DOI: 10.5061/dryad.vq83bk44h
title: AERPAW keysight N6841A RF sensor UAV localization measurements with LOS/NLOS information July 2024

description: This dataset supports research into UAV localization using Time Difference
 of Arrival (TDOA) measurements under mixed line-of-sight (LOS) and
 non-line-of-sight (NLOS) conditions. It contains data collected from five
 UAV flight experiments conducted at varying altitudes (40 m, 70 m, 100 m)
 and bandwidths (1.25 MHz, 2.5 MHz, 5 MHz) using Keysight N6841A RF sensors
 on the AERPAW testbed. The dataset includes UAV position estimates, ground
 truth coordinates, LOS/NLOS indicators for each RF sensor, and
 localization performance metrics. The dataset is a valuable resource for
 studying the impacts of altitude, bandwidth, and NLOS biases on UAV
 localization in real-world environments.
description: The dataset was collected during five UAV flight experiments
 conducted at the Aerial Experimentation and Research Platform for Advanced
 Wireless (AERPAW) testbed. The experiments involved UAVs equipped with a
 software-defined radio (SDR) transmitting a 3.32 GHz signal with varying
 bandwidths (1.25 MHz, 2.5 MHz, and 5 MHz) at different altitudes (40 m, 70
 m, and 100 m). Four Keysight N6841A RF sensors were deployed on towers
 LW2-LW5 at AERPAW's Lake Wheeler Road Field Labto capture
 time-stamped RF signals. The UAVs followed precise, repeatable flight
 trajectories designed to evaluate localization performance under mixed
 line-of-sight (LOS) and non-line-of-sight (NLOS) conditions. Environmental
 factors, including trees and buildings, introduced signal obstructions to
 simulate realistic scenarios. The collected data
 includes time-difference-of-arrival (TDOA) measurements, LOS/NLOS
 indicators, and ground truth UAV positions.
description: # AERPAW keysight N6841A RF sensor UAV localization measurements with
 LOS/NLOS information July 2024
 [https://doi.org/10.5061/dryad.vq83bk44h](https://doi.org/10.5061/dryad.vq83bk44h) ## Description of the data and file structure The experimental efforts for which this data was collected aimed to evaluate the performance of Time Difference of Arrival (TDOA)-based 3D localization of UAVs in real-world environments. A UAV equipped with a software-defined radio transmitted RF signals at varying bandwidths (1.25 MHz, 2.5 MHz, and 5 MHz) and altitudes (40 m, 70 m, and 100 m) over controlled flight trajectories. Four Keysight N6841A RF sensors were deployed on fixed towers to capture RF signals and process them using TDOA algorithms for position estimation. The experiments were conducted under mixed line-of-sight (LOS) and non-line-of-sight (NLOS) conditions with the additional use of ray-tracing simulations to analyze LOS/NLOS effects. These efforts sought to understand how altitude, bandwidth, and environmental factors impact UAV localization accuracy ### Files and variables #### File: TDOA\_UAV\_Localization\_Data.zip **Description:** The .zip file contains one .csv file for each flight, with the altitude, bandwidth, and date of recording specified in the file name. For instance, the file `40m1.25MHz7.15.24.csv` corresponds to a flight conducted at an altitude of 40 meters, with a signal bandwidth of 1.25 MHz, on July 15th, 2024. The archive includes five .csv files, each representing one of the five flights. Each .csv file contains the following information: * Center frequency of the signal. * Latitude, longitude, and elevation estimates for the UAV. * Ground truth coordinates (latitude, longitude, and altitude) labeled with "GT." * RHO and CEP metrics for localization performance. * Timestamps corresponding to each position estimate. * A binary variable (LOStoLW2-5) indicating line-of-sight (LOS) status to AERPAW towers LW2 through LW5: * A value of `1` indicates LOS to the respective tower. * A value of `0` indicates non-line-of-sight (NLOS) to the respective tower. If the latitude, longitude, and elevation estimates for a given measurement are all `0`, it signifies that the geolocation software was unable to generate a reliable position estimate. Additionally, the MATLAB helper file 'KeysightRTDOALocalizationforFlights.m' is included in the .zip file to help process TDOA-based UAV localization data from a selected `.csv` file and generate multiple visualizations and performance metrics to evaluate the accuracy of the UAV position estimates. The key functionalities of the script include:  1. **Data Preprocessing:** * Reads a `.csv` file containing TDOA localization data for a specific UAV flight. * Removes rows where location estimates are missing (latitude, longitude, and altitude are zero). * Extracts relevant columns, such as latitude, longitude, altitude, ground truth coordinates, LOS/NLOS indicators, and timestamps. 2. **Visualization:** * **3D UAV Trajectory:** Plots the UAV's ground truth 3D flight path with annotations for start and end points. * **Estimated vs Ground Truth Coordinates:** Compares the estimated UAV positions to ground truth coordinates in 2D, alongside tower locations. * **Error vs Altitude:** Plots the localization error as a function of the UAV's altitude. * **Error vs Time:** Shows how localization error changes over time. * **Altitude vs Time:** Displays the UAV's altitude throughout the flight. * **3D Trajectory with Error Coding:** Visualizes the UAV's trajectory with color-coded markers indicating distance error (&lt;100m in green, ≥100m in red). * **Ground Truth Coordinates with Error Coding:** Maps the ground truth coordinates with color-coded error levels, also marking tower locations. 3. **Error Analysis:** * Computes the distance error between estimated and ground truth coordinates using geodetic distance calculations. * Highlights regions with high localization error (e.g., errors ≥100m). * Calculates and outputs the average distance error and the mean error for data points with errors under 100 meters. Users simply need to add the `.csv` files and the `.m` file to the working directory of their MATLAB software and update the filename on line 3 of the script to begin. This script offers a comprehensive analysis of UAV localization performance for each flight, enabling the assessment of factors such as LOS/NLOS conditions, altitude, and bandwidth. ## Code/software A licensed installation of MATLAB and the Mapping Toolbox are required to execute the script. ## Access information Other publicly accessible locations of the data: * [https://aerpaw.org/dataset/aerpaw-rf-sensor-measurements-with-uav-july-2024/](https://aerpaw.org/dataset/aerpaw-rf-sensor-measurements-with-uav-july-2024/)