Impact of Altitude, Bandwidth, and NLOS Bias on TDOA-Based 3D UAV Localization: Experimental Results and CRLB Analysis

TL;DR

This study examines how altitude, bandwidth, and NLOS conditions affect UAV localization accuracy using TDOA measurements, supported by experimental data and CRLB analysis, revealing key factors influencing performance in real-world scenarios.

Contribution

The paper develops a 3D TDOA CRLB model accounting for altitude, bandwidth, and NLOS effects, validated through extensive UAV flight experiments, highlighting limitations of traditional LOS models.

Findings

Higher bandwidths improve time resolution and accuracy.

Increased altitude reduces NLOS biases and multipath effects.

Hovering near RF sensors can degrade localization accuracy.

Abstract

This paper investigates unmanned aerial vehicle (UAV) localization using time difference of arrival (TDOA) measurements under mixed line-of-sight (LOS) and non-line-of-sight (NLOS) conditions. A 3D TDOA Cram\'er-Rao lower bound (CRLB) model is developed accounting for varying altitudes and signal bandwidths. The model is compared to five real-world UAV flight experiments conducted at different altitudes (40 m, 70 m, 100 m) and bandwidths (1.25 MHz, 2.5 MHz, 5 MHz) using Keysight N6841A radio frequency (RF) sensors of the NSF AERPAW platform. Results show that altitude, bandwidth, and NLOS obstructions significantly impact localization accuracy. Higher bandwidths enhance signal time resolution, while increased altitudes mitigate multipath and NLOS biases, both contributing to improved performance. However, hovering close to RF sensors degrades accuracy due to antenna pattern misalignment and geometric dilution of precision. These findings emphasize the inadequacy of traditional LOS-based models in NLOS environments and highlight the importance of adaptive approaches for accurate localization in challenging scenarios.