The invention relates to a multi-source
information fusion method based on a
factor graph. The multi-source
information fusion method aims to realize full-source positioning and navigation without relying on
satellite navigation in a complex environment, takes an
inertial navigation system as the core, utilizes all available navigation information sources, and performs rapid fusion, optimal configuration and self-
adaptive switching on asynchronous heterogeneous sensor information. A
factor graph model is constructed by means of recursive Bayesian
estimation, the
factor graph is broadened by means of a variable node and a factor node of the
system after measurement information of different sensors are acquired, state
recursion and updating are completed based on a set cost function, and thefactor
graph optimization problem is solved through sparse
QR decomposition by adopting an increment
smoothing method. The multi-source
information fusion method effectively solves the time-varying
state space problem generated between carrier motion and measurement availability, can calculate a solution of precise navigation according to dynamic changes of a carrying platform, realizes plug-and-play of multiple sensors, and meets the requirements of carriers changing in complex environment and different tasks.