Davide Dardari

Indoor Tracking: Theory, Methods, and Technologies

In the last decade, the research on and the technology for outdoor tracking have seen an explosion of advances. It is expected that in the near future, we will witness similar trends for indoor scenarios where people spend more than 70% of their lives. The rationale for this is that there is a need for reliable and high-definition real-time tracking systems that have the ability to operate in indoor environments, thus complementing those based on satellite technologies, such as the Global Positioning System (GPS). The indoor environments are very challenging, and as a result, a large variety of technologies have been proposed for coping with them, but no legacy solution has emerged. This paper presents a survey on indoor wireless tracking of mobile nodes from a signal processing perspective. It can be argued that the indoor tracking problem is more challenging than the problem on indoor localization. The reason is simple: From a set of measurements, one has to estimate not one location but a series of correlated locations of a mobile node. The paper illustrates the theory, the main tools, and the most promising technologies for indoor tracking. New directions of research are also discussed.

High-accuracy localization for assisted living: 5G systems will turn multipath channels from foe to friend

Assisted living (AL) technologies, enabled by technical advances such as the advent of the Internet of Things, are increasingly gaining importance in our aging society. This article discusses the potential of future high-accuracy localization systems as a key component of AL applications. Accurate location information can be tremendously useful to realize, e.g., behavioral monitoring, fall detection, and real-time assistance. Such services are expected to provide older adults and people with disabilities with more independence and thus to reduce the cost of caretaking. Total cost of ownership and ease of installation are paramount to make sensor systems for AL viable. In case of a radio-based indoor localization system, this implies that a conventional solution is unlikely to gain widespread adoption because of its requirement to install multiple fixed nodes (anchors) in each room. This article therefore places its focus on 1) discussing radiolocalization methods that reduce the required infrastructure by exploiting information from reflected multipath components (MPCs) and 2) showing that knowledge about the propagation environment enables localization with high accuracy and robustness. It is demonstrated that new millimeter-wave (mm-wave) technology, under investigation for 5G communications systems, will be able to provide centimeter (cm)-accuracy indoor localization in a robust manner, ideally suited for AL.

Position and orientation error bound for wideband massive antenna arrays

Next generation cellular networks will experience the combination of femtocells, millimeter-wave (mmW) communications and massive antenna arrays. In addition to benefits in terms of an increased communication capacity, this mix of technologies can be fruitfully exploited to enable high-accuracy indoor positioning. In fact, thanks to the high beamforming capability of massive arrays, mobile terminal localization can be performed in principle by using only one single access point (AP), thus avoiding costly infrastructures with additional APs dedicated to positioning. In this context, our paper aims at investigating the localization and orientation performance limits of networks employing wideband massive arrays both at receiving and transmitting devices. In particular, the effects of the array structure, bandwidth and synchronization error are studied both at mmW and at 10GHz, when phased, timed and random arrays are employed.

Personal Mobile Radars with Millimeter-Wave Massive Arrays for Indoor Mapping

The adoption of millimeter-wave technology could open the possibility to integrate massive antenna arrays inside future 5G user mobile devices, with the possibility to enable new interesting applications. Within this context, in this paper we put forth the concept of a personal mobile radar operating at millimeter-waves and consisting of a massive array for accurate environmental mapping. Frequency selectivity and phase quantization effects are accounted for to characterize the achievable angle and range resolution necessary to collect environmental information. Successively, we propose an effective grid-based Bayesian mapping approach by introducing a new state-space model, which profits of the beneficial effects of the massive antenna array characteristics. Numerical results show that the idea herein investigated is feasible, and that a significant mapping performance is attainable even employing coarse antenna arrays provided that the number of antenna elements is sufficiently high.

Passive UWB RFID for Tag Localization: Architectures and Design

In the new scenarios foreseen by the Internet of Things, industrial and commercial systems will be required to detect and localize tagged items with high accuracy, as well as to monitor the level of certain parameters of interest through the deployment of wireless sensors. To meet these challenging requirements, the adoption of passive and semi-passive ultra-wideband (UWB) radio-frequency identification (RFID) appears a promising solution, which overcomes the limitations of standard Gen.2 ultra-high frequency (UHF) RFID. The design and implementation of such systems pose several practical constraints, impacting the overall network architecture. In this paper, the main issues and challenging aspects for the design of a UWB-RFID network considering architectural and protocol choices are discussed in a unitary framework, and practical solutions, accounting for the presented issues, are proposed. Moreover, the possible integration of UWB-RFID with standard Gen.2 UHF-RFID is proposed as an interesting option, discussing architectural solutions, their advantages, and drawbacks.

Application of transmitarray antennas for indoor mapping at millimeter-waves

Millimeter-waves are expected to play a key role in next 5G scenario due to the availability of a large clean unlicensed bandwidth at 60 GHz and the possibility to realize packed antenna arrays, with a consequent increase of the communication capacity and the introduction of new functionalities, such as high-definition localization and personal radar for automatic environment mapping. In this paper we propose the adoption of millimeter-wave transmitarrays for personal radar applications and we investigate the impact of the radiation pattern characteristics on the map reconstruction accuracy, by analysing how the number of array elements, of quantization bits and the focal distance affect the environment reconstruction performance.

A Robust Wireless Sensor Network for Landslide Risk Analysis: System Design, Deployment, and Field Testing

In this paper, we propose a wireless sensor network (WSN) designed for monitoring and risk management of landslides, where data collected by sensors are delivered through the network to a remote unit for online analysis and alerting. To ensure fast deployment, robustness in harsh environments, and very long lifetime, the sensor nodes and the communication protocol have been specifically conceived, so that the network is self-organizing, fault tolerant, and adaptive. The WSN has been installed on a landslide located in Torgiovannetto (Italy) for an experimental campaign of several months where performance metrics, such as radio link and path statistics as well as battery levels, have been collected. These metrics demonstrated the effectiveness of the network protocols to manage self-organization, node failures, low link quality, and unexpected battery depletion. With negligible human intervention during the pilot experiment, the WSN revealed a very high level of robustness, which makes it suitable to monitor landslides in critical scenarios.

Defective Sensor Identification for WSNs Involving Generic Local Outlier Detection Tests

The behavior of a wireless sensor network dedicated to distributed estimation tasks may be significantly altered by the presence of nodes whose sensors are defective and produce erroneous measurements. This paper proposes and analyzes the performance of two distributed algorithms to help each node in determining whether it is equipped with a defective sensor. A node first collects data from its neighborhood, processes them to decide, using some generic local outlier detection test, whether these data contain outliers and broadcasts the result. Then, it determines the status of its own sensor using its result and those received from neighboring nodes. A single-decision and an iterative algorithm for defective sensor detection are proposed. Bounds on the performance of the single-decision algorithm are derived. A theoretical analysis of the probability of error and of the equilibrium of the iterative algorithm is provided for a wide class of local outlier detection tests. The tradeoff between false alarm probability and detection probability is characterized theoretically and by simulation. MAC-layer issues, as well as the effect of packet losses are accounted for.

Joint Energy Detection and Massive Array Design for Localization and Mapping

The adoption of massive arrays for simultaneous localization and mapping or personal radar applications enables the possibility to detect and localize surrounding objects through an accurate beamforming procedure. Unfortunately, when a classical constant false alarm rate approach accounting for ideal-pencil beam pattern is adopted, ambiguities in signal detection could arise due to the presence of side-lobes which can cause non-negligible errors in target detection and ranging. To counteract such effect, in this paper we propose a joint threshold-array design approach, where the antenna characteristics are taken into account to best set the threshold and to guarantee the desired detection and ranging performance at the non-coherent receiver section. In order to consider realistic arrays impairments, we focus our attention on the number of antenna elements and of phase shifter bits used for beamforming as key players in defining a trade-off between structural complexity, well-defined radiation pattern, and localization performance. Simulation and measurement results show that the number of bits per phase shifter can be relaxed in favor of a simpler array design, if the number of antennas is sufficiently high and the side-lobes are kept within a suitable level allowing a desired robustness to interference signals.

Low-complexity distributed fault detection for wireless sensor networks

To guarantee its integrity, a wireless sensor network needs to efficiently detect faulty nodes producing erroneous measurements. This paper proposes a fully distributed fault detection algorithm. A node first collects the measurements of its neighborhood, processes them to decide whether they contain outliers, and broadcasts the result. Then, it decides autonomously about its functioning status. The detection algorithm is proposed in two variants, depending on the proportion of faulty nodes in the network. A theoretical analysis of the probability of error and of the convergence of the algorithm is provided. The tradeoff between false alarm probability and detection probability is characterized using simulation.