UWB Positioning and Tracking Data Set UWB positioning data set contains measurements from four different indoor environments. The data set contains measurements that can be used for range-based positioning evaluation in different indoor environments. # Measurement system The measurements were made using 9 DW1000 UWB transceivers (DWM1000 modules) connected to the networked RaspberryPi computer using in-house radio board SNPN_UWB. 8 nodes were used as positioning anchor nodes with fixed locations in individual indoor environment and one node was used as a mobile positioning tag. Each UWB node is designed arround the RaspberryPi computer and are wirelessly connected to the measurement controller (e.g. laptop) using Wi-Fi and MQTT communication technologies. All tag positions were generated beforehand to as closelly resemble the human walking path as possible. All walking path points are equally spaced to represent the equidistand samples of a walking path in a time-domain. The sampled walking path (measurement TAG positions) are included in a downloadable data set file under downloads section. # Folder structure Folder structure is represented below this text. Folder contains four subfolders named by the indoor environments measured during the measurement campaign and a folder raw_data where raw measurement data is saved. Each environment folder has a anchors.csv file with anchor names and locations, .json file data.json with measurements, file walking_path.csv file with tag positions and subfolder floorplan with floorplan.dxf (AutoCAD format), floorplan.png and floorplan_track.jpg. Subfolder raw_data contains raw data in subfolders named by the four indor environments where the measurements were taken. Each location subfolder contains a subfolder data where data from each tag position from the walking_path.csv is collected in a separate folder. There is exactly the same number of folders in data folder as is the number of measurement points in the walking_path.csv. Each measurement subfolder contains 48 .csv files named by communication channel and anchor used for those measurements. For example: ch1_A1.csv contains all measurements at selected tag location with anchor A1 on UWB channel ch1. The location folder contains also anchors.csv and walking_path.csv files which are identical to the files mentioned previously. The last folder in the data set is the technical_validation folder, where results of technical validation of the data set are collected. They are separated into 8 subfolders: - cir_min_max_mean - los_nlos - positioning_wls - range - range_error - range_error_A6 - range_error_histograms - rss The organization of the data set is the following: data_set + location0 - anchors.csv - data.json - walking_path.csv + floorplan - floorplan.dxf - floorplan.png - floorplan_track.jpg - walking_path.csv + location1 - ... + location2 - ... + location3 - ... + raw_data + location0 + data + 1.07_9.37_1.2 - ch1_A1.csv - ch7_A8.csv - ... + 1.37_9.34_1.2 - ... + ... + location1 + ... + location2 + ... + location3 + ... + technical validation + cir_min_max_mean + positioning_wls + range + range_error + range_error_histograms + rss - LICENSE - README # Data format Raw measurements are saved in .csv files. Each file starts with a header, where first line represents the version of the file and the second line represents the data column names. The column names have a missing column name. Actual column names included in the .csv files are: TAG_ID ANCHOR_ID X_TAG Y_TAG Z_TAG X_ANCHOR Y_ANCHOR Z_ANCHOR NLOS RANGE FP_INDEX RSS RSS_FP FP_POINT1 FP_POINT2 FP_POINT3 STDEV_NOISE CIR_POWER MAX_NOISE RXPACC CHANNEL_NUMBER FRAME_LENGTH PREAMBLE_LENGTH BITRATE PRFR PREAMBLE_CODE CIR (starts with this column; all columns until the end of the line represent the channel impulse response) # Availability of CODE Code for data analysis and preprocessing of all data available in this data set is published on GitHub: https://github.com/KlemenBr/uwb_positioning.git The code is licensed under the Apache License 2.0. # Authors and License Author of data set in this repository is Klemen Bregar, klemen.bregar@ijs.si. This work is licensed under a Creative Commons Attribution 4.0 International License. # Funding The research leading to the data collection has been partially funded from the European Horizon 2020 Programme project eWINE under grant agreement No. 688116, the Slovenian Research Agency under Grant numbers P2-0016, J2-2507 and bilateral project with Grant number BI-ME/21-22-007.