18 citations · 24 across the 12 of their papers we have counts for
17 papers
GNSS Spoofing in Mobile Devices: A Survey on Impact and Countermeasures
Robert Argo, Andrea Nardin, Alex Minetto +1
Smartphones rely on Global Navigation Satellite System (GNSS)-based positioning for many of the functions they execute everyday. The GNSS receivers embedded in smartphones are susc…
Implementing Robust M-Estimators with Certifiable Factor Graph Optimization
Zhexin Xu, Hanna Jiamei Zhang, Helena Calatrava +2
Parameter estimation in robotics and computer vision faces formidable challenges from both outlier contamination and nonconvex optimization landscapes. While M-estimation addresses…
Label Hijacking in Track Consensus-Based Distributed Multi-Target Tracking
Helena Calatrava, Shuo Tang, Pau Closas
Distributed multi-target tracking (DMTT) in limited field-of-view (FoV) sensor networks commonly suffers from label inconsistency, whereby different nodes disagree on the identity…
Cooperative Differential GNSS Positioning: Estimators and Bounds
Helena Calatrava, Daniel Medina, Pau Closas
In Differential GNSS (DGNSS) positioning, differencing measurements between a user and a reference station suppresses common-mode errors but also introduces reference-station noise…
K-Track: Kalman-Enhanced Tracking for Accelerating Deep Point Trackers on Edge Devices
Bishoy Galoaa, Pau Closas, Sarah Ostadabbas
Point tracking in video sequences is a foundational capability for real-world computer vision applications, including robotics, autonomous systems, augmented reality, and video ana…
Trends and Challenges in Next-Generation GNSS Interference Management
Leatile Marata, Mariona Jaramillo-Civill, Tales Imbiriba +4
The global navigation satellite system (GNSS) continues to evolve in order to meet the demands of emerging applications such as autonomous driving and smart environmental monitorin…
Bayesian Jammer Localization with a Hybrid CNN and Path-Loss Mixture of Experts
Mariona Jaramillo-Civill, Luis González-Gudiño, Tales Imbiriba +1
Global Navigation Satellite System (GNSS) signals are vulnerable to jamming, particularly in urban areas where multipath and shadowing distort received power. Previous data-driven…
Active Jammer Localization via Acquisition-Aware Path Planning
Luis González-Gudiño, Mariona Jaramillo-Civill, Pau Closas +1
We propose an active jammer localization framework that combines Bayesian optimization with acquisition-aware path planning. Unlike passive crowdsourced methods, our approach adapt…
DPMM-CFL: Clustered Federated Learning via Dirichlet Process Mixture Model Nonparametric Clustering
Mariona Jaramillo-Civill, Peng Wu, Pau Closas
Clustered Federated Learning (CFL) improves performance under non-IID client heterogeneity by clustering clients and training one model per cluster, thereby balancing between a glo…
Interpretable Augmented Physics-Based Model for Estimation and Tracking
Ondřej Straka, Jindřich Duník, Pau Closas +1
State-space estimation and tracking rely on accurate dynamical models to perform well. However, obtaining an vaccurate dynamical model for complex scenarios or adapting to changes…
Robust Recursive Fusion of Multiresolution Multispectral Images with Location-Aware Neural Networks
Haoqing Li, Ricardo Borsoi, Tales Imbiriba +1
Multiresolution image fusion is a key problem for real-time satellite imaging and plays a central role in detecting and monitoring natural phenomena such as floods. It aims to solv…
Recursive Deep Inverse Reinforcement Learning
Paul Ghanem, Owen Howell, Michael Potter +4
Inferring an adversary's goals from exhibited behavior is crucial for counterplanning and non-cooperative multi-agent systems in domains like cybersecurity, military, and strategy…
Advances in Anti-Deception Jamming Strategies for Radar Systems: A Survey
Helena Calatrava, Shuo Tang, Pau Closas
Deception jamming has long been a significant threat to radar systems, interfering with search, acquisition, and tracking by introducing false information that diverts attention fr…
A Bayesian Framework for Clustered Federated Learning
Peng Wu, Tales Imbiriba, Pau Closas
One of the main challenges of federated learning (FL) is handling non-independent and identically distributed (non-IID) client data, which may occur in practice due to unbalanced d…
AI-Aided Kalman Filters
Nir Shlezinger, Guy Revach, Anubhab Ghosh +7
The Kalman filter (KF) and its variants are among the most celebrated algorithms in signal processing. These methods are used for state estimation of dynamic systems by relying on…
Mitigation of Radar Range Deception Jamming Using Random Finite Sets
Helena Calatrava, Aanjhan Ranganathan, Tales Imbiriba +3
This paper presents a radar target tracking framework for addressing main-beam range deception jamming attacks using random finite sets (RFSs). Our system handles false alarms and…
On the Impact of Sampling on Deep Sequential State Estimation
Helena Calatrava, Ricardo Augusto Borsoi, Tales Imbiriba +1
State inference and parameter learning in sequential models can be successfully performed with approximation techniques that maximize the evidence lower bound to the marginal log-l…