{"ID":2854701,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.14790","arxiv_id":"2510.14790","title":"Active Jammer Localization via Acquisition-Aware Path Planning","abstract":"We propose an active jammer localization framework that combines Bayesian optimization with acquisition-aware path planning. Unlike passive crowdsourced methods, our approach adaptively guides a mobile agent to collect high-utility Received Signal Strength measurements while accounting for urban obstacles and mobility constraints. For this, we modified the A* algorithm, A-UCB*, by incorporating acquisition values into trajectory costs, leading to high-acquisition planned paths. Simulations on realistic urban scenarios show that the proposed method achieves accurate localization with fewer measurements compared to uninformed baselines, demonstrating consistent performance under different environments.","short_abstract":"We propose an active jammer localization framework that combines Bayesian optimization with acquisition-aware path planning. Unlike passive crowdsourced methods, our approach adaptively guides a mobile agent to collect high-utility Received Signal Strength measurements while accounting for urban obstacles and mobility...","url_abs":"https://arxiv.org/abs/2510.14790","url_pdf":"https://arxiv.org/pdf/2510.14790v1","authors":"[\"Luis González-Gudiño\",\"Mariona Jaramillo-Civill\",\"Pau Closas\",\"Tales Imbiriba\"]","published":"2025-10-16T15:22:24Z","proceeding":"cs.LG","tasks":"[\"cs.LG\"]","methods":"[]","has_code":false}