Work

A Collaborative Navigation with Optimal Clustering for Multi-layer Swarm Systems

Year: 2026

Type: article

Abstract: This paper presents a cluster-optimized collaborative navigation method for large-scale multi-layer swarm systems, addressing challenges in global navigation satellite system (GNSS)-denied environments. The proposed approach divides the swarm into adaptive clusters, selecting cluster heads (CHs) based on optimized metrics to reduce communication load while maintaining navigation accuracy; it integrates a time difference of arrival (TDOA)/frequency difference of arrival (FDOA)-based collaborative navigation model for heterogeneous node coordination and employs a multi-dimensional scaling (MDS) algorithm for intra-cluster relative positioning and coordinate alignment. The system architecture features a three-layer structure consisting of reference nodes, intermediary nodes, and clustered nodes, enabling efficient resource utilization and robust navigation support. Experimental results demonstrate that the method substantially lowers the load while keeping a satisfactory navigation accuracy, facilitating reliable navigation in complex scenarios such as disaster response and intelligent logistics. This work provides theoretical and technical support for enhancing the adaptability and operational efficiency of large-scale multi-layer swarm systems.

Source: Guidance Navigation and Control

DOI: 10.1142/s2737480726500032

Authors: Rong Wang, Sichen Wang, Quyu Cong, Zhi Xiong, Yuxuan Liu

Institutions: Nanjing University of Aeronautics and Astronautics, China Electronics Technology Group Corporation

Language: English

Topic: Indoor and Outdoor Localization Technologies

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: diamond

Funder: National Natural Science Foundation of China