arXiv subjects

Anna Guerra

Publications and source records attributed to Anna Guerra.

26 records · Page 2Linked to original sources

arXiv2020

Reinforcement Learning for UAV Autonomous Navigation, Mapping and Target Detection

In this paper, we study a joint detection, mapping and navigation problem for a single unmanned aerial vehicle (UAV) equipped with a low complexity radar and flying in an unknown environment. The goal is to optimize its trajectory with the purpose of maximizing the mapping accuracy and, at the same time, to avoid areas where measurements might not be sufficiently informative from the perspective of a target detection. This problem is formulated as a Markov decision process (MDP) where the UAV is an agent that runs either a state estimator for target detection and for environment mapping, and a reinforcement learning (RL) algorithm to infer its own policy of navigation (i.e., the control law). Numerical results show the feasibility of the proposed idea, highlighting the UAV's capability of autonomously exploring areas with high probability of target detection while reconstructing the surrounding environment.

cs.RO↗

arXiv2020

Dynamic Radar Network of UAVs: A Joint Navigation and Tracking Approach

Nowadays there is a growing research interest on the possibility of enriching small flying robots with autonomous sensing and online navigation capabilities. This will enable a large number of applications spanning from remote surveillance to logistics, smarter cities and emergency aid in hazardous environments. In this context, an emerging problem is to track unauthorized small unmanned aerial vehicles (UAVs) hiding behind buildings or concealing in large UAV networks. In contrast with current solutions mainly based on static and on-ground radars, this paper proposes the idea of a dynamic radar network of UAVs for real-time and high-accuracy tracking of malicious targets. To this end, we describe a solution for real-time navigation of UAVs to track a dynamic target using heterogeneously sensed information. Such information is shared by the UAVs with their neighbors via multi-hops, allowing tracking the target by a local Bayesian estimator running at each agent. Since not all the paths are equal in terms of information gathering point-of-view, the UAVs plan their own trajectory by minimizing the posterior covariance matrix of the target state under UAV kinematic and anti-collision constraints. Our results show how a dynamic network of radars attains better localization results compared to a fixed configuration and how the on-board sensor technology impacts the accuracy in tracking a target with different radar cross sections, especially in non line-of-sight (NLOS) situations.

cs.IT↗

arXiv2020

An Ultra-wideband Battery-less Positioning System for Space Applications

An ultra-wide bandwidth (UWB) remote-powered positioning system for potential use in tracking floating objects inside space stations is presented. It makes use of battery-less tags that are powered-up and addressed through wireless power transfer in the UHF band and embed an energy efficient pulse generator in the 3-5 GHz UWB band. The system has been mounted on the ESA Mars Rover prototype to demonstrate its functionality and performance. Experimental results show the feasibility of centimeter-level localization accuracy at distances larger than 10 meters, with the capability of determining the position of multiple tags using a 2W-ERP power source in the UHF RFID frequency band.

eess.SP↗

arXiv2019

Automatic Mapping of the Indoor World with Personal Radars

Digital maps will revolutionize our experience of perceiving and navigating indoor environments. While today we rely only on the representation of the outdoors, the mapping of indoors is mainly a part of the traditional SLAM problem where robots discover the surrounding and perform self-localization. Nonetheless, robot deployment prevents from a large diffusion and fast mapping of indoors and, further, they are usually equipped with laser and vision technology that fail in scarce visibility conditions. To this end, a possible solution is to turn future personal devices into personal radars as a milestone towards the automatic generation of indoor maps using massive array technology at millimeter-waves, already in place for communications. In this application-oriented paper, we will describe the main achievements attained so far to develop the personal radar concept, using ad-hoc collected experimental data, and by discussing possible future directions of investigation.

eess.SP↗

arXiv2019

Joint Indoor Localization and Navigation of UAVs for Network Formation Control

In this paper, we propose a joint indoor localization and navigation algorithm to enable a swarm of unmanned aerial vehicles (UAVs) to deploy in a specific spatial formation in indoor environments. In the envisioned scenario, we consider a static user acting as a central unit whose main task is to acquire all the UAV measurements carrying position-dependent information and to estimate the UAV positions when there is no existing infrastructure for positioning. Subsequently, the user exploits the estimated positions as inputs for the navigation control with the aim of deploying the UAVs in a desired formation in space (formation shaping). The user plans the trajectory of each UAV in real time, guaranteeing a safe navigation in the presence of obstacles. The proposed algorithm guides the UAVs to their desired final locations with good accuracy.

eess.SP↗

arXiv2019

Dynamic Radar Networks of UAVs

In the incoming years, the low-aerial space will be crowded by unmanned aerial vehicles (UAVs), which will be providing different services. In this expected context, an emerging problem is to detect and track unauthorized or malicious mini/micro UAVs. In contrast to current solutions mainly based on fixed terrestrial radars, this article will put forth the idea of a dynamic radar network (DRN) composed of UAVs able to smartly adapt their formation-navigation control to best track malicious UAVs in real-time, with high accuracy, and in a distributed fashion. To this end, some technological solutions and the main methods for target detection and tracking will be described. Further, an optimized navigation scheme will be developed according to an information-seeking approach. Some examples of simulation results and future directions of work will be finally presented highlighting the advantages of dynamic and reconfigurable networks over static ones.

eess.SP↗

arXiv2019

Non-Centralized Navigation for Source Localization by Cooperative UAVs

In this paper, we propose a distributed solution to the navigation of a population of unmanned aerial vehicles (UAVs) to best localize a static source. The network is considered heterogeneous with UAVs equipped with received signal strength (RSS) sensors from which it is possible to estimate the distance from the source and/or the direction of arrival through ad-hoc rotations. This diversity in gathering and processing RSS measurements mitigates the loss of localization accuracy due to the adoption of low-complexity sensors. The UAVs plan their trajectories on-the-fly and in a distributed fashion. The collected data are disseminated through the network via multi-hops, therefore being subject to latency. Since not all the paths are equal in terms of information gathering rewards, the motion planning is formulated as a minimization of the uncertainty of the source position under UAV kinematic and anti-collision constraints and performed by 3D non-linear programming. The proposed analysis takes into account non-line-of-sight (NLOS) channel conditions as well as measurement age caused by the latency constraints in communication.

eess.SP↗

arXiv2017

Single Anchor Localization and Orientation Performance Limits using Massive Arrays: MIMO vs. Beamforming

Next generation cellular networks will experience the combination of femtocells, millimeter-wave (mm-wave) communications and massive antenna arrays. Thanks to the beamforming capability as well as the high angular resolution provided by massive arrays, only one single access point (AP) acting as an anchor node could be used for localization estimation, thus avoiding over-sized infrastructures dedicated to positioning. In this context, our paper aims at investigating the localization and orientation performance limits employing massive arrays both at the AP and mobile side. Thus, we first asymptotically demonstrate the tightness of the Cramer-Rao bound (CRB) in massive array regime, and in the presence or not of multipath. Successively, we propose a comparison between MIMO and beamforming in terms of array structure, time synchronization error and multipath components. Among different array configurations, we consider also random weighting as a trade-off between the high diversity gain of MIMO and the high directivity guaranteed by phased arrays. By evaluating the CRB for the different array configurations, results show the interplay between diversity and beamforming gain as well as the benefits achievable by varying the number of array elements in terms of localization accuracy.

cs.IT↗