Indoor positioning and navigation, part III: navigation systems

In the age of automation the ability to navigate persons and devices in indoor environments has become increasingly important for a rising number of applications. With the emergence of global satellite positioning systems, the performance of outdoor navigation has become excellent, but many mass market applications require seamless navigation capabilities in all environments. Therefore indoor navigation has become a focus of research and development during the past decade. It has by now become apparent that there is no overall solution based on a single technology, such as that provided outdoors by satellite-based navigation

Positioning algorithms for RFID-based multi-sensor indoor/outdoor positioning techniques

Position information has been very important. People need this information almost everywhere all the time. However, it is a challenging task to provide precise positions indoor/outdoor seamlessly. Outdoor positioning has been widely studied and accurate positions can usually be achieved by well developed GPS techniques. However, these techniques are difficult to be used indoor since GPS signals are too weak to be received. The alternative techniques, such as inertial sensors and radio-based pseudolites, can be used for indoor positioning but have limitations. For example, the inertial sensors suffer from drifting problems caused by the accumulating errors of measured acceleration and velocity and the radio-based techniques are prone to the obstructions and multipath effects of the transmitted signals. It is therefore necessary to develop improved methods for minimising the limitations of the current indoor positioning techniques and providing an adequately precise solution of the indoor positioning and seamless indoor/outdoor positioning. The main objectives of this research are to investigate and develop algorithms for the low-cost and portable indoor personal positioning system using Radio Frequency Identification (RFID) based multi-sensor techniques, such as integrating with Micro-Electro-Mechanical Systems (MEMS) Inertial Navigation System (INS) and/or GPS. A RFID probabilistic Cell of Origin (CoO) algorithm is developed, which is superior to the conventional CoO positioning algorithm in its positioning accuracy and continuity. Integration algorithms are also developed for RFID-based multi-sensor positioning techniques, which can provide metre-level positioning accuracy for dynamic personal positioning indoors. In addition, indoor/outdoor seamless positioning algorithms are investigated based on the iterated Reduced Sigma Point Kalman Filter (RSPKF) for RFID/MEMS INS/low-cost GPS integrated technique, which can provide metre-level positioning accuracy for personal positioning. 3-D GIS assisted personal positioning algorithms are also developed, including the map matching algorithm based on the probabilistic maps for personal positioning and the Site Specific (SISP) propagation model for efficiently generating the RFID signal strength distributions in location fingerprinting algorithms. Both static and dynamic indoor positioning experiments have been conducted using the RFID and RFID/MEMS INS integrated techniques. Metre-level positioning accuracy is achieved (e.g. 3.5m in rooms and 1.5m in stairways for static position, 4m for dynamic positioning and 1.7m using the GIS assisted positioning algorithms). Various indoor/outdoor experiments have been conducted using the RFID/MEMS INS/low-cost GPS integrated technique. It indicates that the techniques selected in this study, integrated with the low-cost GPS, can be used to provide continuous indoor/outdoor positions in approximately 4m accuracy with the iterated RSPKF. The results from the above experiments have demonstrated the improvements of integrating multiple sensors with RFID and utilizing the 3-D GIS data for personal positioning. The algorithms developed can be used in a portable RFID based multi-sensor positioning system to achieve metre-level accuracy in the indoor/outdoor environments. The proposed system has potential applications, such as tracking miners underground, monitoring athletes, locating first responders, guiding the disabled and providing other general location based services (LBS)

A multimodal Fingerprint-based Indoor Positioning System for airports

[EN] Indoor Localization techniques are becoming popular in order to provide a seamless indoor positioning system enhancing the traditional GPS service that is only suitable for outdoor environments. Though there are proprietary and costly approaches targeting high accuracy positioning, Wi-Fi and BLE networks are widely deployed in many public and private buildings (e.g. shopping malls, airports, universities, etc.). These networks are accessible through mobile phones resulting in an effective commercial off-the-self basic infrastructure for an indoor service. The obtained positioning accuracy is still being improved and there is on-going research on algorithms adapted for Wi-Fi and BLE and also for the particularities of indoor environments. This paper focuses not only on indoor positioning techniques, but also on a multimodal approach. Traditional proposals employ only one network technology whereas this paper integrates two different technologies in order to provide improved accuracy. It also sets the basis for combining (merging) additional technologies, if available. The initial results show that the positioning service performs better with a multimodal approach compared to individual (monomodal) approaches and even compared with Google¿s geolocation service in public spaces such as airports.This work was supported in part by the European Commission through the Door to Door Information for Airports and Airlines Project under Grant GA 635885 and in part by the European Commission through the Interoperability of Heterogeneous IoT Platforms Project under Grant 687283.Molina Moreno, B.; Olivares-Gorriti, E.; Palau Salvador, CE.; Esteve Domingo, M. (2018). A multimodal Fingerprint-based Indoor Positioning System for airports. IEEE Access. 6:10092-10106. https://doi.org/10.1109/ACCESS.2018.2798918S1009210106

The Impact of Interference on GNSS Receiver Observables – A Running Digital Sum Based Simple Jammer Detector

A GNSS-based navigation system relies on externally received information via a space-based Radio Frequency (RF) link. This poses susceptibility to RF Interference (RFI) and may initiate failure states ranging from degraded navigation accuracy to a complete signal loss condition. To guarantee the integrity of the received GNSS signal, the receiver should either be able to function in the presence of RFI without generating misleading information (i.e., offering a navigation solution within an accuracy limit), or the receiver must detect RFI so that some other means could be used as a countermeasure in order to ensure robust and accurate navigation. Therefore, it is of utmost importance to identify an interference occurrence and not to confuse it with other signal conditions, for example, indoor or deep urban canyon, both of which have somewhat similar impact on the navigation performance. Hence, in this paper, the objective is to investigate the effect of interference on different GNSS receiver observables in two different environments: i. an interference scenario with an inexpensive car jammer, and ii. an outdoor-indoor scenario without any intentional interference. The investigated observables include the Automatic Gain Control (AGC) measurements, the digitized IF (Intermediate Frequency) signal levels, the Delay Locked Loop and the Phase Locked Loop discriminator variances, and the Carrier-to-noise density ratio (C/N0) measurements. The behavioral pattern of these receiver observables is perceived in these two different scenarios in order to comprehend which of those observables would be able to separate an interference situation from an indoor scenario, since in both the cases, the resulting positioning accuracy and/or availability are affected somewhat similarly. A new Running Digital Sum (RDS) -based interference detection method is also proposed herein that can be used as an alternate to AGC-based interference detection. It is shown in this paper that it is not at all wise to consider certain receiver observables for interference detection (i.e., C/N0); rather it is beneficial to utilize certain specific observables, such as the RDS of raw digitized signal levels or the AGC-based observables that can uniquely identify a critical malicious interference occurrence

Performance Evaluation of Mobile U-Navigation based on GPS/WLAN Hybridization

This paper present our mobile u-navigation system. This approach utilizes hybridization of wireless local area network and Global Positioning System internal sensor which to receive signal strength from access point and the same time retrieve Global Navigation System Satellite signal. This positioning information will be switched based on type of environment in order to ensure the ubiquity of positioning system. Finally we present our results to illustrate the performance of the localization system for an indoor/ outdoor environment set-up.Comment: Journal of Convergence Information Technology(JCIT

Study of the applicability of cognitive path algorithms for 3D indoor navigation

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Authoring and Living Next-Generation Location-Based Experiences

Authoring location-based experiences involving multiple participants, collaborating or competing in both indoor and outdoor mixed realities, is extremely complex and bound to serious technical challenges. In this work, we present the first results of the MAGELLAN European project and how these greatly simplify this creative process using novel authoring, augmented reality (AR) and indoor geolocalisation techniques