An Improved INS Factor Graph Formulation and Its Application in Integrated Navigation System

Abstract

Abstract.A new method of establishing INS factor graph is proposed to deal with the serious waste of INS measurements in current integrated navigation factor graph algorithm. The INS observations pre-integrated to construct a smart factor during a time period, are used to solution simultaneously, to get the navigation states estimation. Then the estimated values can be used to construct an INS factor, adding into the INS factor graph. As a result, the new model is larger than the original, but the incremental inference technology makes sure the real-time ability of the factor graph algorithm. To analysis the performance of the proposed algorithm, INS and GNSS data are simulated, and the navigation position error of either the INS factors are added or not are compared. The results show that, the precision and stability of the factor graph algorithm are greatly improved by adding the INS factors. The proposed algorithm makes full use of the INS accuracy, and reflects the advantage of INS high stability.

A Moving Target Online Location Algorithm Based on Factor Graph

“…The factor graph [8][9][10] algorithm is an estimation algorithm based on Bayesian networks, which has shown good performance in many fields. For example, in the navigation problem, there are Wen et al in literature [11], Wei et al in literature [12], Gao et al in literature [13], Liu et al in literature [14], and Xu et al in literature [15], all of which use the factor graph algorithm instead of the Kalman filter algorithm. The factor graph algorithm offers superior performance while also ensuring good robustness.…”