故障修复增强的抗差滤波PDR/GNSS行人导航方法

Robust filter-based PDR/GNSS pedestrian integration navigation approach enhanced by fault recovery

针对复杂环境下智能手机卫星信号容易受到干扰而引起组合导航精度降低的问题,提出一种基于故障修复的抗差滤波行人导航方法。该法首先利用等价权因子实时调整观测权值,以有效地减少观测粗差对组合导航精度的影响。其次,针对松组合系统没有观测冗余的模型局限性,将抗差扩展卡尔曼滤波检测区间分为无故障、偏离和异常3段。无故障时,不做处理;出现偏离时,对观测值进行降权处理;异常情况下,利用预测新息对故障进行幅值修复,进而修正观测值。实际实验结果表明,当GNSS出现单历元故障时,经典的抗差滤波方法能够有效提高智能手机PDR/GNSS组合导航定位精度,其北向最大误差由7.27 m减小为3.20 m,东向最大位置误差由24.01 m减小为6.60 m;在GNSS出现多历元连续故障时,所提出的故障修复增强的抗差滤波方法相比经典的抗差滤波方法的平均定位误差下降了50%以上。

In response to the challenge of diminished accuracy in integrated navigation for smartphones due to satellite signal interference in complex environments,this article proposes a robust extended Kalman filter enhanced by fault recovery.Firstly,this method uses equivalent weight factors to adjust observation weights in real-time,effectively reducing the impact of gross errors on combination navigation accuracy.Considering the low redundancy of observations in smartphone-based loosely-coupled navigation,this algorithm divides the detection range into three segments for fault-free,bias,and anomalies.In the absence of faults,no further processing is undertaken.When a deviation occurs,the observation value is reduced in weight.For anomalies,the predicted innovation is used to repair the fault amplitude and correct the observation value.Practical experimental results show that when a satellite experiences a single-epoch fault,the robust filter method can effectively improve the positioning accuracy of the smartphone PDR/GNSS combination navigation.The maximum error in the north direction is reduced from 7.27 m to 3.20 m,and the maximum position error in the east direction is reduced from 24.01 m to 6.60 m.In the case of multiple-epoch consecutive faults in GNSS positions,the proposed fault recovery-enhanced robust filter method shows an average reduction of over 50%in positioning error compared to the classical robust filter method.