机载航电系统中多源信息模糊自适应融合技术

Self-adaptive fusion technology based on multi-source information fuzzy reasoning in airborne avionics systems

为了保障导航的精度与可靠性,目前常采用多源信息融合导航。针对ADS/IRS/GPS组合导航系统,采用基于自适应信息分配的联邦滤波结构处理信息融合问题,并把模糊推理技术融入到ADS/IRS卡尔曼滤波器中,对IRS/GPS子滤波器采用紧组合模式,上述结构算法能对多源导航信息进行最优融合与处理。建立了ADS/IRS模糊自适应卡尔曼滤波模型以及IRS/GPS紧组合滤波模型,设计了自适应信息分配的联邦滤波算法,并进行了仿真,仿真结果验证了设计算法的有效性。

In order to ensure the accuracy and reliability of integrated navigation systems,the scheme of multi-source information fusion navigation is usually used.As for the navigation system integrated with inertial reference system（IRS）/ air data system（ADS）/ global positioning system（GPS）,a federal filter structure based on adaptive information distribution is adopted to deal with information fusion of multi-source system,the fuzzy reasoning technology is introduced into ADS/IRS Kalman filter,and the tight integrated mode is used for IRS/GPS filter.The optimal fusion and processing of multi-source navigation information can be done through the structure algorithm mentioned above.The fuzzy adaptive Kalman filtering model of ADS/IRS and tight integrated filtering model of IRS/GPS are built in this paper,and federal filtering algorithm based on adaptive information distribution is designed.The simulation is carried out based on above algorithms.The simulation results verify the effectiveness of the proposed tightly-coupled navigation algorithm integrated with ADS/IRS/GPS.