Skip to content

Author

Khadijeh Ali Mahmoodi

2 papers indexed here

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

Open access Aug 2026

Comprehensive Channel Modeling of UAV-Assisted FSO Systems under Fog, AoA Fluctuations, and Pointing Errors

This paper investigates the outage performance of unmanned aerial vehicle (UAV)-assisted free-space optical (FSO) communication systems operating in foggy channels. The analysis jointly accounts for atmospheric turbulence, fog-induced attenuation, generalized Beckmann-distributed pointing errors (PE), and angle-of-arrival (AoA) fluctuations caused by UAV orientation jitter. A comprehensive statistical channel model is developed, from which closed-form expressions for outage probability and an analytical characterization of outage capacity are derived. The effects of receiver field-of-view (FoV) limitations and multi-UAV amplify-and-forward relaying on link reliability are also investigated. Numerical results validate the proposed analysis and reveal that AoA fluctuations impose a fundamental performance limit, resulting in an outage floor, particularly under dense fog and narrow-FoV conditions. These findings provide practical design insights for improving the reliability of UAV-assisted FSO communication systems in adverse weather environments.

Mahdi Ataee, S. Sadough, Khadijeh Ali Mahmoodi · 0 citations
Jul 2026

Passive Retroreflector-Based Optical Multilateration for Three-Dimensional UAV Localization

This paper presents a three-dimensional (3D) unmanned aerial vehicle (UAV) localization framework based on optical round-trip time (RTT) ranging and multilateration. Multiple fixed optical transmitters estimate distances via laser reflections from a UAV equipped with passive retroreflectors, enabling infrastructure-assisted localization without active onboard hardware or additional energy consumption. The system model incorporates additive Gaussian ranging noise, and the localization problem is formulated as a non-linear least-squares estimation problem. Monte Carlo simulations demonstrate a median localization error of approximately 0.055 m, with 90% and 95% of errors below 0.11 m and 0.14 m, respectively, under centimeter-level ranging noise. The results show that localization accuracy depends on transmitter geometry and UAV altitude, with errors increasing at higher altitudes and under larger noise levels. Furthermore, increasing the number of transmitters improves accuracy through enhanced measurement redundancy. The results provide practical design guidelines for optical UAV tracking systems.

Khadijeh Ali Mahmoodi, Bastien Béchadergue, Luc Chassagne et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.