Dead on Arrival: An Empirical Study of The Bluetooth 5.1 Positioning System

The recently released Bluetooth 5.1 specification introduces fine-grained positioning capabilities in this wireless technology, which is deemed essential to context-/location-based Internet of Things (IoT) applications. In this paper, we evaluate experimentally, for the first time, the accuracy of a positioning system based on the Angle of Arrival (AoA) mechanism adopted by the Bluetooth standard. We first scrutinize the fidelity of angular detection and then assess the feasibility of using angle information from multiple fixed receivers to determine the position of a device. Our results reveal that angular detection is limited to a restricted range. On the other hand, even in a simple deployment with only two antennas per receiver, the AoA-based positioning technique can achieve sub-meter accuracy; yet attaining localization within a few centimeters remains a difficult endeavor. We then demonstrate that a malicious device may be able to easily alter the truthfulness of the measured AoA, by tampering with the packet structure. To counter this protocol weakness, we propose simple remedies that are missing in the standard, but which can be adopted with little effort by manufacturers, to secure the Bluetooth 5.1 positioning system.Comment: 8 pages, 11 figure

Acoustical Ranging Techniques in Embedded Wireless Sensor Networked Devices

Location sensing provides endless opportunities for a wide range of applications in GPS-obstructed environments; where, typically, there is a need for higher degree of accuracy. In this article, we focus on robust range estimation, an important prerequisite for fine-grained localization. Motivated by the promise of acoustic in delivering high ranging accuracy, we present the design, implementation and evaluation of acoustic (both ultrasound and audible) ranging systems.We distill the limitations of acoustic ranging; and present efficient signal designs and detection algorithms to overcome the challenges of coverage, range, accuracy/resolution, tolerance to Doppler’s effect, and audible intensity. We evaluate our proposed techniques experimentally on TWEET, a low-power platform purpose-built for acoustic ranging applications. Our experiments demonstrate an operational range of 20 m (outdoor) and an average accuracy 2 cm in the ultrasound domain. Finally, we present the design of an audible-range acoustic tracking service that encompasses the benefits of a near-inaudible acoustic broadband chirp and approximately two times increase in Doppler tolerance to achieve better performance

BLoB: Beating-based Localization for Single-antenna BLE Devices

Low-power wireless communication protocols based on synchronous transmissions have recently gained popularity. In such protocols, packets can be demodulated correctly even though several devices transmit at the same time, which results in high reliability and energy efficiency. A by-product of synchronous transmissions is the beating effect: a sinusoidal pattern of constructive and destructive interference across the received signal. In this paper, we leverage this beating to propose a new localization approach. Specifically, we present BLoB, a system in which multiple anchors transmit packets synchronously using the constant tone extension, an optional bit sequence introduced by BLE 5.1, whose signal is sent with constant amplitude and frequency. We let mobile tags sample the superimposed signal resulting from the synchronous transmissions, and extract peaks in the beating and signal spectrum. These peaks provide key insights about the anchors’ location that complement received signal strength information and allow BLoB to derive a tag’s position with sub-meter accuracy. A key property of BLoB is that both anchors and tags employ a single antenna, in contrast to state-of-the-art localization schemes based on angle of arrival/departure information that require costly and bulky antenna arrays to achieve sub-meter accuracy. We implement BLoB on off-the-shelf BLE devices and evaluate its performance experimentally in both static and mobile settings, and in different environments: office rooms, library, meeting room, and sports hall. Our results show that BLoB can distinguish several anchors in a single synchronous transmission and that it retains a sub-meter localization accuracy even in challenging indoor environments

Sensors and Systems for Indoor Positioning

This reprint is a reprint of the articles that appeared in Sensors' (MDPI) Special Issue on “Sensors and Systems for Indoor Positioning". The published original contributions focused on systems and technologies to enable indoor applications

Item Tracer

One of our daily issues for searching indoor lost item remain unresolved until today as there is no any systematic way of locating it. Unaccounted amount of time and energy has been wasted each day trying to retrieve it based on memory. Therefore, in this project, a prototype is proposed to locate indoor lost item utilizing received signal strength (RSS) for distance estimation. The prototype primary consists of a small size tag for attaching on any item and a reader for computing the estimated location of the tag. A positioning algorithm is developed to analyse the behaviour of received signal strength and calculate the probability of the target location. As the nature of indoor environment varies across each location, the prototype is tested at multiple indoor locations for refining the algorithm and verifying its robustness and consistency in estimating the target location. The results obtained showed that the percentage of error for direction probability is 32 % and accuracy of distance is at 0.9m

Towards joint communication and sensing (Chapter 4)

Localization of user equipment (UE) in mobile communication networks has been supported from the early stages of 3rd generation partnership project (3GPP). With 5th Generation (5G) and its target use cases, localization is increasingly gaining importance. Integrated sensing and localization in 6th Generation (6G) networks promise the introduction of more efficient networks and compelling applications to be developed

Wireless indoor localisation within the 5G internet of radio light

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonNumerous applications can be enhanced by accurate and efficient indoor localisation using wireless sensor networks, however trade-offs often exist between these two parameters. In this thesis, realworld and simulation data is used to examine the hybrid millimeter wave and Visible Light Communications (VLC) architecture of the 5G Internet of Radio Light (IoRL) Horizon 2020 project. Consequently, relevant localisation challenges within Visible Light Positioning (VLP) and asynchronous sampling networks are identified, and more accurate and efficient solutions are developed. Currently, VLP relies strongly on the assumed Lambertian properties of light sources. However, in practice, not all lights are Lambertian. To support the widespread deployment of VLC technology in numerous environments, measurements from non-Lambertian sources are analysed to provide new insights into the limitations of existing VLP techniques. Subsequently, a novel VLP calibration technique is proposed, and results indicate a 59% accuracy improvement against existing methods. This solution enables high accuracy centimetre level VLP to be achieved with non- Lambertian sources. Asynchronous sampling of range-based measurements is known to impact localisation performance negatively. Various Asynchronous Sampling Localisation Techniques (ASLT) exist to mitigate these effects. While effective at improving positioning performance, the exact suitability of such solutions is not evident due to their additional processes, subsequent complexity, and increased costs. As such, extensive simulations are conducted to study the effectiveness of ASLT under variable sampling latencies, sensor measurement noise, and target trajectories. Findings highlight the computational demand of existing ASLT and motivate the development of a novel solution. The proposed Kalman Extrapolated Least Squares (KELS) method achieves optimal localisation performance with a significant energy reduction of over 50% when compared to current leading ASLT. The work in this thesis demonstrates both the capability for high performance VLP from non- Lambertian sources as well as the potential for energy efficient localisation for sequentially sampled range measurements.Horizon 202

Edge Artificial Intelligence for Real-Time Target Monitoring

The key enabling technology for the exponentially growing cellular communications sector is location-based services. The need for location-aware services has increased along with the number of wireless and mobile devices. Estimation problems, and particularly parameter estimation, have drawn a lot of interest because of its relevance and engineers' ongoing need for higher performance. As applications expanded, a lot of interest was generated in the accurate assessment of temporal and spatial properties. In the thesis, two different approaches to subject monitoring are thoroughly addressed. For military applications, medical tracking, industrial workers, and providing location-based services to the mobile user community, which is always growing, this kind of activity is crucial. In-depth consideration is given to the viability of applying the Angle of Arrival (AoA) and Receiver Signal Strength Indication (RSSI) localization algorithms in real-world situations. We presented two prospective systems, discussed them, and presented specific assessments and tests. These systems were put to the test in diverse contexts (e.g., indoor, outdoor, in water...). The findings showed the localization capability, but because of the low-cost antenna we employed, this method is only practical up to a distance of roughly 150 meters. Consequently, depending on the use-case, this method may or may not be advantageous. An estimation algorithm that enhances the performance of the AoA technique was implemented on an edge device. Another approach was also considered. Radar sensors have shown to be durable in inclement weather and bad lighting conditions. Frequency Modulated Continuous Wave (FMCW) radars are the most frequently employed among the several sorts of radar technologies for these kinds of applications. Actually, this is because they are low-cost and can simultaneously provide range and Doppler data. In comparison to pulse and Ultra Wide Band (UWB) radar sensors, they also need a lower sample rate and a lower peak to average ratio. The system employs a cutting-edge surveillance method based on widely available FMCW radar technology. The data processing approach is built on an ad hoc-chain of different blocks that transforms data, extract features, and make a classification decision before cancelling clutters and leakage using a frame subtraction technique, applying DL algorithms to Range-Doppler (RD) maps, and adding a peak to cluster assignment step before tracking targets. In conclusion, the FMCW radar and DL technique for the RD maps performed well together for indoor use-cases. The aforementioned tests used an edge device and Infineon Technologies' Position2Go FMCW radar tool-set

Software-Defined Lighting.

For much of the past century, indoor lighting has been based on incandescent or gas-discharge technology. But, with LED lighting experiencing a 20x/decade increase in flux density, 10x/decade decrease in cost, and linear improvements in luminous efficiency, solid-state lighting is finally cost-competitive with the status quo. As a result, LED lighting is projected to reach over 70% market penetration by 2030. This dissertation claims that solid-state lighting’s real potential has been barely explored, that now is the time to explore it, and that new lighting platforms and applications can drive lighting far beyond its roots as an illumination technology. Scaling laws make solid-state lighting competitive with conventional lighting, but two key features make solid-state lighting an enabler for many new applications: the high switching speeds possible using LEDs and the color palettes realizable with Red-Green-Blue-White (RGBW) multi-chip assemblies. For this dissertation, we have explored the post-illumination potential of LED lighting in applications as diverse as visible light communications, indoor positioning, smart dust time synchronization, and embedded device configuration, with an eventual eye toward supporting all of them using a shared lighting infrastructure under a unified system architecture that provides software-control over lighting. To explore the space of software-defined lighting (SDL), we design a compact, flexible, and networked SDL platform to allow researchers to rapidly test new ideas. Using this platform, we demonstrate the viability of several applications, including multi-luminaire synchronized communication to a photodiode receiver, communication to mobile phone cameras, and indoor positioning using unmodified mobile phones. We show that all these applications and many other potential applications can be simultaneously supported by a single lighting infrastructure under software control.PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111482/1/samkuo_1.pd