Developing an Indoor Navigation Application: Identifying the Needs and Preferences of Users Who Are Visually Impaired

Object positioning is a trending topic currently. The global positioning system (GPS) is the most common positioning method. Cars rely on GPS to navigate and plan routes to destinations. Unmanned aerial vehicles employ the GPS to assist flight and achieve cruise functions of automatic altitude and fixed point flights. However, the GPS fails when positioning is conducted indoors because GPS signals cannot be received indoors. Therefore, an indoor positioning system (IPS) should be used for indoor positioning. This paper mainly discusses the localization error of an ultra-wideband (UWB) indoor positioning system. A two-triangle positioning method was used to locate a target point separately through each triangle. Finally, values obtained using the two triangles were calculated using an algorithm to obtain a more accurate position.

People generally find themselves lost while visiting a new indoor location because they are unaware of the building’s architecture, especially when it is a large one or a shopping mall. The Global Position System (GPS) does not work properly in the indoor environment because of the satellite signal attenuation. In this paper, to assist people in finding their path, a Li-Fi (Light-Fidelity) based Indoor Positioning System (IPS) is proposed. A framework is developed based on a Li-Fi LED lamp transmitter and a dongle receiver connected to an Android smartphone to decode the received sequence. The pathfinding graph-based algorithm is proceeded in a REST architecture by a Web service consulting the graph-path database both installed on a Raspberry pi 4. The proposed solution is a low cost and does not require any additional infrastructure. It is easy to implement in most indoor environments like hospitals, buildings, and campuses. A short survey of techniques and algorithms for indoor positioning and navigation with the help of smartphones is also presented.

Purpose – A simplified global positioning system (GPS) error model including models for a variety of abnormal operational conditions and failures is developed to provide simulation tools for the design, testing, and evaluation of autonomous flight fault tolerant control laws. The paper aims to discuss these issues. Design/methodology/approach – Analysis and experimental data are used to build simplified models for GPS position and velocity errors on all three channels. The GPS model is interfaced with West Virginia University unmanned aerial vehicles (UAV) simulation environment and its utility demonstrated through simulation for several autonomous flight scenarios including GPS abnormal operation. Findings – The proposed simplified GPS model achieves desirable levels of accuracy and realism for all components for the purpose of general UAV dynamic simulation and development of fault tolerant autonomous flight control laws. Research limitations/implications – The simplified GPS model allows investigating GPS malfunction effects on the performance of autonomous UAVs and designing trajectory tracking algorithms with advanced fault tolerant capabilities. Practical implications – The simplified GPS model has proved to be a flexible and useful tool for UAV simulation and design of autonomous flight control laws at normal and abnormal conditions. Originality/value – The outcomes of this research effort achieve a level of detail never attempted before in modeling GPS operation at normal and abnormal conditions for UAV simulation and autonomous flight control laws design using a simplified framework.

Global positioning system (GPS) tracks a desired location and display it on map. However, GPS may not work properly for indoor positioning, when we are concerned with an accurate location of a person inside a building. Therefore, to determine an accurate indoor positioning based on smart devices a scheme is proposed and called iLocation. iLocation measures the location by obtaining and computing values from an accelerometer and a barometer of a smart device. iLocation uses MySQL to maintain records of the computed indoor positions. Such positions are displayed on Google Maps with its images for the verification. iLocation is tested on various real time scenarios and experimental results shows the accuracy, which is better than other existing approaches.

Global positioning system (GPS) based indoor positioning techniques generally utilize repeaters to amplify and retransmit the original GPS signals to indoor receivers. In this paper, a GPS repeater based indoor positioning approach is proposed. Unlike most repeater-based indoor positioning techniques in current literature, repeaters are not required to connect to an outdoor antenna with fixed length cables. Neither do repeaters need to be synchronized. Each repeater retransmits the GPS signals continuously to the indoor receivers without sequential switching. Assume more than one satellite is visible to four or more repeaters. At a measuring time instance, the range from a repeater to the user receiver is identical for any travelling satellite signal, which is repeated by this repeater. Incorporating this feature and comparing the ranges measured by means of repeated signals of different satellites, the receiver is able to identify the repeater, which repeats a given satellite signal. With the known coordinates of the identified repeaters and the ranges from repeaters to the receiver, then the receiver position can be found. To compromise the impact of the repeater signal processing time difference on positioning accuracy, this work proposes two methods to calculate the receiver position and fuses the results by Kalman filter. Furthermore, considering the general indoor positioning environments, altitudes of floors of a building are utilized to assist in improving the positioning performance. Simulation results with true repeater coordinate data are provided to verify the proposed approach.

Localization is a fundamental operation in wireless networks. Location determination is normally accomplished using the Global Positioning System (GPS) for outdoor applications. For indoor localization, GPS does not work due to the lack of the line of sight to satellites. High-precision indoor localization is critical to many personal and business applications. WiFi-based indoor localization was proposed to be a practical method to locate WiFi-enabled devices due to the popularity of WiFi networks. However, it suffers from large localization errors. Our experimental results indicate that this scheme consistently leads to an average error around 3 meters. The existence of different locations with similar WiFi signal strength is the reason behind the large errors. To improve the localization precision, a hybrid indoor localization scheme, HILL, is proposed in this paper. Inspired by the fact that a large number of WiFi-enabled mobile devices have been deployed, HILL uses 3 phases to improve the precision of WiFi-based localization. First of all, it measures the distances between each pair of peer devices through acoustic ranging. Secondly, the Classical Metric Multidimensional Scaling (MDS) method is applied to the collected distances, which results in a graph consistent with the distances. Finally, the graph generated by MDS is embedded onto the graph corresponding to WiFi-based localization in order to achieve high localization precision. Our experimental results indicate that the average localization error of HILL is about 1 meter.

This paper proposes a method for fused navigation of an unmanned marine surface vehicle (UMSV). The method also detects the outlier and interference of global positioning system (GPS) simultaneously. The method fuses available sensor measurements through extended Kalman filter (EKF) to find the location and attitude of the vehicle. The method uses error covariance of estimated location for detection of GPS outlier and interference. When outlier and interference of the GPS is detected, the method excludes GPS data from navigation process. The measurements to be fused for the navigation are position by GPS, acceleration, angular rate, magnetic field, linear velocity, and range and bearing to acoustic beacons. The method is tested through simulated data and measurement data produced through navigation of a vehicle. The results show that the method detects GPS outlier and interference as well as the GPS recovery, which frees the UMSV navigation from the problem of GPS abnormality. The method is applicable to the vehicle navigation where the UMSV is out of reach from the GPS jamming detection network such as GAARDIAN (GNSS Availability Accuracy Reliability and Integrity Assessment for Timing and Navigation) or jammer detection and location (JLOC) system.

본 논문에서는 ZigBee와 GPS를 이용한 실내 위치 인식 시스템을 설계하였다. 본 연구에서 설계한 위치 인식 시스템은 실외 위치 인식에 대표적으로 사용되는 GPS 값을 실내 위치인식에 사용함으로서 기존 실내와 실외로 구분되던 위치 인식 기술을 하나로 통합하였다. 개발된 시스템은 노드간의 거리를 이용하여 위치를 구하는 방식으로 노드 간의 거리는 ZigBee의 수신 신호 세기를 이용하여 거리를 계산하는 방식을 사용하였다. 그러나 ZigBee의 수신 세기의 경우 거리에 따라 달라지나 그 값이 정확하지 않아 오차가 크다. 이 오차를 줄이기 위하여 개발 시스템에서는 ZigBee의 출력 파워를 5단계로 조절하여 거리에 따른 수신 신호 세기를 세분화하였다. 이동 노드가 신호를 발생하면 고정 노드에서는 수신된 신호의 세기와 자신의 GPS 정보를 고정 노드로 전송을 한다. 이동 노드에서는 수신된 정보를 이용하여 자신의 위치를 구하는 방식을 제안하였다. This paper proposes a new indoor location recognition system using a ZigBee network and a global positioning system(GPS). The proposed location recognition system applies GPS values that are mainly used for outdoor location recognition, to indoor location recognition; hence the techniques conventionally separated for the indoor and outdoor location recognition are integrated into one location recognition technique. The proposed system recognizes a location using the distance between nodes. Although the distance between nodes can be calculated by measuring the strength of the received ZigBee signals, generally the measured distance is not accurate and has high error rates since the strength of the ZigBee signals is different depending on the distance. In order to reduce the error rate, we have subdivided the output power of the received ZigBee signals into five levels. When a moving node generates a signal, each fixed node transmits the received signal strength and its own GPS information to other nodes, so the moving node can find its own accurate location in terms of the received signals.

The integration of location information with day-to-day applications will grow significantly over the next decade as the technology’s accuracy evolves. Currently outdoor localization, thanks to the Global Positioning System (GPS), has revolutionized navigation-based applications running on automotive GPS-enabled devices and smart phones. Applications range from guiding drivers to their destinations to providing point-by-point directions to the closest cinema or coffee shop. The success of GPS has been due to the reliability, availability, and practical accuracy that the orbiting satellites covering the globe provide. However, GPS provides limited coverage indoors and poor quality information in urban areas and near buildings which has motivated research in indoor geolocation in the last decade. A major challenge facing the indoor localization industry is the indoor propagation problem. The indoor environment is not friendly to wireless signals and that is manifested through limited coverage, multipath propagation, and the non-line-of-sight (NLOS) problem. Many research areas developed in the last decade to address those challenges. A fundamental aspect to addressing the challenges is understanding the indoor propagation mechanisms affecting the accuracy of localization; and efforts to measure, characterize and model the wireless channel from a geolocation perspective have received significant attention. Further algorithms and techniques to mitigate the multipath and NLOS problems have emerged recently for many systems (e.g. WLAN, WSN, UWB, etc.). Another area of research that has evolved around the indoor problem is the inertial measurement unit (IMU) based approaches in navigation and tracking (e.g. Kalman filters, particle filters, etc.) which adds another dimension to indoor location estimation. Finally hybrid technologies and signals of opportunity approaches have gained popularity recently to harness the most available information in order to improve robustness and accuracy of indoor localization systems. Although many approaches have been investigated and proposed, accurate indoor location remains a challenging problem. This special issue aims at attracting research papers focusing on mitigating the indoor geolocation challenges. The annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) is one of the premier conferences in the wireless research arena and has a long history of bringing together academia, industry and regulatory bodies. Today, it has become one of the IEEE Communication Society’s flagship conferences in telecommunications. The 23rd IEEE PIMRC was held successfully in Sydney Australia, from 9 to 12 September 2012, where several hundred researchers met to share their latest research results in wireless technologies. In this special issue, we have compiled the extended versions of the best papers on indoor geolocation techniques from this conference as well as a few invited papers from wellknown experts in this field. The invited authors have done an excellent job in substantially extending the conference version of the papers, which significantly improved the X. Li (&) Department of Electrical Engineering, University of North Texas, Denton, TX, USA e-mail: xinrong.li@unt.edu

Augmented Reality (AR) technology has become increasingly popular due to its potential use in an indoor environment. AR technology enables virtual information, such as navigation instructions, to be merged into the actual environment via a mobile screen. Using an AR-based Indoor Navigation speeds uptime while also being interactive in searching for a particular building location. Every year when new semester students enrol in the university, some students will have difficulty finding a particular location on the campus. The most searched for building upon arrival at the university is the student halls of residence. While searching for it, students waste time asking others for information or looking for a nearby campus map. Therefore, this project investigates the requirements needed for an AR-based indoor navigation application to be applied within the student halls of residence and identifies technical issues through a small-scale prototype development within a small navigational area. Seventy-one students participated in the feasibility study by responding to a set of questionnaires related to the Student Residence AR indoor navigation application. At the same time, four users with and without previous experience with AR applications evaluated the prototype application. The results identified that the more the students have difficulty searching, the more they require additional time to reach their destination and seek help from others, an excellent reason to implement the Student Residence AR indoor navigation. In addition, the prototype evaluation results discussed issues related to arrow path confusion, distance accuracy, assistive guideline, and software development challenges in AR development that could be beneficial to future developers and researchers.

In large-scale commercial facilities, location information has much importance for visitor, administrator, and staff of facilities in order to provide various services such as navigation, information inquiry and response, recommendation, marketing analysis, and so on. In particular, indoor positioning and navigation are expected to be useful for visitors of the facilities, and the information of positioning result can be utilized for the analysis of marketing and demand control for the supply side of the commercial facilities. However, it is not easy to achieve indoor positioning and navigation, because there are some crucial problems, for example, it is difficult to apply Global Positioning System (GPS) technologies in indoor environments. In this chapter, we introduce an indoor autonomous positioning and navigation system without using the GPS technology. Some attractive features of the proposed system are that it can work on a smartphone as an application alone without server communications and can provide continuous positioning results. In addition to it, the system is robust against disturbances in real target environments. We have carried out some experiments of the system in a real large-scale commercial facility called Yokohama Landmark Plaza. A result of experiments shows that the positioning result can be obtained with high accuracy and that system can produce continuous positioning results in a robust way against noise and changes of radio wave strength in real environments. These properties will work effectively for providing the services mentioned above.

The Global Positioning System (GPS) uses signals from satellites to specialised devices to detect an entity’s location on Earth’s surface. However, GPS is ineffective for indoor navigation due to high power consumption and signal obstruction by walls. This study proposes a low-cost, energy-efficient alternative using Bluetooth 4.0-enabled Bluetooth Low Energy (BLE) beacons to enable Indoor Positioning and guide users in confined spaces, such as libraries. Tiny, low-energy BLE beacons transmit Advertising Packets at regular intervals. In contrast, Anchor Nodes send and receive signals to construct a Received Signal Strength Indication (RSSI)-based signal-to-distance model, enabling triangulation-based localisation. The system monitors behaviour and environmental interaction through RSSI analysis and user interaction with Beacons. Proven in a library setting, the BLE-based system proved extremely accurate in guiding users to destinations, bridging GPS shortcomings at minimal energy expenditure and cost.

The need for indoor localization systems that can provide reliable access to location information in areas that are not serviced sufficiently by a global positioning system (GPS) has continued to grow. There are a wide variety of use cases for this localization data and increasing interest from industry, academia, and government agencies that has fueled research in this area. Smartphones are uniquely positioned to be a critical part of a localization solution based on the proliferation of these devices and the diverse array of sensors and radios that they contain. In this article, the capabilities of these sensors are explored along with the benefits and drawbacks of each for localization. Various methods for employing these sensors are surveyed. Many localization systems currently being explored utilize a combination of complimentary methods to enhance accuracy and reliability and decrease energy consumption of the overall system. Several of these localization frameworks are also explored. Finally, we describe the major challenges that are being faced in current research on indoor localization with smartphones, as they are critical for charting the path for future advances in indoor localization.

UWB (Ultra Wideband) TOF (Time of Flight) location system is a high accuracy real time indoor location system. It includes many anchors and positioning tags. GDOP (geometric dilution of precision) is an index that used to measures the accuracy of GPS (Global positioning system). In this paper we will study GDOP from the GPS and use GDOP into indoor location system. Researching whether GDOP is a big impact to the accuracy of UWB indoor location system. At the end of the paper, there are two-dimensional positioning GDOP simulation based on MATLAB and several groups of experimental data which calculated by hyperbolic positioning algorithm.

People have to move between indoor and outdoor frequently in city scenarios. The global navigation satellite system signal cannot provide reliable indoor positioning services. To solve the problem, this article proposes a seamless positioning system based on an inverse global navigation satellite system signal, which can extend the global navigation satellite system service into the indoor scenario. In this method, a signal source is arranged at a key position in the room, and the inverse global navigation satellite system signal is transmitted to the global navigation satellite system receiver to obtain a preset positioning result. The indoor positioning service is continued with the inertial navigation system after leaving the key position. The inverse global navigation satellite system seamless positioning system proposed in this article can unify indoor and outdoor positioning using the same receiver. The receiver does not need to re-receive navigation information when the scene changes, which avoids the switching process. Through the design of signal layer coverage, the receiver is in a warm start state, and the users can quickly fix the position when the scenario changes, realizing quick access in a true sense. This enables the ordinary commercial global navigation satellite system receiver to obtain indoor positioning capability without modification, and the algorithm can perform accurate positioning indoors and outdoors without switching.