Communication-Aware Distributed Estimation Over a Network of Aerial Vehicles
Ruihao Cao, Byoung-Ju Jeon, Shaoming He · IEEE Transactions on Instrumentation and Measurement · 2024
This paper investigates the problem of distributed estimation over a network of multiple aerial vehicles with limited communication bandwidth. By introducing the concept of partial update, a information weighted consensus filter with partial information exchange (ICF-PIE) is firstly designed to reduce the bandwidth of signals transmitted. In this algorithm, only a subset of information vector/matrix of each aerial vehicle node is selected to transmit to the locally connected nodes, deducing the communication burden. On this basis, the fixed-step consensus based information weighted consensus filter with partial information exchange (FS-ICF-PIE) is developed to further solve the ideal hypothesis of infinite consensus iterations at each time step, which is generally required in the consensus-based algorithms. Theoretical analysis reveals that the proposed distributed tracking algorithm can achieve convergence to the optimal centralized Kalman filter, while reducing the network communication bandwidth. Numerical simulations, as well as outdoor flight experiment, are relatively conducted to validate the effectiveness of proposed FS-ICF-PIE algorithm and the related theoretical findings.