Multi-UAV Trajectory Optimization for Bearing-Only Localization in GPS Denied Environments

2026-02-11

AI Summary

This work addresses the challenge of target localization in GPS-denied maritime environments, where conventional approaches rely on costly gimbaled cameras and are vulnerable to single-point failures. The authors propose a multi-UAV cooperative trajectory optimization framework that, for the first time, integrates an estimation-aware mechanism into collaborative localization using fixed-view, non-gimbaled cameras. The framework jointly accounts for platform dynamics, mission requirements, and imaging events to generate trajectories that balance dynamic feasibility with estimation performance. Experimental results demonstrate that the proposed approach reduces localization error by over 50% compared to heuristic paths. Moreover, the multi-UAV fixed-camera system achieves localization accuracy comparable to—or even surpassing—that of a single gimbaled-camera UAV, while significantly enhancing system scalability and mission robustness.

Technology Category

• Intelligent Robots: Localization, Mapping, and Navigation
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Local Search

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Location- and context-aware Web and WoT applications and services
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Accurate localization of maritime targets by unmanned aerial vehicles (UAVs) remains challenging in GPS-denied environments. UAVs equipped with gimballed electro-optical sensors are typically used to localize targets, however, reliance on these sensors increases mechanical complexity, cost, and susceptibility to single-point failures, limiting scalability and robustness in multi-UAV operations. This work presents a new trajectory optimization framework that enables cooperative target localization using UAVs with fixed, non-gimballed cameras operating in coordination with a surface vessel. This estimation-aware optimization generates dynamically feasible trajectories that explicitly account for mission constraints, platform dynamics, and out-of-frame events. Estimation-aware trajectories outperform heuristic paths by reducing localization error by more than a factor of two, motivating their use in cooperative operations. Results further demonstrate that coordinated UAVs with fixed, non-gimballed cameras achieve localization accuracy that meets or exceeds that of single gimballed systems, while substantially lowering system complexity and cost, enabling scalability, and enhancing mission resilience.

Problem

• Bearing-only localization
• GPS-denied environments
• Multi-UAV coordination
• Fixed cameras
• Trajectory optimization

Innovation

• trajectory optimization
• bearing-only localization
• estimation-aware planning
• fixed-camera UAVs
• GPS-denied environment