Cooperative Terrain Navigation Using Hybrid GMM/SMC Message Passing on Factor Graphs

We introduce in this article a distributed factor-graph-based algorithm for anchorless cooperative aircraft localization in a GNSS-denied scenario without fixed infrastructure. The agents use terrain-aided navigation (TAN) to perform local position estimation and exchange messages to improve their position beliefs. Internode communication cost is reduced using a hybrid Gaussian mixture model / sequential Monte Carlo (GMM/SMC) approach. Simulation results show that, even in a partially connected network where only a small part of the agents perform TAN, cooperation yields better results than all aircraft performing TAN independently.