论文部分内容阅读
太阳能高空长航时无人机导航系统中,捷联惯导/北斗2κ全球卫星导航/星光导航(SINS/BD2/GPS/CNS)是一种可用的组合方案.针对常规容错组合导航算法故障检测类型单一,故障时滤波精度下降的问题,提出一种采用双状态卡方检验(TSPCST)和模糊自适应滤波(FAF)的容错组合导航算法.为了同时检测多种故障,将TSPCST应用于联邦滤波结构中;为了防止故障数据污染系统,利用FAF输出的高精度导航信息,对双状态传播器定期交替校正;进一步,FAF运用TSPCST检测得到的故障信息变量,定义量测子系统模糊有效域,将检测阈值模糊化,以弥补常规固定检测阈值算法难以选取阈值的不足;最后,通过计算信息分配因子,自适应处理多种故障数据.仿真结果表明,该容错组合导航算法性能优于常规固定检测阈值算法.
SINS / BD2 / GPS / CNS is a combinatorial scheme of SINS / BeiDou 2K global navigation satellite navigation (SINS / BD2 / GPS / CNS) .Aiming at the fault detection of conventional fault tolerant integrated navigation algorithm Type and fault filtering accuracy, a fault-tolerant integrated navigation algorithm using two-state chi-squared test (TSPCST) and fuzzy adaptive filtering (FAF) is proposed.In order to detect multiple faults at the same time, TSPCST is applied to federal filtering Structure; In order to prevent the fault data from polluting the system, FAF uses the high precision navigation information output to periodically and alternately calibrate the dual state propagator. Further, the FAF uses the fault information variables detected by TSPCST to define the fuzzy effective area of the measurement subsystem, The detection threshold is fuzzified so as to make up for the lack of thresholds that the traditional fixed detection threshold algorithm can not choose. Finally, a variety of fault data are adaptively processed by calculating the information distribution factor.The simulation results show that the performance of the fault tolerant integrated navigation algorithm is better than the conventional fixed detection threshold algorithm.