Challenges in platform-independent UWB ranging and localization systems

The Ultra-Wideband (UWB) technology has grown in popularity to the point in which there are numerous UWB transceivers on the market that use different center frequencies, bandwidths, or hardware architectures. At the same time, efforts are made to reduce the ranging and localization errors of UWB systems. Until now, not much attention has been dedicated to the cross-platform compatibility of these methods. In this paper, we discuss for the first time the challenges in obtaining platform-independent UWB ranging and localization systems. We derive our observations from a measurement campaign conducted with UWB devices from three different developers. We evaluate the differences in the ranging errors and channel impulse responses of the devices and show how they can affect ranging mitigation methods customized for one device only. Finally, we discuss possible solutions towards platform-independent UWB localization systems.publishedVersionPeer reviewe

Self-Learning Detection and Mitigation of Non-Line-of-Sight Measurements in Ultra-Wideband Localization

Non-line-of-sight (NLOS) propagation is one of the main error sources in indoor localization, so a large body of work has been dedicated to identifying and mitigating NLOS errors. The most accurate NLOS detection methods often rely on large training data sets that are time-consuming to obtain and depend on the environment and hardware. We propose a method for detecting NLOS distance measurements without manually collected training data and knowledge of channel statistics. Instead, the algorithm generates LOS/NLOS labels for sets of distance measurements between fixed sensors and the mobile target based on distance residuals. The residual-based detection has 70-80% accuracy but has high complexity and cannot be used with high confidence on all measurements. Therefore, we use the predicted labels and the channel impulse responses of the measurements to train a classifier that achieves over 90% accuracy and can be used on all measurements, with low complexity. After we train the classifier during an initial phase that captures specifics of the devices and of the environment, we can skip the residual-based detection and use only the trained model to classify all measurements. We also propose an NLOS mitigation method that reduces, on average, the mean and standard deviation of the localization error by 2.2 and 5.8 times, respectively.Peer reviewe

On the energy consumption and ranging accuracy of ultra-wideband physical interfaces

Ultra-wideband (UWB) communication is attracting increased interest for its high-accuracy distance measurements. However, the typical current consumption of tens to hundreds of mA during transmission and reception might make the technology prohibitive to battery-powered devices in the Internet of Things. The IEEE 802.15.4 standard specifies two UWB physical layer interfaces (PHYs), with low- and high-rate pulse repetition (LRP and HRP, respectively). While the LRP PHY allows a more energy-efficient implementation of the UWB transceiver than its HRP counterpart, the question is whether some ranging quality is lost in exchange. We evaluate the trade-off between power and energy consumption, on the one hand, and distance measurement accuracy and precision, on the other hand, using UWB devices developed by Decawave (HRP) and 3db Access (LRP). We find that the distance measurement errors of 3db Access devices have at most 12 cm higher bias and standard deviation in line-of-sight propagation and 2-3 times higher spread in non-line-of-sight scenarios than those of Decawave devices. However, 3db Access chips consume 10 times less power and 125 times less energy per distance measurement than Decawave ones. Since the LRP PHY has an ultra-low energy consumption, it should be preferred over the HRP PHY when energy efficiency is critical, with a small penalty in the ranging performance.acceptedVersionPeer reviewe

On the High Fluctuations of Received Signal Strength Measurements with BLE Signals for Contact Tracing and Proximity Detection

This paper presents a measurement-based analysis of the Received Signal Strength (RSS) of Bluetooth Low Energy (BLE) signals, under Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) scenarios, performed in tandem at two universities in Tampere, Finland, and Bucharest, Romania. We adopted the same hardware and methodology for measurements in both places, and paid particular attention to the impact of RSS on various environmental factors, such as LOS and NLOS scenarios and interference in 2.4 GHz band. In addition, we considered the receiver orientation and the different frequencies of BLE advertising channels. We show that snapshot RSS measurements typically have high variability, not easily explainable by classical path-loss models. A snapshot recording is defined here as one continuous recording at fixed device locations in a static setup. Our observations also show that aggregated RSS data (i.e., considering several snapshot measurements together) is more informative from a statistical point of view and more in agreement with current theoretical path-loss models than snapshot measurements. However, in BLE applications such as contact tracing and proximity detection, the receivers typically have access only to snapshot measurements (e.g., taken over a short duration of 10–20 minutes or less), so the accuracy of contact-tracing and proximity detection can be highly affected by RSS instabilities. In addition to presenting the measurement-based BLE RSS analysis in a comprehensive and well-documented format, our paper also emphasizes open challenges when BLE RSS is used for contact tracing, ranging, and positioning applications.publishedVersionPeer reviewe

FlexTDOA : Robust and Scalable Time-Difference of Arrival Localization Using Ultra-Wideband Devices

In this paper, we propose FlexTDOA, an indoor localization method using ultra-wideband (UWB) radios, and we demonstrate its performance in a functional system. Our method uses time-difference of arrival (TDOA) localization so that the user device remains passive and is able to compute its location simply by listening to the communication between the fixed anchors, ensuring the scalability of the system. The anchors communicate using a custom and flexible time-division multiple-access (TDMA) scheme in which time is divided in slots. In each time slot, one anchor interrogates one or more anchors which respond in the same slot. The anchors do not need to have their clocks synchronized. We implemented FlexTDOA on in-house designed hardware using a commercial UWB module. We evaluate the localization accuracy of FlexTDOA with different system parameters such as the number of responses, the order of responses, and the number of anchors. We simulate and evaluate the effect of the physical speed of the tag on the choice of optimum system parameters. We also compare FlexTDOA against the classic TDOA approach and range-based localization in a deployment of ten anchors and one tag, both with and without obstructions. Results show that FlexTDOA achieves the highest localization accuracy in most of the scenarios, with up to 38% reduction in the localization error compared to the classic approach.Peer reviewe

High-Accuracy Ranging and Localization with Ultra-Wideband Communications for Energy-Constrained Devices

Ultra-wideband (UWB) communications have gained popularity in recent years for being able to provide distance measurements and localization with high accuracy, which can enhance the capabilities of devices in the Internet of Things (IoT). Since energy efficiency is of utmost concern in such applications, in this work we evaluate the power and energy consumption, distance measurements, and localization performance of two types of UWB physical interfaces (PHYs), which use either a low-or high-rate pulse repetition (LRP and HRP, respectively). The evaluation is done through measurements acquired in identical conditions, which is crucial in order to have a fair comparison between the devices. We performed measurements in typical line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios. Our results suggest that the LRP interface allows a lower power and energy consumption than the HRP one. Both types of devices achieved ranging and localization errors within the same order of magnitude and their performance depended on the type of NLOS obstruction. We propose theoretical models for the distance errors obtained with LRP devices in these situations, which can be used to simulate realistic building deployments and we illustrate such an example. This paper, therefore, provides a comprehensive overview of the energy demands, ranging characteristics, and localization performance of state-of-the-art UWB devices.acceptedVersionPeer reviewe

High-Accuracy Ranging and Localization with Ultra-Wideband Communications for Energy-Constrained Devices

Ultra-wideband (UWB) communications have gained popularity in recent years for being able to provide distance measurements and localization with high accuracy, which can enhance the capabilities of devices in the Internet of Things (IoT). Since energy efficiency is of utmost concern in such applications, in this work we evaluate the power and energy consumption, distance measurements, and localization performance of two types of UWB physical interfaces (PHYs), which use either a low-or high-rate pulse repetition (LRP and HRP, respectively). The evaluation is done through measurements acquired in identical conditions, which is crucial in order to have a fair comparison between the devices. We performed measurements in typical line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios. Our results suggest that the LRP interface allows a lower power and energy consumption than the HRP one. Both types of devices achieved ranging and localization errors within the same order of magnitude and their performance depended on the type of NLOS obstruction. We propose theoretical models for the distance errors obtained with LRP devices in these situations, which can be used to simulate realistic building deployments and we illustrate such an example. This paper, therefore, provides a comprehensive overview of the energy demands, ranging characteristics, and localization performance of state-of-the-art UWB devices.acceptedVersionPeer reviewe

Persona: A High-Performance Bioinformatics Framework

Next-generation genome sequencing technology has reached a point at which it is becoming cost-effective to sequence all patients. Biobanks and researchers are faced with an oncoming deluge of genomic data, whose processing requires new and scalable bioinformatics architectures and systems. Processing raw genetic sequence data is computationally expensive and datasets are large. Current software systems can require many hours to process a single genome and generally run only on a single computer. Common file formats are monolithic and row-oriented, a barrier to distributed computation. To address these challenges, we built Persona, a cluster-scale, high-throughput bioinformatics framework. Persona currently supports paired-read alignment, sorting, and duplicate marking using well-known algorithms and techniques. Persona can significantly reduce end-to-end processing times for bioinformatics computations. A new Aggregate Genomic Data (AGD) format unifies sample data and analysis results, while enabling efficient distributed computation and I/O. In a case study on sequence alignment, Persona sustains 1.353 gigabases aligned per second with 101 base pair reads on a 32-node cluster and can align a full genome in ~16.7 seconds using the SNAP algorithm. Our results demonstrate that: (1) alignment computation with Persona scales linearly across servers with no measurable completion-time imbalance and negligible framework overheads; (2) on a single server, sorting with Persona and AGD is up to 2.3× faster than commonly used tools, while duplicate marking is 3× faster; (3) with AGD, a 7 node COTS network storage system can service up to 60 alignment compute nodes; (4) server cost dominates for a balanced system running Persona, while long-term data storage dwarfs the cost of computation

HTC Vive as a Ground-Truth System for Anchor-Based Indoor Localization

The last decade has seen a surge in the popularity of indoor localization systems. Researchers and companies keep searching for technologies that can locate users on a large scale with low costs and the highest possible accuracy. When evaluating the accuracy of a localization system, there is a trade-off between the cost and labor involved in acquiring ground-truth measurements. The cheapest option is to acquire measurements in fixed spots and manually compute their true location in a local coordinate system using distance measuring tools. However, this method is prone to human errors and has a high setup overhead. In contrast, high-end motion capture systems are easy to set up but have prohibitive prices. A middle-of-the-road solution is to use a consumer-grade motion capture system such as the HTC Vive which, although designed for virtual reality video games, can be adapted for scientific applications. We propose a ground-truth system for anchor-based indoor localization systems which builds on the HTC Vive and we demonstrate its use on ultra-wideband (UWB) localization. We apply Procrustes Analysis to bring location data sets into the coordinate system of a room, in order to easily overlap, visualize, and analyze measurements. We use the HTC Vive to acquire the locations of UWB anchors, which allows users to quickly test which hardware placement yields the lowest localization error. The resulting ground-truth system costs under 1000, has an average accuracy of more than 5 mm, is easy to set up, and can be used for both static and dynamic measurements.acceptedVersionPeer reviewe

A Survey on Wearable Technology: History, State-of-the-Art and Current Challenges

Technology is continually undergoing a constituent development caused by the appearance of billions new interconnected “things” and their entrenchment in our daily lives. One of the underlying versatile technologies, namely wearables, is able to capture rich contextual information produced by such devices and use it to deliver a legitimately personalized experience. The main aim of this paper is to shed light on the history of wearable devices and provide a state-of-the-art review on the wearable market. Moreover, the paper provides an extensive and diverse classification of wearables, based on various factors, a discussion on wireless communication technologies, architectures, data processing aspects, and market status, as well as a variety of other actual information on wearable technology. Finally, the survey highlights the critical challenges and existing/future solutions.publishedVersionPeer reviewe