Analysis of Joint Radar and Communication in Disaster Scenarios

TL;DR

This paper investigates ad-hoc mesh joint radar and communication networks as a resilient, scalable, and energy-efficient solution for disaster management, capable of operating independently of traditional infrastructure to improve situational awareness and response.

Contribution

It introduces a novel joint radar and communication network architecture optimized for disaster scenarios, with an energy-efficient resource allocation scheme and performance evaluation metrics.

Findings

JRC networks improve target detection and communication under cluttered disaster environments.

The proposed optimization enhances energy efficiency in resource allocation.

Performance metrics indicate robust detection and communication capabilities.

Abstract

With the increasing frequency and intensity of natural disasters, there is a necessity for advanced technologies that can provide reliable situational awareness and communication. Conventional systems are often inadequate due to unreliable infrastructure, power grid failures, high investment costs and scalability challenges. This paper explores the potential of ad-hoc mesh joint radar and communication (JRC) networks as a scalable, resilient, energy-efficient solution for disaster management that can operate independently of conventional infrastructure. The proposed JRC network enhances disaster response by integrating target detection (such as identifying vital signs, hazardous leaks, and fires) with communication capabilities to ensure efficient information dissemination under intense clutter conditions. Key performance metrics, including data rate, Signal-to-Clutter and Noise Ratio (SCNR), probability of detection, and false alarm rate, are used to assess performance. An optimization approach is proposed to provide an energy-efficient resource allocation scheme. The results show the performance of ad-hoc mesh JRC systems, underscoring their potential to enhance disaster management efforts by addressing unique operational challenges.