Landing Guidance Based on Multi-Sensor Variational Bayesian Adaptive Fusion

Terminal landing requires reliable redundant guidance information fusion under asynchronous multi-rate measurements, communication delays, packet loss, and nonstationary noise with occasional outliers. This paper proposes an integrated framework that combines time alignment, integrated scheduling, and a robust variational Bayesian adaptive filter with anomaly score driven strong tracking. Three-point Lagrange interpolation with time backtracking is used for time registration, while the scheduling module unifies coordinate frames and manages repeated updates. Simulation comparisons with an interacting multiple model (IMM) baseline demonstrate improved fusion reliability in terminal landing conditions.