自适应UKF在GNSS/INS紧组合导航中的应用研究

STUDY ON ADAPTIVE UNSCENTED KALMAN FILTER AND ITS APPLICATION TO GNSS /INS TIGHTLY COUPLED NAVIGATION

基于IAE滤波自适应估计算法,构造自适应无味卡尔曼滤波模型,利用模拟GNSS/INS组合导航平台,建立21状态紧组合导航模型,设计基于不同滤波模型的测试方案进行测试,结果表明:AUKF模型通过自适应估计原理能够抑制状态估计误差的影响,并能消除异常误差的出现,明显改善了导航系统的精度及可靠性,并且其执行效率并未受到影响;多卫星组合系统使定位精度提高了49.38%。

An Adaptive Unscented Kalman Filter （AUKF） model using Innovation -based Adaptive Estima- tion （IAE） is implemented. A 21-state filter using tightly coupled integration scheme is employed on the GNSS/ INS simulation platform, several test schemes are designed based on different filter models, the result shows that the AUKF model can restrain the influence of the state estimation errors for adaptive estimation, and reduce abnormal errors, the accuracy and reliability of navigation system are improved obviously, and it has no negative impact on the efficiency. The positioning precision of muhimode satellites systems increases by 49.38%.