基于量测残差估计残差协方差的RAE-PEKF匹配算法

RAE-PEKF Matching Algorithm Based on Measurement Residuals to Estimate Residuals Covariance

地磁异常数据可以为水下潜器提供高隐蔽性的外部辅助信息,修正由惯性导航产生的累积误差。滤波匹配算法作为地磁辅助惯性导航中的核心技术,能够有效削弱地磁观测噪声不确定的影响。基于航迹仿真数据,将全球地磁异常格网数据作为基准图,提出使用量测残差自适应估计观测噪声方差的地磁异常并行扩展卡尔曼滤波匹配算法。通过建立一组基于地磁异常观测量的并行滤波器,结合最优滤波器选取准则来提高算法的可用性和鲁棒性。选取地磁特征分布不同的中国南海海域进行仿真匹配实验,结果表明,该算法能够有效降低纯惯性导航经纬向的匹配误差。仿真条件下,在地磁特征变化明显的区域,地磁辅助惯性导航系统的精度在纬度方向上提高至0.75153 n mile,在经度方向上提高至0.77845 n mile。

Geomagnetic matching technology can provide passive external resource of correction information for underwater vehicle,which improves the long voyage navigation accuracy of inertial navigation system.The filtering matching algorithm is the core technology in geomagnetic aided inertial navigation,which can effectively mitigate the influence from the uncertainty of geomagnetic observation noise.Based on track simulation data,the earth magnetic anomaly grid 2(EMAG2)is selected as reference map in this paper.To properly model the observation noise of geomagnetic anomaly in unpredictable geomagnetic environment and the error from measuring instruments,this paper proposes the matching algorithm of geomagnetic anomaly filter based on residual errors.The observation noise variance is estimated adaptively through the residual-based adaptive estimation(RAE)filter.Meanwhile,the availability and robustness of the algorithm are improved by combining the optimal filter selection criteria.The validation experiments of RAE filter are conducted in different maritime space of the South China Sea.It is shown that the drifting errors of inertial navigation system in longitude and latitude can be reduced based on the RAE filter.Moreover,the positioning accuracy and reliability of the aided navigation system can be improved significantly.In obvious geomagnetic fluctuating region under the simulation condition,position accuracy is raised to 0.75153 n mile and 0.77845 n mile respectively in latitude and longitude directions through RAE filter.