ANN-based LiDAR Positioning System for B5G

Author(s)

Neto, Egidio Raimundo ; Silva, Matheus Ferreira ; Sodre, Arismar Cerqueira

• Document type: Journal article
• Source: 2023 SBMO/IEEE MTT-S INTERNATIONAL MICROWAVE AND OPTOELECTRONICS CONFERENCE, IMOC; v. N/A, p. 3-pg., 2023-01-01.

Abstract

Accurate positioning and mapping are essential in telecommunications applications, but conventional methods, including the Global Positioning System (GPS), have limitations in indoor environments. This paper presents preliminary results on the effectiveness of using Light Detection and Ranging (LiDAR) for indoor positioning, specifically targeting beyond 5G (B5G) applications, with a focus on the integration of LiDAR in these networks. The proposed system utilizes a two-dimensional LiDAR sensor for data acquisition and digital filters for signal improvement. The proposed methodology involves object detection using LiDAR and camera fusion, employing an Artificial Neural Network (ANN) for people detection. We demonstrate person detection within a designated area, by harnessing the complementary strengths of LiDAR and camera technologies. (AU)

• FAPESP's process: 22/09319-9 - Center of Science for Development in Digital Agriculture - CCD-AD/SemeAr
• Grantee: Silvia Maria Fonseca Silveira Massruhá
• Support Opportunities: Research Grants - Science Centers for Development
• FAPESP's process: 21/06569-1 - High-speed strategic internet technologies
• Grantee: Evandro Conforti
• Support Opportunities: Research Projects - Thematic Grants