Hierarchical Digital-Twin-Enhanced Cooperative Sensing for UAV Swarms
Longyu Zhou, Supeng Leng, Tony Q. S. Quek
Abstract
With the development of the future wireless communication technology and the Internet of Things (IoT), the digital twin (DT) system has become a new enabler for high-efficiency sensing in industrial applications. However, traditional DT designers may encounter a challenging situation for highly dynamic mobile entities in large-scale unmanned aerial vehicle (UAV) application scenarios. It has a direct influence on accurate and real-time sensing. To address the issue, we propose a hierarchical DT-enhanced cooperative sensing architecture. We proposed an intelligent DT model acquisition algorithm for real-time DT model construction. The accuracy of DT models is improved through our proposed model aggregation algorithm for accurate cooperative sensing. In addition, we propose a model transfer algorithm to perform a real-time cooperative sensing manner. We demonstrate the effectiveness of the proposed architecture using a multitarget tracking case study. The results show that our solution provides an accurate and real-time mobile sensing performance in the case study, with up to 90% sensing accuracy, under an acceptable system latency, compared to the traditional centralized and distributed DT manners.