# Active Jammer Localization via Acquisition-Aware Path Planning

arXiv: https://arxiv.org/abs/2510.14790 · HTML: https://mlsanity.com/paper/2510.14790/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 23 references that are in the map.
- First posted on arXiv 16 Oct 2025.

## Builds on (most cited first, 3 of 3)

- [Jamming Source Localization Using Augmented Physics-Based Model](https://mlsanity.com/paper/2212.08097/) (2022)
- [Using Mobile Phones for Participatory Detection and Localization of a GNSS Jammer](https://mlsanity.com/paper/2305.02038/) (2023)
- [GNSS jammer localization and identification with airborne commercial GNSS receivers](https://mlsanity.com/paper/2503.20352/) (2025)

## Abstract (arXiv)

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.