Active Localisation of Intermittent Radio Frequency Interference Sources Using an Unmanned Aerial Vehicle in Urban Environments

ABSTRACT

Localisation of intermittent radio frequency (RF) interference sources is important for urban spectrum monitoring and the protection of safety‐critical navigation services. Among existing approaches, received signal strength indicator (RSSI)‐based localisation is attractive for unmanned aerial vehicle (UAV) platforms because it requires lightweight receivers and no antenna arrays or strict time synchronisation. However, most RSSI‐based localisation and UAV path‐planning methods rely on fixed sensing geometries, empirical dwell times or propagation models weakly coupled with online manoeuvring decisions. These limitations become critical in dense urban environments, where building‐induced line‐of‐sight/non‐line‐of‐sight transitions, intermittent emissions and unknown propagation parameters jointly reduce localisation reliability. In this paper, we propose a UAV‐based active localisation framework, termed VISTA, for intermittent urban RF interference sources. VISTA formulates each decision as a joint selection of flight direction and dwell time, maintains a joint belief over the source position, propagation parameters and emission behaviour and uses a unified action‐conditioned observation model for both planning and Bayesian update. A control‐aware Bayes‐risk criterion with three‐branch approximate scoring enables real‐time action selection. Unlike waypoint‐only informative path planning or estimator‐side NLOS mitigation, VISTA couples spatial motion, sensing time, intermittent detection and map‐aware propagation within one Bayesian action‐evaluation loop. Closed‐loop simulations using real Shanghai Lujiazui GIS data evaluate the proposed method, showing an reduction in per‐step planning time compared with a Monte Carlo reference while maintaining comparable localisation accuracy.