Please use this identifier to cite or link to this item:
https://dl.ucsc.cmb.ac.lk/jspui/handle/123456789/4909
Title: | Long Range Tomography for Outdoor Localization |
Authors: | Aaloka, S |
Issue Date: | 28-Jun-2025 |
Abstract: | Abstract The identification of the position of a human target in a given area of interest (AoI) is localization. When it comes to Radio Frequency (RF) based outdoor localization, the signals used have a limitation of short sensing range. LoRa is a technology that is used for long-range Internet of Things (IoT) communication, which has potential for long-range sensing and localization. The study suggests a mathematical model for LoRa-based long-range outdoor localization. The mathematical model is developed using the vectorization technique, where phase, amplitude, Received Signal Strength Indicator (RSSI), and statistical vectors are employed. The study was able to successfully perform outdoor localization with the data collected using the voxel grid. The amplitude vector-based mathematical model gives a 100% accuracy at 12m and 20m distances. The research discusses the effect of distance on localization using this mathematical model by experimenting at a distance of 12m and 20m. The research further provides insight about line of sight (LOS) and non-line of sight (NLOS) localization using the model. |
URI: | https://dl.ucsc.cmb.ac.lk/jspui/handle/123456789/4909 |
Appears in Collections: | 2025 |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
20000014 - H. D. S. Aaloka - sanduni aloka hewadewage.pdf | 5.3 MB | Adobe PDF | View/Open |
Items in UCSC Digital Library are protected by copyright, with all rights reserved, unless otherwise indicated.