Target Detection in Challenging Environments: Photonic Radar with a Hybrid Multiplexing Scheme for 5G Autonomous Vehicles

Sushank Chaudhary (), Abhishek Sharma (), Muhammad Ali Naeem and Yahui Meng
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Sushank Chaudhary: School of Computer, Guangdong University of Petrochemical Technology, Maoming 525000, China
Abhishek Sharma: Department of Electronics Technology, Guru Nanak Dev University, Amritsar 143005, India
Muhammad Ali Naeem: School of Science, Guangdong University of Petrochemical Technology, Maoming 525000, China
Yahui Meng: School of Science, Guangdong University of Petrochemical Technology, Maoming 525000, China

Sustainability, 2024, vol. 16, issue 3, 1-15

Abstract: The rapid deployment of 5G autonomous vehicles has placed a premium on low-latency communication and reliable sensor technologies for the real-time mapping of road conditions, aligning with sustainability objectives in transport. In response to this imperative, photonic-based radar systems have emerged as an increasingly attractive solution, characterized by their low power consumption and cost-effectiveness. This study delves into the application of linear frequency-modulated continuous wave (FMCW) techniques within photonic radar sensors for the precise detection of multiple targets. Our proposed system seamlessly integrates mode-division multiplexing (MDM) and polarization-division multiplexing (PDM) to achieve a robust target detection capability, contributing to sustainable traffic management. To assess its effectiveness, we rigorously evaluated the system’s performance under challenging conditions, marked by a high atmospheric attenuation of 75 dB/km and a low material reflectivity of 20%. Our results unequivocally demonstrate the efficacy of the MDM-PDM photonic radar in successfully detecting all four specified targets, underscoring its potential to enhance road safety in the realm of autonomous vehicles. The adoption of this technology supports sustainable mobility by mitigating human errors and optimizing the real-time mapping of road conditions.

Keywords: autonomous vehicles; sustainable transport; photonic radar; material reflectivity; hybrid multiplexing schemes (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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