A Cooperative GNSS Vector-DLL (CoVDLL) Method for Multiple UAVs Positioning - Chuntao Li; Xinru Wang; Changhui Jiang; Zikang Su; Shoubin Chen; Yuwei Chen (Remote Sensing, 2025)
Currently, the Global Navigation Satellite System (GNSS) plays a critical role in providing position information for UAVs. Traditional GNSS receivers typically employ the scalar-tracking (ST) method to track signals and extract observations. An advanced alternative to ST is the Vector Delay Lock Loop (VDLL), which enables more reliable navigation solution estimation for GNSS receivers. To enhance GNSS positioning performance for UAVs, this paper proposes a cooperative VDLL (CoVDLL) that incorporates ranging information. While single VDLL (S-VDLL) explores the inherent relationship between signal tracking parameters and navigation solutions, the CoVDLL leverages signal tracking parameters from multiple UAVs along with their ranging data. To optimize navigation solution estimation in the CoVDLL, a Factor Graph Optimization (FGO) algorithm is employed to realize the navigation solution’s optimal estimation. Experiments conducted under various settings demonstrate that the CoVDLL method reduces positioning errors by an average of approximately 30% compared to the single-VDLL approach.