GNSS/INS Semi-deep Integration with Federated Filtering for High Dynamic Vehicle

Baoyu Liu ； Xingqun Zhan ； Ming Liu ； Jinyu Liu

《Journal of Aeronautics, Astronautics and Aviation》 50卷3期 Vol.50 No.3 (2018/09) Pp. 223-235

https://doi.org/10.6125/JoAAA.201809_50(3).01

摘要

Deep integration of GNSS/INS is an advisable solution to improve high dynamic vehicle's navigation accuracy and reliability. The key feature of deep integration is that the navigation solution is fed back into receiver baseband to improve GNSS signal tracking performance. However, deeply integrating all-in-view satellites from multiple GNSS constellations with INS will lead to heavy computational burden and fault cross-infection among receiver channels. To address the issue, this paper investigates a federated filtering algorithm based semi-deep integration of GNSS/INS. The available GNSS signals are divided into two groups on the basis of the level of dynamics and C/N0 (Carrier-to-Noise Ratio). One group of the GNSS signals are deeply coupled with INS as traditional deep integration, the remaining signals are tracked without INS feedback but tightly coupled with INS. Estimates of these two group integrations are eventually fused by a federated filter with designed information-sharing coefficients. Thus, these two groups of GNSS signal tracking as well as INS can benefit from mutual assistance while the system enjoying less complexity and high fault tolerance. The scheme effectiveness is verified by a simulation case under high dynamic scenario. Results show that compared with traditional deep integration, the presented integration has competitive efficiency with little accuracy degradation and leads to an easier implementation and parameter tuning.

關鍵字

GNSS/INS ； Deep integration ； Tight integration ； Federated filtering ； High dynamics ； Computational complexity