Hierarchical Digital-Twin-Enhanced Cooperative Sensing for UAV Swarms

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.