Stefania Bartoletti

A Mathematical Model for Wideband Ranging

Wideband ranging is essential for numerous emerging applications that rely on accurate location awareness. The quality of range information, which depends on network intrinsic properties and signal processing techniques, affects the localization accuracy. A popular class of ranging techniques is based on energy detection owing to its low-complexity implementation. This paper establishes a tractable model for the range information as a function of wireless environment, signal features, and energy detection techniques. Such a model serves as a cornerstone for the design and analysis of wideband ranging systems. Based on the proposed model, we develop practical soft-decision and hard-decision algorithms. A case study for ranging and localization systems operating in a wireless environment is presented. Sample-level simulations validate our theoretical results.

Analysis of UWB Radar Sensor Networks

Radar sensor networks (RSNs) are gaining importance in the context of passive localization and tracking. The performance of RSNs is affected by disturbances, systems parameters, network topology, and the number of radar elements. In this paper, we derive a unified analytical framework that takes all this aspects into account and allows the derivation of probability of detection and localization uncertainty. The results enable the system designer to have a clear understanding on the effects of each system parameter and the trade-off between performance and complexity. Moreover, the potential for high-accuracy passive localization of ultrawide bandwidth (UWB) systems is shown.

Blind Selection of Representative Observations for Sensor Radar Networks

Sensor radar networks enable important new applications based on accurate localization. They rely on the quality of range measurements, which serve as observations for inferring a target location. In harsh propagation environments (e.g., indoors), such observations can be nonrepresentative of the target due to noise, multipath, clutter, and non-line-of-sight conditions leading to target misdetection, false-alarm events, and inaccurate localization. These conditions can be mitigated by selecting and processing a subset of representative observations. We introduce blind techniques for the selection of representative observations gathered by sensor radars operating in harsh environments. A methodology for the design and analysis of sensor radar networks is developed, taking into account the aforementioned impairments and observation selection. Results are obtained for noncoherent ultra-wideband sensor radars in a typical indoor environment (with obstructions, multipath, and clutter) to enable a clear understanding of how observation selection improves the localization accuracy.

Sensor Radar Networks for Indoor Tracking

Sensor radars (SRs) are important for a variety of applications requiring passive tracking of moving targets. The accuracy of passive tracking is severely degraded by wireless propagation impairments such as multipath, clutter, and non line-of-sight conditions, especially in indoor environments. These impairments can be alleviated by exploiting the multiple sensing and smart processing of radar signals. In this letter, we aim to illustrate the dependence of sensor topologies, waveform processing methods, and tracking algorithm parameters on SR performance. A case study involving both monostatic and multistatic ultra-wideband SRs for indoor environments is presented by jointly considering the wireless medium, ranging technique, and tracking algorithm.

An UWB-UHF semi-passive RFID System for localization and tracking applications

We present a novel radio-frequency identification (RFID) system with capability of localization and tracking of passive or semi-passive tags. Localization and tracking features are enabled by backscatter modulation on ultra-wide bandwidth tags antenna. A ultra-high frequency signal allows the wake-up of the tags enabling the reduction of energy consumption and ensuring compatibility with existing RFID systems. The overall system as well as the reader and tag architectures are introduced. The localization and tracking performance evaluation is presented in some reference scenarios.

Detection of Multiple Tags Based on Impulsive Backscattered Signals

Passive and semipassive ultrawideband (UWB) radio-frequency identification (RFID) technology has been recently proposed to offer high-accuracy localization capabilities in next-generation RFID systems. This technology relies on the modulation of backscattered signals, i.e., backscatter modulation, from multiple tags present in the environment. The detection of multiple tags based on backscattered signals is challenging in harsh environments with nonideal conditions such as clutter, near-far interference effects, and clock drift. This paper analyzes the detection of multiple tags employing UWB backscatter modulation and proposes practical signaling, spreading codes, and detection schemes that are robust to nonideal conditions. A case study is presented to evaluate the performance of the proposed technique for the detection of multiple tags based on impulsive backscattered signals.

Passive radar via LTE signals of opportunity

Passive radars relying on signals of opportunity enable new applications based on stealth tracking of targets without the need of radar signals emissions. Long term evolution (LTE) base stations employing orthogonal frequency division multiplexing (OFDM) signals are excellent candidates as illuminators of opportunity thanks to their wide availability. The tracking accuracy of such passive radars depends on prior knowledge (e.g., the wireless environment) and signal processing (e.g., clutter mitigation and tracking algorithm). This paper proposes passive radar systems exploiting LTE base stations as illuminators of opportunity to detect and track moving targets in a monitored environment. We analyze such systems based on a Bayesian framework for detection of moving targets and estimation of their position and velocity. A case study accounting for the LTE extended pedestrian model is presented, with various settings in terms of network configuration, wireless propagation, and signal processing.

UWB sensor radar networks for indoor passive navigation

Localization and navigation of passive objects enables new important applications in wireless environments. Monostatic sensor radar networks generate interesting solutions for passive localization and navigation in a variety of scenarios. In particular, ultrawide band (UWB) sensing provides fine delay resolution enabling high localization accuracy even in harsh propagation environments such as indoor. We develop a framework for design and analysis of passive navigation based on UWB monostatic sensor radar networks that relies on propagation environment and time-of-arrival estimation characterized by network experiments. As a case study, an UWB monostatic sensor radar network deployed in an indoor environment is considered, and the position of moving objects is inferred. In particular, Bayesian navigation based on particle filters implementation is employed and the role of mobility model for inferring target position is shown.

UWB passive navigation in indoor environments

Localization and navigation of passive target objects play a key role in many important applications. An interesting solution for passive localization and navigation is given by monostatic wireless sensor radar (WSR) networks. In this context, ultrawide band (UWB) radar provide fine delay resolution enabling high accuracy localization also in harsh environments such as indoor. We present a mathematical framework for analysis and design of passive navigation based on UWB monostatic WSRs that relies on environment propagation and time-of-arrival estimation characterized by network experiments. A case study where a UWB monostatic WSR network is deployed to infer the position of moving target objects is considered. In particular, Bayesian navigation based on particle filters implementation is analyzed and the role of mobility model for inferring target position is shown.

The GRETA architecture for energy efficient radio identification and localization

This paper presents an overview of the innovative solutions developed within the Italian project GRETA (GREen TAgs and sensors with ultra-wide-band identification and localization capabilities), whose aim is the development of a distributed and comprehensive system for identification, localization, tracking and monitoring in indoor scenarios. The system is based on hybrid UWB-UHF RFID tags, and the realization and experimental validation of novel tag prototypes based on environmentally friendly materials is a major achievement of the project.