Improve Sensing and Communication Performance of UAV via Integrated Sensing and Communication

TL;DR

This paper proposes an integrated sensing and communication (ISAC) approach for UAVs that enhances sensing accuracy and reduces communication delay by combining EKF-based data fusion and a novel IFF method, leading to significant performance improvements.

Contribution

It introduces a novel ISAC-based framework for UAVs that simultaneously improves sensing accuracy and communication efficiency through data fusion and parallel radar sensing and communication.

Findings

Communication delay reduced by up to 50%

Target sensing accuracy improved by 24.2%

Enhanced UAV sensing and communication performance

Abstract

The unmanned aerial vehicle (UAV) needs to sense the environment to ensure safe flight, and the sensing accuracy and communication delay performance are two important indicators of safe flight. The strategy of using integrated sensing and communication (ISAC) technology to improve the sensing and communication performance is proposed in this paper. On the one hand, the extended kalman filter (EKF) algorithm is adopted to achieve the fusion of communication location information and sensing information to improve the accuracy of target sensing. On the other hand, a Identification Friend or Foe (IFF) method based on ISAC is proposed to reduce communication delay. Compared with the traditional IFF method, the integrated technology used for IFF can realize the radar sensing and communication interrogating functions in parallel, greatly shortening the sensing time. Simulation results show that using ISAC technology, the sensing performance of UAV has been greatly improved, the communication delay can be reduced by up to 50%, the accuracy of target sensing can be improved by 24.2% when communication location information and radar sensing information have the same sensing accuracy.