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

Acceptable Margin of Error : Quantifying Location Privacy in BLE Localization

Location privacy poses a critical challenge as the use of mobile devices and location-based services becomes more and more widespread. Proximity-detection data can reveal sensitive information about individuals, making it essential to preserve their location data. One way to achieve privacy protection is by adding noise to ground-truth data, which can introduce uncertainty while still allowing moderate utility for proximity-detection services and Received Signal Strength (RSS)-based localization. However, it is important to carefully adjust the amount of noise added in order to balance the privacy and accuracy concerns. This paper expands our previous work on evaluating location privacy bounds based on measurement error and intentionally added noise. Our model builds upon existing work in differential privacy and introduces other techniques to estimate privacy bounds specific to proximity data. By using real-world measurement data, we measure the privacy-accuracy trade-off and suggest cases where additional noise could be added. Our framework can be utilized to inform privacy-preserving location-based applications and guide the selection of appropriate noise levels in order to achieve the desired privacy-accuracy balance.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

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

Coastal Sea Level Monitoring in the Mediterranean and Black Seas

Spanning over a century, a traditional way to monitor sea level variability by tide gauges is – in combination with modern observational techniques like satellite altimetry – an inevitable ingredient in sea level studies over the climate scales and in coastal seas. The development of the instrumentation, remote data acquisition, processing and archiving in last decades allowed for extending the applications towards a variety of users and coastal hazard managers. The Mediterranean and Black50 seas are an example for such a transition – while having a long tradition for sea level observations with several records spanning over a century, the number of modern tide gauge stations are growing rapidly, with data available both in real-time and as a research product at different time resolutions. As no comprehensive survey of the tide gauge networks has been carried out recently in these basins, the aim of this paper is to map the existing coastal sea level monitoring infrastructures and the respective data availability. The survey encompasses description of major monitoring networks in the Mediterranean and Black55 seas and their characteristics, including the type of sea level sensors, measuring resolutions, data availability and existence of ancillary measurements, altogether collecting information about 236 presently operational tide gauge stations. The availability of the Mediterranean and Black seas sea level data in the global and European sea level repositories has been also screened and classified following their sampling interval and level of quality-check, pointing to the necessity of harmonization of the data available with different metadata and series at different repositories. Finally, an assessment of the networks’ capabilities60 for their usage in different sea level applications has been done, with recommendations that might mitigate the bottlenecks and assure further development of the networks in a coordinated way, being that more necessary in the era of the human-induced climate changes and the sea level ris