A Robust UAV-Based Approach for Power-Modulated Jammer Localization Using DoA

TL;DR

This paper introduces a UAV-based localization method called SPGD that effectively detects power-modulated jammers with high robustness and low computational cost.

Contribution

The paper presents a novel sample pruning gradient descent (SPGD) algorithm for robust UAV-based jammer localization, addressing challenges posed by power modulation.

Findings

SPGD achieves high localization accuracy in simulations.

The method demonstrates robustness against multiple power-modulated jammers.

Computational complexity remains low, suitable for real-time applications.

Abstract

Unmanned aerial vehicles (UAVs) are well-suited to localize jammers, particularly when jammers are at non-terrestrial locations, where conventional detection methods face challenges. In this work we propose a novel localization method, sample pruning gradient descend (SPGD), which offers robust performance against multiple power-modulated jammers with low computational complexity.