A Relative Navigation Integrity Monitoring Algorithm for UAV Swarm

Relative navigation provides relative position information for unmanned aerial vehicle (UAV) swarm. Accurate and reliable relative position information is vital to ensure the successful execution of cooperative tasks. Integrity monitoring (IM) is essential for assessing the reliability of relative position information. However, existing IM methods are unable to evaluate the availability of relative navigation systems in global navigation satellite system (GNSS)-denied environments. To address this challenge, a relative navigation integrity monitoring (RNIM) algorithm is proposed. The proposed algorithm employs Kalman filter innovation residuals to detect faults in relative time of arrival (TOA) measurements based on a relative state-space model. A novel relative protection level is introduced to evaluate the availability of relative navigation systems in GNSS-denied environments. Simulation results show that the proposed algorithm effectively detects and isolates faults in relative TOA measurements while accurately assessing relative navigation system availability.