Asynchronous Ultrasonic Trilateration for Indoor Positioning of Mobile Phones

Spatial awareness is fast becoming the key feature on today‟s mobile devices. While accurate outdoor navigation has been widely available for some time through Global Positioning Systems (GPS), accurate indoor positioning is still largely an unsolved problem. One major reason for this is that GPS and other Global Navigation Satellite Systems (GNSS) systems offer accuracy of a scale far different to that required for effective indoor navigation. Indoor positioning is also hindered by poor GPS signal quality, a major issue when developing dedicated indoor locationing systems. In addition, many indoor systems use specialized hardware to calculate accurate device position, as readily available wireless protocols have so far not delivered sufficient levels of accuracy. This research aims to investigate how the mobile phone‟s innate ability to produce sound (notably ultrasound) can be utilised to deliver more accurate indoor positioning than current methods. Experimental work covers limitations of mobile phone speakers in regard to generation of high frequencies, propagation patternsof ultrasound and their impact on maximum range, and asynchronous trilateration. This is followed by accuracy and reliability tests of an ultrasound positioning system prototype.This thesis proposes a new method of positioning a mobile phone indoors with accuracy substantially better than other contemporary positioning systems available on off-theshelf mobile devices. Given that smartphones can be programmed to correctly estimate direction, this research outlines a potentially significant advance towards a practical platform for indoor Location Based Services. Also a novel asynchronous trilateration algorithm is proposed that eliminates the need for synchronisation between the mobile device and the positioning infrastructure

Positioning Techniques with Smartphone Technology: Performances and Methodologies in Outdoor and Indoor Scenarios

Smartphone technology is widespread both in the academy and in the commercial world. Almost every people have today a smartphone in their pocket, that are not only used to call other people but also to share their location on social networks or to plan activities. Today with a smartphone we can compute our position using the sensors settled inside the device that may also include accelerometers, gyroscopes and magnetometers, teslameter, proximity sensors, barometer, and GPS/GNSS chipset. In this chapter we want to analyze the state-of-the-art of the positioning with smartphone technology, considering both outdoor and indoor scenarios. Particular attention will be paid to this last situation, where the accuracy can be improved fusing information coming from more than one sensor. In particular, we will investigate an innovative method of image recognition based (IRB) technology, particularly useful in GNSS denied environment, taking into account the two main problems that arise when the IRB positioning methods are considered: the first one is the optimization of the battery, that implies the minimization of the frame rate, and secondly the latencies due to image processing for visual search solutions, required by the size of the database with the 3D environment images

Evaluating Wi-Fi indoor positioning approaches in a real world environment

Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced AnalyticsGlobal positioning system(GPS) does not provide generally a good positioning performance in an indoor location because of many reasons (Henniges, 2012). On the other hand, other alternatives such as the WI-FI technology has become recently in a popular use to provide indoor localization. And that is due to many reasons, such as the wide spread of WI-FI infrastructure in the indoor environments and the low cost of this technology. This study attempts to evaluate different WI-FI indoor positioning approaches in a real world environment. In particular, in retail stores and shopping malls. The pros and cons of each one of these approaches are pointed out. The main purpose of this study from the company perspective is to explore the state of the art methods and the cutting edge technologies of the WI-FI IPS and to come up with an improvement of their indoor localization system. This system forms the core of the company`s retail-analytics product that uses a Wi-Fi positioning technology to provide indoor location based services for the customers and helps retailers to better understanding their businesses

Combining Mobile Technologies For Accurate, Open Source, Privacy Sensitive, Zero Cost, Location Determination

Determining the location of an object or individual using a mobile device (e.g. cell phone) is an important aspect of modern information gathering. Various solutions have been proposed which all have their strengths and weaknesses. To date, no solution has been devised for a mobile device that will work effectively in multiple environments and without assistance from network-provider connections1. To address this, it is argued that the current state of the art can be advanced using a hybrid approach that combines a number of sensor technologies to provide a more reliable, and accurate mobile location determination that functions in multiple environments (indoors and outdoors). This thesis examines in detail current relevant available technology, calculation techniques for location determination, the Global Navigation Satellite System (GNSS) and other noteworthy location determination research. It then introduces our solution of a hybrid positioning system that is an open-source, provider-network independent, privacy sensitive, zero-cost and accurate software component. First the overall system design is described and then individual modules are described in detail. It describes in full an algorithm that intelligently combines signals from various technologies, applies weights to these signals and also leverages past signal readings to enhance current calculations. Next, the evaluation section is introduced which discusses how and why the test bed was chosen and deployed. It then discusses individual test results and finally the overall tests are analysed, discussed and summarised. Finally, the conclusions are prepared in detail, the three initial questions raised in the introduction are answered and discussed and the contributions to the body of knowledge are reaffirmed. Future work finishes the thesis and looks at several research paths that can be pursued from this research

The spy in your pocket: Smartphones and geo-location data

The integration of Global Positioning Systems and Smartphones has seen the significance of location based services rise. Geo-location data could prove to be an invaluable source of evidence in a forensic investigation. An attempt to extract geo-location data from an iPhone4s and Huawei Ascend G526 in a forensically sound manner revealed significant geo-location data embedded within geo-tags within photos taken on the devices. Other limited evidence was located on the devices

ASSESSMENT OF ELECTRO-OPTICAL IMAGING TECHNOLOGY FOR UNMANNED AERIAL SYSTEM NAVIGATION IN A GPS-DENIED ENVIRONMENT

Navigation systems of unmanned aircraft systems (UAS) are heavily dependent on the availability of Global Positioning Systems (GPS) or other Global Navigation Satellite Systems (GNSS). Although inertial navigation systems (INS) can provide position and velocity of an aircraft based on acceleration measurements, the information degrades over time and reduces the capability of the system. In a GPS-denied environment, a UAS must utilize alternative sensor sources for navigating. This thesis presents preliminary evaluation results on the usage of onboard down-looking electro-optical sensors and image matching techniques to assist in GPS-free navigation of aerial platforms. Following the presentation of the fundamental mathematics behind the proposed concept, the thesis analyzes the key results from three flight campaign experiments that use different sets of sensors to collect data. Each of the flight experiments explores different sensor setups, assesses a variety of image processing methods, looks at different terrain environments, and reveals limitations related to the proposed approach. In addition, an attempt to incorporate navigational aid solutions into a navigation system using a Kalman filter is demonstrated. The thesis concludes with recommendations for future research on developing an integrated navigation system that relies on inertial measurement unit data complemented by the positional fixes from the image-matching technique.Outstanding ThesisCivilian, DSO National Laboratories, SingaporeApproved for public release. Distribution is unlimited

Making the Case for New Research to Support the Integration of Small Unmanned Aircraft Systems into the National Airspace System

This paper describes the current state of sUAS regulation, their technical capabilities and the latest technologies that will allow for sUAS NAS integration. The research that is needed to demonstrate sUAS NAS integration capability is identified, and recommendations for conducting this necessary research are suggested

Ibeacon based proximity and indoor localization system

User location can be leveraged to provide a wide range of services in a variety of indoor locations including retails stores, hospitals, airports, museums and libraries etc. The widescale proliferation of user devices such as smart phones and the interconnectivity among different entities, powered by Internet of Things (IoT), makes user device-based localization a viable approach to provide Location Based Services (LBS). Location based services can be broadly classified into 1) Proximity based services that provides services based on a rough estimate of users distance to any entity, and 2) Indoor localization that locates a user\u27s exact location in the indoor environment rather than a rough estimate of the distance. The primary requirements of these services are higher energy efficiency, localization accuracy, wide reception range, low cost and availability. Technologies such as WiFi, Radio Frequency Identification (RFID) and Ultra Wideband (UWB) have been used to provide both indoor localization and proximity based services. Since these technologies are not primarily intended for LBS, they do not fulfill the aforementioned requirements. Bluetooth Low Energy (BLE) enabled beacons that use Apple\u27s proprietary iBeacon protocol are mainly intended to provide proximity based services. iBeacons satisfy the energy efficiency, wide reception range and availability requirements of LBS. However, iBeacons are prone to noise due to their reliance on Received Signal Strength Indicator (RSSI), which drastically fluctuates in indoor environments due to interference from different obstructions. This limits its proximity detection accuracy. In this thesis, we present an iBeacon based proximity and indoor localization system. We present our two server-based algorithms to improve the proximity detection accuracy by reducing the variation in the RSSI and using the RSSI-estimated distance, rather than the RSSI itself, for proximity classification. Our algorithms Server-side Running Average and Server-side Kalman Filter improves the proximity detection accuracy by 29% and 32% respectively in contrast to Apple\u27s current approach of using moving average of RSSI values for proximity classification. We utilize a server-based approach because of the greater computing power of servers. Furthermore, server-based approach helps reduce the energy consumption of user device. We describe our cloud based architecture for iBeacon based proximity detection. We also use iBeacons for indoor localization. iBeacons are not primarily intended for indoor localization as their reliance on RSSI makes them unsuitable for accurate indoor localization. To improve the localization accuracy, we use Bayesian filtering algorithms such as Particle Filter (PF), Kalman Filter (KF), and Extended Kalman Filter (EKF). We show that by cascading Kalman Filter and Extended Kalman Filter with Particle Filter, the indoor localization accuracy can be improved by 28% and 33.94% respectively when compared with only using PF. The PF, KFPF and PFEKF algorithm on the server side have average localization error of 1.441 meters, 1.0351 meters and 0.9519 meters respectively

Multimodal Content Delivery for Geo-services

This thesis describes a body of work carried out over several research projects in the area of multimodal interaction for location-based services. Research in this area has progressed from using simulated mobile environments to demonstrate the visual modality, to the ubiquitous delivery of rich media using multimodal interfaces (geo- services). To effectively deliver these services, research focused on innovative solutions to real-world problems in a number of disciplines including geo-location, mobile spatial interaction, location-based services, rich media interfaces and auditory user interfaces. My original contributions to knowledge are made in the areas of multimodal interaction underpinned by advances in geo-location technology and supported by the proliferation of mobile device technology into modern life. Accurate positioning is a known problem for location-based services, contributions in the area of mobile positioning demonstrate a hybrid positioning technology for mobile devices that uses terrestrial beacons to trilaterate position. Information overload is an active concern for location-based applications that struggle to manage large amounts of data, contributions in the area of egocentric visibility that filter data based on field-of-view demonstrate novel forms of multimodal input. One of the more pertinent characteristics of these applications is the delivery or output modality employed (auditory, visual or tactile). Further contributions in the area of multimodal content delivery are made, where multiple modalities are used to deliver information using graphical user interfaces, tactile interfaces and more notably auditory user interfaces. It is demonstrated how a combination of these interfaces can be used to synergistically deliver context sensitive rich media to users - in a responsive way - based on usage scenarios that consider the affordance of the device, the geographical position and bearing of the device and also the location of the device