

As interests and demands for indoor positioning have recently increased, a positioning scheme utilizing the smartphone equipped with various sensors like an acceleration sensor and a geomagnetic sensor has been expected as a high potential and practical candidate for indoor positioning purpose. The acceleration sensor and the geomagnetic sensor are used for the estimation of travelled distance and the direction of movement of pedestrians, respectively. Although it provides very accurate positioning performance, the positioning scheme based only sensors tends to be affected by indoor environments like magnetic field of general indoor office building. In addition, the positioning error is apt to be accumulated as the travelled distance is increased. In this paper, therefore, a new positioning scheme is proposed to compensate the conventional positioning technology and to enhance the positioning performance. The proposed scheme consists with positioning based sensors, multi-lateration and WLAN-ID based on received signal strength (RSS) of Wi-Fi signals. The proposed scheme is evaluated with experiments at general building in university and the performance of the proposed scheme is superior to the conventional schemes such as a positioning scheme with only sensors and a positioning scheme based on RSS of Wi-Fi signals only.

A Hybrid Intelligent Multisensor Positioning Methodology for Reliable Vehicle Navigation

With the rapid development of intelligent transportation systems worldwide, it becomes more important to realize accurate and reliable vehicle positioning in various environments whether GPS is available or not. This paper proposes a hybrid intelligent multisensor positioning methodology fusing the information from low-cost sensors including GPS, MEMS-based strapdown inertial navigation system (SINS) and electronic compass, and velocity constraint, which can achieve a significant performance improvement over the integration scheme only including GPS and MEMS-based SINS. First, the filter model of SINS aided by multiple sensors is presented in detail and then an improved Kalman filter with sequential measurement-update processing is developed to realize the filtering fusion. Further, a least square support vector machine- (LS SVM-) based intelligent module is designed and augmented with the improved KF to constitute the hybrid positioning system. In case of GPS outages, the LS SVM-based intelligent module trained recently is used to predict the position error to achieve more accurate positioning performance. Finally, the proposed hybrid positioning method is evaluated and compared with traditional methods through real field test data. The experimental results validate the feasibility and effectiveness of the proposed method.

A hybrid positioning strategy for vehicles in a tunnel based on RFID and in-vehicle sensors.

Many intelligent transportation system applications require accurate, reliable, and continuous vehicle positioning. How to achieve such positioning performance in extended GPS-denied environments such as tunnels is the main challenge for land vehicles. This paper proposes a hybrid multi-sensor fusion strategy for vehicle positioning in tunnels. First, the preliminary positioning algorithm is developed. The Radio Frequency Identification (RFID) technology is introduced to achieve preliminary positioning in the tunnel. The received signal strength (RSS) is used as an indicator to calculate the distances between the RFID tags and reader, and then a Least Mean Square (LMS) federated filter is designed to provide the preliminary position information for subsequent global fusion. Further, to improve the positioning performance in the tunnel, an interactive multiple model (IMM)-based global fusion algorithm is developed to fuse the data from preliminary positioning results and low-cost in-vehicle sensors, such as electronic compasses and wheel speed sensors. In the actual implementation of IMM, the strong tracking extended Kalman filter (STEKF) algorithm is designed to replace the conventional extended Kalman filter (EKF) to achieve model individual filtering. Finally, the proposed strategy is evaluated through experiments. The results validate the feasibility and effectiveness of the proposed strategy.

Hybrid positioning data fusion in heterogeneous networks with critical hearability

In this paper, we propose and investigate a hybrid positioning data fusion technique for heterogeneous networks in critical transmission scenarios. The focus is on two scenarios: the small indoor scenario combining Wi-Fi and cellular systems and the small-to-mid-scale scenario composed of one located Mobile Terminal (MT) and one anchor node (AN). More specifically, we investigate the effect of the availability of three metrics i.e. the time of arrival (ToA), the angle of arrival (AoA), and the received signal strength-based fingerprint (RSS) on the positioning accuracy when the number of ANs is less than three. To combine these measurements, we use a 2-level unscented Kalman Filter (UKF) in conjunction with some advanced clustering techniques based on genetic algorithms. Simulation results show that the proposed hybrid data fusion technique outperforms the techniques presented in the literature independently of the transmission conditions.

Research of BD/GPS Hybrid Positioning Module Based on ARM and GPRS

Based on UM220-BD/GPS hybrid positioning module, LPC1768 module taking ARM Cortex-M3 as the kernel and Q2403A communication module, the receiving and processing data circuit and wireless communication circuit in GPRS are designed. This research develops the processing and controlling data program of LPC1768 module, GPRS communication program in Text and receiving and displaying data program. The article realizes receiving, resolving, processing, transmitting, displaying satellite data and verifies the system functions.

Accuracy synthesis of a multi-level hybrid positioning mechanism for the feed support system in FAST

Abstract This study examines the terminal accuracy synthesis of a multi-level hybrid positioning mechanism for the feed support system in a Five-hundred-meter Aperture Spherical Radio Telescope (FAST) project, specifically considering three types of error influence factors such as time-varying barycenter, geometric error, and structural deformation. An error model caused by a time-varying barycenter and that for the entire mechanism are first established, and the physical meaning of the latter is further explained. The three factors that influence terminal accuracy are then analyzed. An efficient approach for acquiring the terminal error boundary over the entire workspace is proposed on the basis of the vector set theory and a linear algebra method. After employing an error compensation method for the first-level mechanism through control strategy, terminal accuracy synthesis is conducted by using a nonlinear optimization algorithm. Both constraints for accuracy and weight are satisfied after introducing measurement systems. Moreover, the proposed method of accuracy analysis and synthesis can be applied to other multi-level hybrid mechanisms.